From c6dd3569448d1e48ef673ac61b3390c1823aca2a Mon Sep 17 00:00:00 2001 From: dhuangnm <74931910+dhuangnm@users.noreply.github.com> Date: Wed, 31 Mar 2021 18:45:14 -0400 Subject: [PATCH] rebuild docs based on latest repos (#22) Co-authored-by: Jenkins --- deepsparse/.buildinfo | 2 +- deepsparse/_modules/deepsparse/engine.html | 14 +- .../_modules/deepsparse/utils/data.html | 45 +- .../numactl-utility.md.txt | 2 +- deepsparse/_static/doctools.js | 7 +- deepsparse/_static/language_data.js | 4 +- deepsparse/_static/pygments.css | 7 +- deepsparse/_static/searchtools.js | 26 +- deepsparse/_static/underscore.js | 37 +- deepsparse/api/deepsparse.html | 786 +------ deepsparse/api/deepsparse.utils.html | 103 +- deepsparse/api/modules.html | 20 +- .../debugging-optimizing/numactl-utility.html | 2 +- deepsparse/genindex.html | 337 --- deepsparse/index.html | 12 +- deepsparse/objects.inv | Bin 992 -> 506 bytes deepsparse/quicktour.html | 10 +- deepsparse/searchindex.js | 2 +- sparseml/_modules/index.html | 16 +- .../datasets/classification/imagefolder.html | 488 ++++ .../datasets/classification/imagenet.html | 366 +++ .../datasets/classification/imagenette.html | 314 +++ .../sparseml/keras/datasets/dataset.html | 332 +++ .../sparseml/keras/datasets/helpers.html | 310 +++ .../sparseml/keras/datasets/registry.html | 321 +++ .../keras/models/classification/resnet.html | 803 +++++++ .../sparseml/keras/models/registry.html | 565 +++++ .../sparseml/keras/optim/manager.html | 13 +- .../sparseml/keras/optim/mask_pruning.html | 124 +- .../keras/optim/mask_pruning_creator.html | 158 +- .../sparseml/keras/optim/modifier.html | 17 +- .../sparseml/keras/optim/modifier_lr.html | 43 +- .../sparseml/keras/optim/modifier_params.html | 9 +- .../keras/optim/modifier_pruning.html | 31 +- .../sparseml/keras/utils/callbacks.html | 11 +- .../_modules/sparseml/keras/utils/compat.html | 272 +++ .../sparseml/keras/utils/exporter.html | 16 +- .../_modules/sparseml/keras/utils/model.html | 15 +- .../sparseml/onnx/utils/graph_editor.html | 177 +- .../sparseml/onnx/utils/graph_optimizer.html | 98 +- .../_modules/sparseml/onnx/utils/helpers.html | 22 + .../_modules/sparseml/optim/modifier.html | 4 +- .../pytorch/models/detection/yolo_v3.html | 2 +- .../sparseml/pytorch/nn/activations.html | 51 +- .../pytorch/optim/modifier_quantization.html | 2 +- .../sparseml/pytorch/utils/callbacks.html | 345 +++ .../sparseml/pytorch/utils/exporter.html | 176 +- .../sparseml/pytorch/utils/helpers.html | 6 +- .../_modules/sparseml/pytorch/utils/loss.html | 2 +- .../sparseml/pytorch/utils/model.html | 36 +- .../quantization/helpers.html | 12 +- .../quantization/quantize_qat_export.html | 156 +- .../sparseml/utils/datasets/imagenette.html | 21 +- ...seml.keras.datasets.classification.rst.txt | 37 + .../api/sparseml.keras.datasets.rst.txt | 45 + ...arseml.keras.models.classification.rst.txt | 21 + .../sparseml.keras.models.external.rst.txt | 21 + .../api/sparseml.keras.models.rst.txt | 30 + sparseml/_sources/api/sparseml.keras.rst.txt | 2 + .../_sources/api/sparseml.keras.utils.rst.txt | 8 + .../api/sparseml.pytorch.optim.rst.txt | 8 - ...arseml.pytorch.utils.quantization.rst.txt} | 12 +- .../api/sparseml.pytorch.utils.rst.txt | 16 + .../api/sparseml.utils.datasets.rst.txt | 24 + sparseml/api/sparseml.html | 23 +- ...parseml.keras.datasets.classification.html | 496 ++++ sparseml/api/sparseml.keras.datasets.html | 403 ++++ sparseml/api/sparseml.keras.html | 45 +- .../sparseml.keras.models.classification.html | 462 ++++ .../api/sparseml.keras.models.external.html | 285 +++ sparseml/api/sparseml.keras.models.html | 431 ++++ sparseml/api/sparseml.keras.optim.html | 30 +- sparseml/api/sparseml.keras.utils.html | 16 +- sparseml/api/sparseml.onnx.utils.html | 179 +- ...rseml.pytorch.datasets.classification.html | 4 +- sparseml/api/sparseml.pytorch.html | 21 +- ...parseml.pytorch.models.classification.html | 4 +- sparseml/api/sparseml.pytorch.nn.html | 28 +- sparseml/api/sparseml.pytorch.optim.html | 18 +- sparseml/api/sparseml.pytorch.utils.html | 178 +- ... sparseml.pytorch.utils.quantization.html} | 85 +- ...tensorflow_v1.datasets.classification.html | 4 +- sparseml/api/sparseml.tensorflow_v1.html | 4 +- ...l.tensorflow_v1.models.classification.html | 2 +- sparseml/api/sparseml.utils.datasets.html | 9 + sparseml/api/sparseml.utils.html | 3 + sparseml/genindex.html | 519 ++++- sparseml/objects.inv | Bin 12209 -> 12954 bytes sparseml/py-modindex.html | 123 +- sparseml/searchindex.js | 2 +- .../sparsezoo/requests/authentication.html | 6 +- .../_modules/sparsezoo/requests/base.html | 14 +- .../_modules/sparsezoo/requests/download.html | 15 +- .../_modules/sparsezoo/requests/search.html | 6 +- .../_modules/sparsezoo/utils/helpers.html | 15 +- sparsezoo/_static/underscore-1.3.1.js | 999 --------- sparsezoo/api/sparsezoo.utils.html | 13 + sparsezoo/genindex.html | 6 +- sparsezoo/objects.inv | Bin 2193 -> 2204 bytes sparsezoo/searchindex.js | 2 +- sparsify/.buildinfo | 2 +- sparsify/_static/doctools.js | 7 +- sparsify/_static/language_data.js | 4 +- sparsify/_static/pygments.css | 7 +- sparsify/_static/searchtools.js | 26 +- sparsify/_static/underscore.js | 37 +- sparsify/api/modules.html | 92 +- .../api/sparsify.blueprints.code_samples.html | 49 +- sparsify/api/sparsify.blueprints.html | 109 +- sparsify/api/sparsify.blueprints.utils.html | 574 +---- sparsify/api/sparsify.html | 169 +- sparsify/api/sparsify.models.html | 1570 +------------ sparsify/api/sparsify.schemas.html | 1372 +----------- sparsify/api/sparsify.utils.html | 53 +- sparsify/api/sparsify.workers.html | 762 +------ sparsify/genindex.html | 1990 ----------------- sparsify/index.html | 6 +- sparsify/objects.inv | Bin 4793 -> 723 bytes sparsify/searchindex.js | 2 +- 119 files changed, 8977 insertions(+), 9278 deletions(-) create mode 100644 sparseml/_modules/sparseml/keras/datasets/classification/imagefolder.html create mode 100644 sparseml/_modules/sparseml/keras/datasets/classification/imagenet.html create mode 100644 sparseml/_modules/sparseml/keras/datasets/classification/imagenette.html create mode 100644 sparseml/_modules/sparseml/keras/datasets/dataset.html create mode 100644 sparseml/_modules/sparseml/keras/datasets/helpers.html create mode 100644 sparseml/_modules/sparseml/keras/datasets/registry.html create mode 100644 sparseml/_modules/sparseml/keras/models/classification/resnet.html create mode 100644 sparseml/_modules/sparseml/keras/models/registry.html create mode 100644 sparseml/_modules/sparseml/keras/utils/compat.html create mode 100644 sparseml/_modules/sparseml/pytorch/utils/callbacks.html rename sparseml/_modules/sparseml/pytorch/{optim => utils}/quantization/helpers.html (98%) rename sparseml/_modules/sparseml/pytorch/{optim => utils}/quantization/quantize_qat_export.html (84%) create mode 100644 sparseml/_sources/api/sparseml.keras.datasets.classification.rst.txt create mode 100644 sparseml/_sources/api/sparseml.keras.datasets.rst.txt create mode 100644 sparseml/_sources/api/sparseml.keras.models.classification.rst.txt create mode 100644 sparseml/_sources/api/sparseml.keras.models.external.rst.txt create mode 100644 sparseml/_sources/api/sparseml.keras.models.rst.txt rename sparseml/_sources/api/{sparseml.pytorch.optim.quantization.rst.txt => sparseml.pytorch.utils.quantization.rst.txt} (53%) create mode 100644 sparseml/api/sparseml.keras.datasets.classification.html create mode 100644 sparseml/api/sparseml.keras.datasets.html create mode 100644 sparseml/api/sparseml.keras.models.classification.html create mode 100644 sparseml/api/sparseml.keras.models.external.html create mode 100644 sparseml/api/sparseml.keras.models.html rename sparseml/api/{sparseml.pytorch.optim.quantization.html => sparseml.pytorch.utils.quantization.html} (76%) delete mode 100644 sparsezoo/_static/underscore-1.3.1.js diff --git a/deepsparse/.buildinfo b/deepsparse/.buildinfo index be20e0084e9..3b04e9d0c59 100644 --- a/deepsparse/.buildinfo +++ b/deepsparse/.buildinfo @@ -1,4 +1,4 @@ # Sphinx build info version 1 # This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done. -config: 09cf2dae090a5215faeb91fd805fe11e +config: c0e84c5bd7f1ae1547decebf78328f3b tags: 645f666f9bcd5a90fca523b33c5a78b7 diff --git a/deepsparse/_modules/deepsparse/engine.html b/deepsparse/_modules/deepsparse/engine.html index efde5367144..2504d1c7af4 100644 --- a/deepsparse/_modules/deepsparse/engine.html +++ b/deepsparse/_modules/deepsparse/engine.html @@ -303,9 +303,6 @@

Source code for deepsparse.engine

     Note 1: Engines are compiled for a specific batch size and
     for a specific number of CPU cores.
 
-    Note 2: multi socket support is not yet built in to the Engine,
-    all execution assumes single socket
-
     | Example:
     |    # create an engine for batch size 1 on all available cores
     |    engine = Engine("path/to/onnx", batch_size=1, num_cores=None)
@@ -405,8 +402,7 @@ 
Source code for deepsparse.engine
     @property
     def num_sockets(self) -> int:
         """
-        :return: The number of sockets the engine is compiled to run on;
-            only current support is 1
+        :return: The number of sockets the engine is compiled to run on
         """
         return self._num_sockets
 
@@ -682,8 +678,8 @@ 
Source code for deepsparse.engine
     """
     Convenience function to compile a model in the DeepSparse Engine
     from an ONNX file for inference.
-    Gives defaults of batch_size == 1 and num_cores == None
-    (will use all physical cores available on a single socket).
+    Gives defaults of batch_size == 1, num_cores == None and num_sockets = None
+    (will use all physical cores available on all available sockets).
 
     :param model: Either a path to the model's onnx file, a SparseZoo model stub
         prefixed by 'zoo:', a SparseZoo Model object, or a SparseZoo ONNX File
@@ -718,6 +714,8 @@ 
Source code for deepsparse.engine
     Gives defaults of batch_size == 1 and num_cores == None
     (will use all physical cores available on a single socket).
 
+    Note 1: Benchmarking is currently only supported on a single socket.
+
     :param model: Either a path to the model's onnx file, a SparseZoo model stub
         prefixed by 'zoo:', a SparseZoo Model object, or a SparseZoo ONNX File
         object that defines the neural network
@@ -773,6 +771,8 @@ 
Source code for deepsparse.engine
     Gives defaults of batch_size == 1 and num_cores == None
     (will use all physical cores available on a single socket).
 
+    Note 1: Analysis is currently only supported on a single socket.
+
     :param model: Either a path to the model's onnx file, a SparseZoo model stub
         prefixed by 'zoo:', a SparseZoo Model object, or a SparseZoo ONNX File
         object that defines the neural network graph definition to analyze
diff --git a/deepsparse/_modules/deepsparse/utils/data.html b/deepsparse/_modules/deepsparse/utils/data.html
index 2181838b3e0..f6c186ca286 100644
--- a/deepsparse/_modules/deepsparse/utils/data.html
+++ b/deepsparse/_modules/deepsparse/utils/data.html
@@ -201,11 +201,54 @@ 
Source code for deepsparse.utils.data
 from deepsparse.utils.log import log_init
 
 
-__all__ = ["verify_outputs"]
+__all__ = [
+    "arrays_to_bytes",
+    "bytes_to_arrays",
+    "verify_outputs",
+]
 
 log = log_init(os.path.basename(__file__))
 
 
+
[docs]def arrays_to_bytes(arrays: List[numpy.array]) -> bytearray:
+    """
+    :param arrays: List of numpy arrays to serialize as bytes
+    :return: bytearray representation of list of numpy arrays
+    """
+    to_return = bytearray()
+    for arr in arrays:
+        arr_dtype = bytearray(str(arr.dtype), "utf-8")
+        arr_shape = bytearray(",".join([str(a) for a in arr.shape]), "utf-8")
+        sep = bytearray("|", "utf-8")
+        arr_bytes = arr.ravel().tobytes()
+        to_return += arr_dtype + sep + arr_shape + sep + arr_bytes
+    return to_return

+
+
+
[docs]def bytes_to_arrays(serialized_arr: bytearray) -> List[numpy.array]:
+    """
+    :param serialized_arr: bytearray representation of list of numpy arrays
+    :return: List of numpy arrays decoded from input
+    """
+    sep = "|".encode("utf-8")
+    arrays = []
+    i_start = 0
+    while i_start < len(serialized_arr) - 1:
+        i_0 = serialized_arr.find(sep, i_start)
+        i_1 = serialized_arr.find(sep, i_0 + 1)
+        arr_dtype = numpy.dtype(serialized_arr[i_start:i_0].decode("utf-8"))
+        arr_shape = tuple(
+            [int(a) for a in serialized_arr[i_0 + 1 : i_1].decode("utf-8").split(",")]
+        )
+        arr_num_bytes = numpy.prod(arr_shape) * arr_dtype.itemsize
+        arr_str = serialized_arr[i_1 + 1 : arr_num_bytes + (i_1 + 1)]
+        arr = numpy.frombuffer(arr_str, dtype=arr_dtype).reshape(arr_shape)
+        arrays.append(arr.copy())
+
+        i_start = i_1 + arr_num_bytes + 1
+    return arrays

+
+
 
[docs]def verify_outputs(
     outputs: List[numpy.array],
     gt_outputs: List[numpy.array],
diff --git a/deepsparse/_sources/debugging-optimizing/numactl-utility.md.txt b/deepsparse/_sources/debugging-optimizing/numactl-utility.md.txt
index 86bf11ef32d..2c0e1a4b00e 100644
--- a/deepsparse/_sources/debugging-optimizing/numactl-utility.md.txt
+++ b/deepsparse/_sources/debugging-optimizing/numactl-utility.md.txt
@@ -52,7 +52,7 @@ Given the architecture above, to run the DeepSparse Engine on the first four CPU
 
 Appending `--preferred 1` is needed here since the DeepSparse Engine is being bound to CPUs on the second socket.
 
-Note that using more than two sockets may not offer improvements over two sockets; if you have options, try different scenarios to see which setup is ideal for your use case. For batch size considerations, use an amount that is evenly divisible by the number of sockets you intend to use.
+Note: When running on multiple sockets using a batch size that is evenly divisible by the number of sockets will yield the best performance.
 
 
 ## DeepSparse Engine and Thread Pinning
diff --git a/deepsparse/_static/doctools.js b/deepsparse/_static/doctools.js
index 61ac9d266f9..144884ea651 100644
--- a/deepsparse/_static/doctools.js
+++ b/deepsparse/_static/doctools.js
@@ -29,14 +29,9 @@ if (!window.console || !console.firebug) {
 
 /**
  * small helper function to urldecode strings
- *
- * See https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/decodeURIComponent#Decoding_query_parameters_from_a_URL
  */
 jQuery.urldecode = function(x) {
-  if (!x) {
-    return x
-  }
-  return decodeURIComponent(x.replace(/\+/g, ' '));
+  return decodeURIComponent(x).replace(/\+/g, ' ');
 };
 
 /**
diff --git a/deepsparse/_static/language_data.js b/deepsparse/_static/language_data.js
index 863704b310d..0e7dc7e9ef0 100644
--- a/deepsparse/_static/language_data.js
+++ b/deepsparse/_static/language_data.js
@@ -13,8 +13,7 @@
 var stopwords = ["a","and","are","as","at","be","but","by","for","if","in","into","is","it","near","no","not","of","on","or","such","that","the","their","then","there","these","they","this","to","was","will","with"];
 
 
-/* Non-minified version is copied as a separate JS file, is available */
-
+/* Non-minified version JS is _stemmer.js if file is provided */ 
 /**
  * Porter Stemmer
  */
@@ -200,6 +199,7 @@ var Stemmer = function() {
 
 
 
+
 var splitChars = (function() {
     var result = {};
     var singles = [96, 180, 187, 191, 215, 247, 749, 885, 903, 907, 909, 930, 1014, 1648,
diff --git a/deepsparse/_static/pygments.css b/deepsparse/_static/pygments.css
index 691aeb82d00..20c4814dcf0 100644
--- a/deepsparse/_static/pygments.css
+++ b/deepsparse/_static/pygments.css
@@ -1,10 +1,5 @@
-pre { line-height: 125%; }
-td.linenos .normal { color: inherit; background-color: transparent; padding-left: 5px; padding-right: 5px; }
-span.linenos { color: inherit; background-color: transparent; padding-left: 5px; padding-right: 5px; }
-td.linenos .special { color: #000000; background-color: #ffffc0; padding-left: 5px; padding-right: 5px; }
-span.linenos.special { color: #000000; background-color: #ffffc0; padding-left: 5px; padding-right: 5px; }
 .highlight .hll { background-color: #ffffcc }
-.highlight { background: #eeffcc; }
+.highlight  { background: #eeffcc; }
 .highlight .c { color: #408090; font-style: italic } /* Comment */
 .highlight .err { border: 1px solid #FF0000 } /* Error */
 .highlight .k { color: #007020; font-weight: bold } /* Keyword */
diff --git a/deepsparse/_static/searchtools.js b/deepsparse/_static/searchtools.js
index 1a90152eb0e..6fc9e7f3338 100644
--- a/deepsparse/_static/searchtools.js
+++ b/deepsparse/_static/searchtools.js
@@ -248,7 +248,7 @@ var Search = {
       // results left, load the summary and display it
       if (results.length) {
         var item = results.pop();
-        var listItem = $('
  • ');
+        var listItem = $('
  • ');
         var requestUrl = "";
         var linkUrl = "";
         if (DOCUMENTATION_OPTIONS.BUILDER === 'dirhtml') {
@@ -273,9 +273,9 @@ var Search = {
         if (item[3]) {
           listItem.append($(' (' + item[3] + ')'));
           Search.output.append(listItem);
-          setTimeout(function() {
+          listItem.slideDown(5, function() {
             displayNextItem();
-          }, 5);
+          });
         } else if (DOCUMENTATION_OPTIONS.HAS_SOURCE) {
           $.ajax({url: requestUrl,
                   dataType: "text",
@@ -285,16 +285,16 @@ var Search = {
                       listItem.append(Search.makeSearchSummary(data, searchterms, hlterms));
                     }
                     Search.output.append(listItem);
-                    setTimeout(function() {
+                    listItem.slideDown(5, function() {
                       displayNextItem();
-                    }, 5);
+                    });
                   }});
         } else {
           // no source available, just display title
           Search.output.append(listItem);
-          setTimeout(function() {
+          listItem.slideDown(5, function() {
             displayNextItem();
-          }, 5);
+          });
         }
       }
       // search finished, update title and status message
@@ -379,13 +379,6 @@ var Search = {
     return results;
   },
 
-  /**
-   * See https://developer.mozilla.org/en-US/docs/Web/JavaScript/Guide/Regular_Expressions
-   */
-  escapeRegExp : function(string) {
-    return string.replace(/[.*+\-?^${}()|[\]\\]/g, '\\$&'); // $& means the whole matched string
-  },
-
   /**
    * search for full-text terms in the index
    */
@@ -409,14 +402,13 @@ var Search = {
       ];
       // add support for partial matches
       if (word.length > 2) {
-        var word_regex = this.escapeRegExp(word);
         for (var w in terms) {
-          if (w.match(word_regex) && !terms[word]) {
+          if (w.match(word) && !terms[word]) {
             _o.push({files: terms[w], score: Scorer.partialTerm})
           }
         }
         for (var w in titleterms) {
-          if (w.match(word_regex) && !titleterms[word]) {
+          if (w.match(word) && !titleterms[word]) {
               _o.push({files: titleterms[w], score: Scorer.partialTitle})
           }
         }
diff --git a/deepsparse/_static/underscore.js b/deepsparse/_static/underscore.js
index 166240ef2dd..5b55f32beac 100644
--- a/deepsparse/_static/underscore.js
+++ b/deepsparse/_static/underscore.js
@@ -1,6 +1,31 @@
-!function(n,r){"object"==typeof exports&&"undefined"!=typeof module?module.exports=r():"function"==typeof define&&define.amd?define("underscore",r):(n=n||self,function(){var t=n._,e=n._=r();e.noConflict=function(){return n._=t,e}}())}(this,(function(){
-//     Underscore.js 1.12.0
-//     https://underscorejs.org
-//     (c) 2009-2020 Jeremy Ashkenas, DocumentCloud and Investigative Reporters & Editors
-//     Underscore may be freely distributed under the MIT license.
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diff --git a/deepsparse/api/deepsparse.html b/deepsparse/api/deepsparse.html
index d773343e328..3943902ee2e 100644
--- a/deepsparse/api/deepsparse.html
+++ b/deepsparse/api/deepsparse.html
@@ -114,12 +114,12 @@
 
 
 
  • Submodules
    • 
-
  • deepsparse.benchmark module
    • 
-
  • deepsparse.cpu module
    • 
-
  • deepsparse.engine module
    • 
-
  • deepsparse.lib module
    • 
-
  • deepsparse.version module
    • 
-
  • Module contents
    • 
+
  • deepsparse.benchmark module
    • 
+
  • deepsparse.cpu module
    • 
+
  • deepsparse.engine module
    • 
+
  • deepsparse.lib module
    • 
+
  • deepsparse.version module
    • 
+
  • Module contents
    • 
 
 
 
@@ -203,10 +203,10 @@ 
    Subpackagesdeepsparse.utils package
 
 
@@ -215,765 +215,23 @@ 
    Subpackages
 
    SubmodulesΒΆ
    
 
    
-
    
-
    deepsparse.benchmark moduleΒΆ
    
-
    Code related to benchmarking batched inference runs
    
-
    
-
    
-class deepsparse.benchmark.BatchBenchmarkResult(time_start: float, time_end: float, batch_size: int, inputs: Union[None, List[numpy.ndarray]] = None, outputs: Union[None, List[numpy.ndarray], Dict[str, numpy.ndarray]] = None, extras: Optional[Any] = None)[source]ΒΆ
    
-
    Bases: object
    
-
    A benchmark result for a batched inference run
    
-
    
-
    Parameters
    
-
      
-
    • time_start – The system time when the run for the batch was started
      • 
-
    • time_end – The system time when the run for the batch ended
      • 
-
    • batch_size – The size of the batch that was benchmarked
      • 
-
    • inputs – Optional batch inputs that were given for the run
      • 
-
    • outputs – Optional batch outputs that were given for the run
      • 
-
    • extras – Optional batch extras to store any other data for the run
      • 
-
    
-
    
-
    
-
    
-
    
-property batch_sizeΒΆ
    
-
    The size of the batch that was benchmarked
    
-
    
-
    Type
    
-
    return
    
-
    
-
    
-
    
-
-
    
-
    
-property batches_per_secondΒΆ
    
-
    The number of batches that could be run in one second
-based on this result
    
-
    
-
    Type
    
-
    return
    
-
    
-
    
-
    
-
-
    
-
    
-property extrasΒΆ
    
-
    Batch extras to store any other data for the run
    
-
    
-
    Type
    
-
    return
    
-
    
-
    
-
    
-
-
    
-
    
-property inputsΒΆ
    
-
    Batch inputs that were given for the run, if any
    
-
    
-
    Type
    
-
    return
    
-
    
-
    
-
    
-
-
    
-
    
-property items_per_secondΒΆ
    
-
    The number of items that could be run in one second
-based on this result
    
-
    
-
    Type
    
-
    return
    
-
    
-
    
-
    
-
-
    
-
    
-property ms_per_batchΒΆ
    
-
    The number of milliseconds it took to run the batch
    
-
    
-
    Type
    
-
    return
    
-
    
-
    
-
    
-
-
    
-
    
-property ms_per_itemΒΆ
    
-
    The averaged number of milliseconds it took to run each item
-in the batch
    
-
    
-
    Type
    
-
    return
    
-
    
-
    
-
    
-
-
    
-
    
-property outputsΒΆ
    
-
    Batch outputs that were given for the run, if any
    
-
    
-
    Type
    
-
    return
    
-
    
-
    
-
    
-
-
    
-
    
-property time_elapsedΒΆ
    
-
    The time elapsed for the entire run (end - start)
    
-
    
-
    Type
    
-
    return
    
-
    
-
    
-
    
-
-
    
-
    
-property time_endΒΆ
    
-
    The system time when the run for the batch ended
    
-
    
-
    Type
    
-
    return
    
-
    
-
    
-
    
-
-
    
-
    
-property time_startΒΆ
    
-
    The system time when the run for the batch was started
    
-
    
-
    Type
    
-
    return
    
-
    
-
    
-
    
-
-
    
-
-
    
-
    
-class deepsparse.benchmark.BenchmarkResults[source]ΒΆ
    
-
    Bases: Iterable
    
-
    The benchmark results for a list of batched inference runs
    
-
    
-
    
-append_batch(time_start: float, time_end: float, batch_size: int, inputs: Union[None, List[numpy.ndarray]] = None, outputs: Union[None, List[numpy.ndarray], Dict[str, numpy.ndarray]] = None, extras: Optional[Any] = None)[source]ΒΆ
    
-
    Add a recorded batch to the current results
    
-
    
-
    Parameters
    
-
      
-
    • time_start – The system time when the run for the batch was started
      • 
-
    • time_end – The system time when the run for the batch ended
      • 
-
    • batch_size – The size of the batch that was benchmarked
      • 
-
    • inputs – Optional batch inputs that were given for the run
      • 
-
    • outputs – Optional batch outputs that were given for the run
      • 
-
    • extras – Optional batch extras to store any other data for the run
      • 
-
    
-
    
-
    
-
    
-
-
    
-
    
-property batch_sizesΒΆ
    
-
    the list of all batch run sizes that have been added
    
-
    
-
    Type
    
-
    return
    
-
    
-
    
-
    
-
-
    
-
    
-property batch_timesΒΆ
    
-
    the list of all batch run times that have been added
    
-
    
-
    Type
    
-
    return
    
-
    
-
    
-
    
-
-
    
-
    
-property batch_times_meanΒΆ
    
-
    the mean of all the batch run times that have been added
    
-
    
-
    Type
    
-
    return
    
-
    
-
    
-
    
-
-
    
-
    
-property batch_times_medianΒΆ
    
-
    the median of all the batch run times that have been added
    
-
    
-
    Type
    
-
    return
    
-
    
-
    
-
    
-
-
    
-
    
-property batch_times_stdΒΆ
    
-
    the standard deviation of all the batch run times that have been added
    
-
    
-
    Type
    
-
    return
    
-
    
-
    
-
    
-
-
    
-
    
-property batches_per_secondΒΆ
    
-
    The number of batches that could be run in one second
-based on this result
    
-
    
-
    Type
    
-
    return
    
-
    
-
    
-
    
-
-
    
-
    
-property inputsΒΆ
    
-
    Batch inputs that were given for the run, if any
    
-
    
-
    Type
    
-
    return
    
-
    
-
    
-
    
-
-
    
-
    
-property items_per_secondΒΆ
    
-
    The number of items that could be run in one second
-based on this result
    
-
    
-
    Type
    
-
    return
    
-
    
-
    
-
    
-
-
    
-
    
-property ms_per_batchΒΆ
    
-
    The number of milliseconds it took to run the batch
    
-
    
-
    Type
    
-
    return
    
-
    
-
    
-
    
-
-
    
-
    
-property ms_per_itemΒΆ
    
-
    The averaged number of milliseconds it took to run each item
-in the batch
    
-
    
-
    Type
    
-
    return
    
-
    
-
    
-
    
-
-
    
-
    
-property num_batchesΒΆ
    
-
    the number of batches that have been added
    
-
    
-
    Type
    
-
    return
    
-
    
-
    
-
    
-
-
    
-
    
-property num_itemsΒΆ
    
-
    the number of items across all batches that have been added
    
-
    
-
    Type
    
-
    return
    
-
    
-
    
-
    
-
-
    
-
    
-property outputsΒΆ
    
-
    Batch outputs that were given for the run, if any
    
-
    
-
    Type
    
-
    return
    
-
    
-
    
-
    
-
-
    
-
    
-property resultsΒΆ
    
-
    the list of recorded batch results
    
-
    
-
    Type
    
-
    return
    
-
    
-
    
-
    
-
-
    
-
-
    
-
    
-
    deepsparse.cpu moduleΒΆ
    
-
    code related to detecting the details of the currently available cpu
    
-
    
-
    
-deepsparse.cpu.cpu_details() → Tuple[int, str, bool][source]ΒΆ
    
-
    Detect the CPU details on linux systems
-If any other OS is used, will raise an exception
    
-
    
-
    Specifically:
      
-
    • the number of physical cores available per socket on the system
      • 
-
    • detects the vector instruction set available (avx2, avx512)
      • 
-
    • if vnni is available
      • 
-
    
-
    
-
    
-
    NM_ARCH environment variable can be used to override the avx instruction set detection
    
-
    
-
    Returns
    
-
    a tuple containing the detected cpu information
-(number of physical cores per socket, avx instruction set, vnni support)
    
-
    
-
    
-
    
-
+
    
+
    deepsparse.benchmark moduleΒΆ
    
 
    
-
    
-
    deepsparse.engine moduleΒΆ
    
-
    Code related to interfacing with a Neural Network in the DeepSparse Engine using python
    
-
    
-
    
-class deepsparse.engine.Engine(model: Union[str, sparsezoo.objects.model.Model, sparsezoo.objects.file.File], batch_size: int, num_cores: int, num_sockets: Optional[int] = None)[source]ΒΆ
    
-
    Bases: object
    
-
    Create a new DeepSparse Engine that compiles the given onnx file
-for GPU class performance on commodity CPUs.
    
-
    Note 1: Engines are compiled for a specific batch size and
-for a specific number of CPU cores.
    
-
    Note 2: multi socket support is not yet built in to the Engine,
-all execution assumes single socket
    
-
    
-
    Example:
    
-
    
-
    # create an engine for batch size 1 on all available cores
    
-
    engine = Engine(β€œpath/to/onnx”, batch_size=1, num_cores=None)
    
+
    
+
    deepsparse.cpu moduleΒΆ
    
 
    
+
    
+
    deepsparse.engine moduleΒΆ
    
 
    
-
    
-
    Parameters
    
-
      
-
    • model – Either a path to the model’s onnx file, a SparseZoo model stub
-prefixed by β€˜zoo:’, a SparseZoo Model object, or a SparseZoo ONNX File
-object that defines the neural network
      • 
-
    • batch_size – The batch size of the inputs to be used with the engine
      • 
-
    • num_cores – The number of physical cores to run the model on.
-Pass None or 0 to run on the max number of cores
-in one socket for the current machine, default None
      • 
-
    • num_sockets – The number of physical sockets to run the model on.
-Pass None or 0 to run on the max number of sockets for the
-current machine, default None
      • 
-
    
-
    
-
    
-
    
-
    
-property batch_sizeΒΆ
    
-
    The batch size of the inputs to be used with the model
    
-
    
-
    Type
    
-
    return
    
-
    
-
    
-
    
-
-
    
-
    
-benchmark(inp: List[numpy.ndarray], num_iterations: int = 20, num_warmup_iterations: int = 5, include_inputs: bool = False, include_outputs: bool = False, show_progress: bool = False) → deepsparse.benchmark.BenchmarkResults[source]ΒΆ
    
-
    A convenience function for quickly benchmarking the instantiated model
-on a given input in the DeepSparse Engine.
-After executing, will return the summary statistics for benchmarking.
    
-
    
-
    Parameters
    
-
      
-
    • inp – The list of inputs to pass to the engine for benchmarking.
-The expected order is the inputs order as defined in the ONNX graph.
      • 
-
    • num_iterations – The number of iterations to run benchmarking for.
-Default is 20
      • 
-
    • num_warmup_iterations – T number of iterations to warm up engine before
-benchmarking. These executions will not be counted in the benchmark
-results that are returned. Useful and recommended to bring
-the system to a steady state. Default is 5
      • 
-
    • include_inputs – If True, inputs from forward passes during benchmarking
-will be added to the results. Default is False
      • 
-
    • include_outputs – If True, outputs from forward passes during benchmarking
-will be added to the results. Default is False
      • 
-
    • show_progress – If True, will display a progress bar. Default is False
      • 
-
    
-
    
-
    Returns
    
-
    the results of benchmarking
    
-
    
-
    
-
    
-
-
    
-
    
-benchmark_loader(loader: Iterable[List[numpy.ndarray]], num_iterations: int = 20, num_warmup_iterations: int = 5, include_inputs: bool = False, include_outputs: bool = False, show_progress: bool = False) → deepsparse.benchmark.BenchmarkResults[source]ΒΆ
    
-
    A convenience function for quickly benchmarking the instantiated model
-on a give DataLoader in the DeepSparse Engine.
-After executing, will return the summary statistics for benchmarking.
    
-
    
-
    Parameters
    
-
      
-
    • loader – An iterator of inputs to pass to the engine for benchmarking.
-The expected order of each input is as defined in the ONNX graph.
      • 
-
    • num_iterations – The number of iterations to run benchmarking for.
-Default is 20
      • 
-
    • num_warmup_iterations – T number of iterations to warm up engine before
-benchmarking. These executions will not be counted in the benchmark
-results that are returned. Useful and recommended to bring
-the system to a steady state. Default is 5
      • 
-
    • include_inputs – If True, inputs from forward passes during benchmarking
-will be added to the results. Default is False
      • 
-
    • include_outputs – If True, outputs from forward passes during benchmarking
-will be added to the results. Default is False
      • 
-
    • show_progress – If True, will display a progress bar. Default is False
      • 
-
    
-
    
-
    Returns
    
-
    the results of benchmarking
    
-
    
-
    
-
    
-
-
    
-
    
-property cpu_avx_typeΒΆ
    
-
    The detected cpu avx type that neural magic is running with.
-One of {avx2, avx512}. AVX instructions give significant execution speedup
-with avx512 > avx2.
    
-
    
-
    Type
    
-
    return
    
-
    
-
    
-
    
-
-
    
-
    
-property cpu_vnniΒΆ
    
-
    True if vnni support was detected on the cpu, False otherwise.
-VNNI gives performance benefits for quantized networks.
    
-
    
-
    Type
    
-
    return
    
-
    
-
    
-
    
-
-
    
-
    
-mapped_run(inp: List[numpy.ndarray], val_inp: bool = True) → Dict[str, numpy.ndarray][source]ΒΆ
    
-
    Run given inputs through the model for inference.
-Returns the result as a dictionary of numpy arrays corresponding to
-the output names of the model as defined in the ONNX graph.
    
-
    Note 1: this function can add some a performance hit in certain cases.
-If using, please validate that you do not incur a performance hit
-by comparing with the regular run func
    
-
    See @run for more details on specific setup for the inputs.
    
-
    
-
    Example:
    
-
    
-
    engine = Engine(β€œpath/to/onnx”, batch_size=1)
    
-
    inp = [numpy.random.rand(1, 3, 224, 224).astype(numpy.float32)]
    
-
    out = engine.mapped_run(inp)
    
-
    assert isinstance(out, Dict)
    
-
    
-
    
-
    
-
    Parameters
    
-
      
-
    • inp – The list of inputs to pass to the engine for inference.
-The expected order is the inputs order as defined in the ONNX graph.
      • 
-
    • val_inp – Validate the input to the model to ensure numpy array inputs
-are setup correctly for the DeepSparse Engine
      • 
-
    
-
    
-
    Returns
    
-
    The dictionary of outputs from the model after executing
-over the inputs
    
-
    
-
    
-
    
-
-
    
-
    
-property model_pathΒΆ
    
-
    The local path to the model file the current instance was compiled from
    
-
    
-
    Type
    
-
    return
    
-
    
-
    
-
    
-
-
    
-
    
-property num_coresΒΆ
    
-
    The number of physical cores the current instance is running on
    
-
    
-
    Type
    
-
    return
    
-
    
-
    
-
    
-
-
    
-
    
-property num_socketsΒΆ
    
-
    The number of sockets the engine is compiled to run on;
-only current support is 1
    
-
    
-
    Type
    
-
    return
    
-
    
-
    
-
    
-
-
    
-
    
-run(inp: List[numpy.ndarray], val_inp: bool = True) → List[numpy.ndarray][source]ΒΆ
    
-
    Run given inputs through the model for inference.
-Returns the result as a list of numpy arrays corresponding to
-the outputs of the model as defined in the ONNX graph.
    
-
    Note 1: the input dimensions must match what is defined in the ONNX graph.
-To avoid extra time in memory shuffles, the best use case
-is to format both the onnx and the input into channels first format;
-ex: [batch, height, width, channels] => [batch, channels, height, width]
    
-
    Note 2: the input type for the numpy arrays must match
-what is defined in the ONNX graph.
-Generally float32 is most common,
-but int8 and int16 are used for certain layer and input types
-such as with quantized models.
    
-
    Note 3: the numpy arrays must be contiguous in memory,
-use numpy.ascontiguousarray(array) to fix if not.
    
-
    
-
    Example:
    
-
    
-
    engine = Engine(β€œpath/to/onnx”, batch_size=1, num_cores=None)
    
-
    inp = [numpy.random.rand(1, 3, 224, 224).astype(numpy.float32)]
    
-
    out = engine.run(inp)
    
-
    assert isinstance(out, List)
    
-
    
-
    
-
    
-
    Parameters
    
-
      
-
    • inp – The list of inputs to pass to the engine for inference.
-The expected order is the inputs order as defined in the ONNX graph.
      • 
-
    • val_inp – Validate the input to the model to ensure numpy array inputs
-are setup correctly for the DeepSparse Engine
      • 
-
    
-
    
-
    Returns
    
-
    The list of outputs from the model after executing over the inputs
    
-
    
-
    
-
    
-
-
    
-
    
-timed_run(inp: List[numpy.ndarray], val_inp: bool = True) → Tuple[List[numpy.ndarray], float][source]ΒΆ
    
-
    Convenience method for timing a model inference run.
-Returns the result as a tuple containing (the outputs from @run, time take)
    
-
    See @run for more details.
    
-
    
-
    Example:
    
-
    
-
    engine = Engine(β€œpath/to/onnx”, batch_size=1, num_cores=None)
    
-
    inp = [numpy.random.rand(1, 3, 224, 224).astype(numpy.float32)]
    
-
    out, time = engine.timed_run(inp)
    
-
    assert isinstance(out, List)
    
-
    assert isinstance(time, float)
    
-
    
-
    
-
    
-
    Parameters
    
-
      
-
    • inp – The list of inputs to pass to the engine for inference.
-The expected order is the inputs order as defined in the ONNX graph.
      • 
-
    • val_inp – Validate the input to the model to ensure numpy array inputs
-are setup correctly for the DeepSparse Engine
      • 
-
    
-
    
-
    Returns
    
-
    The list of outputs from the model after executing over the inputs
    
-
    
-
    
-
    
-
-
    
-
-
    
-
    
-deepsparse.engine.analyze_model(model: Union[str, sparsezoo.objects.model.Model, sparsezoo.objects.file.File], inp: List[numpy.ndarray], batch_size: int = 1, num_cores: Optional[int] = None, num_iterations: int = 20, num_warmup_iterations: int = 5, optimization_level: int = 1, imposed_as: Optional[float] = None, imposed_ks: Optional[float] = None, num_sockets: Optional[int] = None) → dict[source]ΒΆ
    
-
    Function to analyze a model’s performance in the DeepSparse Engine.
-The model must be defined in an ONNX graph and stored in a local file.
-Gives defaults of batch_size == 1 and num_cores == None
-(will use all physical cores available on a single socket).
    
-
    
-
    Parameters
    
-
      
-
    • model – Either a path to the model’s onnx file, a SparseZoo model stub
-prefixed by β€˜zoo:’, a SparseZoo Model object, or a SparseZoo ONNX File
-object that defines the neural network graph definition to analyze
      • 
-
    • inp – The list of inputs to pass to the engine for analyzing inference.
-The expected order is the inputs order as defined in the ONNX graph.
      • 
-
    • batch_size – The batch size of the inputs to be used with the model
      • 
-
    • num_cores – The number of physical cores to run the model on.
-Pass None or 0 to run on the max number of cores
-in one socket for the current machine, default None
      • 
-
    • num_iterations – The number of times to repeat execution of the model
-while analyzing, default is 20
      • 
-
    • num_warmup_iterations – The number of times to repeat execution of the model
-before analyzing, default is 5
      • 
-
    • optimization_level – The amount of graph optimizations to perform.
-The current choices are either 0 (minimal) or 1 (all), default is 1
      • 
-
    • imposed_as – Imposed activation sparsity, defaults to None.
-Will force the activation sparsity from all ReLu layers in the graph
-to match this desired sparsity level (percentage of 0’s in the tensor).
-Beneficial for seeing how AS affects the performance of the model.
      • 
-
    • imposed_ks – Imposed kernel sparsity, defaults to None.
-Will force all prunable layers in the graph to have weights with
-this desired sparsity level (percentage of 0’s in the tensor).
-Beneficial for seeing how pruning affects the performance of the model.
      • 
-
    • num_sockets – The number of physical sockets to run the model on.
-Pass None or 0 to run on the max number of sockets for the
-current machine, default None
      • 
-
    
-
    
-
    Returns
    
-
    the analysis structure containing the performance details of each layer
    
-
    
-
    
-
    
-
-
    
-
    
-deepsparse.engine.benchmark_model(model: Union[str, sparsezoo.objects.model.Model, sparsezoo.objects.file.File], inp: List[numpy.ndarray], batch_size: int = 1, num_cores: Optional[int] = None, num_iterations: int = 20, num_warmup_iterations: int = 5, include_inputs: bool = False, include_outputs: bool = False, show_progress: bool = False, num_sockets: Optional[int] = None) → deepsparse.benchmark.BenchmarkResults[source]ΒΆ
    
-
    Convenience function to benchmark a model in the DeepSparse Engine
-from an ONNX file for inference.
-Gives defaults of batch_size == 1 and num_cores == None
-(will use all physical cores available on a single socket).
    
-
    
-
    Parameters
    
-
      
-
    • model – Either a path to the model’s onnx file, a SparseZoo model stub
-prefixed by β€˜zoo:’, a SparseZoo Model object, or a SparseZoo ONNX File
-object that defines the neural network
      • 
-
    • batch_size – The batch size of the inputs to be used with the model
      • 
-
    • num_cores – The number of physical cores to run the model on.
-Pass None or 0 to run on the max number of cores
-in one socket for the current machine, default None
      • 
-
    • inp – The list of inputs to pass to the engine for benchmarking.
-The expected order is the inputs order as defined in the ONNX graph.
      • 
-
    • num_iterations – The number of iterations to run benchmarking for.
-Default is 20
      • 
-
    • num_warmup_iterations – T number of iterations to warm up engine before
-benchmarking. These executions will not be counted in the benchmark
-results that are returned. Useful and recommended to bring
-the system to a steady state. Default is 5
      • 
-
    • include_inputs – If True, inputs from forward passes during benchmarking
-will be added to the results. Default is False
      • 
-
    • include_outputs – If True, outputs from forward passes during benchmarking
-will be added to the results. Default is False
      • 
-
    • show_progress – If True, will display a progress bar. Default is False
      • 
-
    • num_sockets – The number of physical sockets to run the model on.
-Pass None or 0 to run on the max number of sockets for the
-current machine, default None
      • 
-
    
-
    
-
    Returns
    
-
    the results of benchmarking
    
-
    
-
    
-
    
-
-
    
-
    
-deepsparse.engine.compile_model(model: Union[str, sparsezoo.objects.model.Model, sparsezoo.objects.file.File], batch_size: int = 1, num_cores: Optional[int] = None, num_sockets: Optional[int] = None) → deepsparse.engine.Engine[source]ΒΆ
    
-
    Convenience function to compile a model in the DeepSparse Engine
-from an ONNX file for inference.
-Gives defaults of batch_size == 1 and num_cores == None
-(will use all physical cores available on a single socket).
    
-
    
-
    Parameters
    
-
      
-
    • model – Either a path to the model’s onnx file, a SparseZoo model stub
-prefixed by β€˜zoo:’, a SparseZoo Model object, or a SparseZoo ONNX File
-object that defines the neural network
      • 
-
    • batch_size – The batch size of the inputs to be used with the model
      • 
-
    • num_cores – The number of physical cores to run the model on.
-Pass None or 0 to run on the max number of cores
-in one socket for the current machine, default None
      • 
-
    • num_sockets – The number of physical sockets to run the model on.
-Pass None or 0 to run on the max number of sockets for the
-current machine, default None
      • 
-
    
-
    
-
    Returns
    
-
    The created Engine after compiling the model
    
-
    
-
    
-
    
-
-
    
-
    
-
    deepsparse.lib moduleΒΆ
    
-
    
-
    
-deepsparse.lib.init_deepsparse_lib()[source]ΒΆ
    
-
    
-
+
    
+
    deepsparse.lib moduleΒΆ
    
 
    
-
    
-
    deepsparse.version moduleΒΆ
    
+
    
+
    deepsparse.version moduleΒΆ
    
 
    
-
    
-
    Module contentsΒΆ
    
-
    The DeepSparse package used to achieve GPU class performance
-for Neural Networks on commodity CPUs.
    
+
    
+
    Module contentsΒΆ
    
 
    
 
    
 
diff --git a/deepsparse/api/deepsparse.utils.html b/deepsparse/api/deepsparse.utils.html
index c4abdd470a0..de2552cb0f2 100644
--- a/deepsparse/api/deepsparse.utils.html
+++ b/deepsparse/api/deepsparse.utils.html
@@ -111,21 +111,21 @@
 
  • Subpackages
 
    • 
 
  • Submodules
    • 
-
  • deepsparse.benchmark module
    • 
-
  • deepsparse.cpu module
    • 
-
  • deepsparse.engine module
    • 
-
  • deepsparse.lib module
    • 
-
  • deepsparse.version module
    • 
-
  • Module contents
    • 
+
  • deepsparse.benchmark module
    • 
+
  • deepsparse.cpu module
    • 
+
  • deepsparse.engine module
    • 
+
  • deepsparse.lib module
    • 
+
  • deepsparse.version module
    • 
+
  • Module contents
    • 
 
 
 
@@ -208,84 +208,17 @@ 
    deepsparse.utils package
 
    SubmodulesΒΆ
    
 
    
-
    
-
    deepsparse.utils.data moduleΒΆ
    
-
    
-
    
-deepsparse.utils.data.verify_outputs(outputs: List[numpy.array], gt_outputs: List[numpy.array], atol: float = 0.0008, rtol: float = 0.0) → List[float][source]ΒΆ
    
-
    Compares two lists of output tensors, checking that they are sufficiently similar
-:param outputs: List of numpy arrays, usually model outputs
-:param gt_outputs: List of numpy arrays, usually reference outputs
-:param atol: Absolute tolerance for allclose
-:param rtol: Relative tolerance for allclose
-:return: The list of max differences for each pair of outputs
    
-
    
-
+
    
+
    deepsparse.utils.data moduleΒΆ
    
 
    
-
    
-
    deepsparse.utils.log moduleΒΆ
    
-
    
-
    
-deepsparse.utils.log.log_init(name)[source]ΒΆ
    
-
    
-
+
    
+
    deepsparse.utils.log moduleΒΆ
    
 
    
-
    
-
    deepsparse.utils.onnx moduleΒΆ
    
-
    
-
    
-deepsparse.utils.onnx.generate_random_inputs(onnx_filepath: str, batch_size: Optional[int] = None) → List[numpy.array][source]ΒΆ
    
-
    Generate random data that matches the type and shape of ONNX model,
-with a batch size override
-:param onnx_filepath: File path to ONNX model
-:param batch_size: If provided, override for the batch size dimension
-:return: List of random tensors
    
-
    
-
-
    
-
    
-deepsparse.utils.onnx.get_external_inputs(onnx_filepath: str) → List[source]ΒΆ
    
-
    Gather external inputs of ONNX model
-:param onnx_filepath: File path to ONNX model
-:return: List of input objects
    
-
    
-
-
    
-
    
-deepsparse.utils.onnx.get_external_outputs(onnx_filepath: str) → List[source]ΒΆ
    
-
    Gather external outputs of ONNX model
-:param onnx_filepath: File path to ONNX model
-:return: List of output objects
    
-
    
-
-
    
-
    
-deepsparse.utils.onnx.get_input_names(onnx_filepath: str) → List[str][source]ΒΆ
    
-
    Gather names of all external inputs of ONNX model
-:param onnx_filepath: File path to ONNX model
-:return: List of string names
    
-
    
-
-
    
-
    
-deepsparse.utils.onnx.get_output_names(onnx_filepath: str) → List[str][source]ΒΆ
    
-
    Gather names of all external outputs of ONNX model
-:param onnx_filepath: File path to ONNX model
-:return: List of string names
    
-
    
-
-
    
-
    
-deepsparse.utils.onnx.override_onnx_batch_size(onnx_filepath: str, batch_size: int)[source]ΒΆ
    
-
    Rewrite batch sizes of ONNX model, saving the modified model and returning its path
-:param onnx_filepath: File path to ONNX model
-:param batch_size: Override for the batch size dimension
-:return: File path to modified ONNX model
    
-
    
-
+
    
+
    deepsparse.utils.onnx moduleΒΆ
    
 
    
-
    
-
    Module contentsΒΆ
    
+
    
+
    Module contentsΒΆ
    
 
    
 
    
 
diff --git a/deepsparse/api/modules.html b/deepsparse/api/modules.html
index 2df365f5890..fd8d1cfc9fc 100644
--- a/deepsparse/api/modules.html
+++ b/deepsparse/api/modules.html
@@ -188,21 +188,21 @@ 
    deepsparseSubpackages
 
 
  • Submodules
    • 
-
  • deepsparse.benchmark module
    • 
-
  • deepsparse.cpu module
    • 
-
  • deepsparse.engine module
    • 
-
  • deepsparse.lib module
    • 
-
  • deepsparse.version module
    • 
-
  • Module contents
    • 
+
  • deepsparse.benchmark module
    • 
+
  • deepsparse.cpu module
    • 
+
  • deepsparse.engine module
    • 
+
  • deepsparse.lib module
    • 
+
  • deepsparse.version module
    • 
+
  • Module contents
    • 
 
 
 
diff --git a/deepsparse/debugging-optimizing/numactl-utility.html b/deepsparse/debugging-optimizing/numactl-utility.html
index 6c0155bdcfb..6c7f74302b7 100644
--- a/deepsparse/debugging-optimizing/numactl-utility.html
+++ b/deepsparse/debugging-optimizing/numactl-utility.html
@@ -232,7 +232,7 @@ 
    Using the numactl Utility to Control Resource Utilization with the DeepSpars
 
    
 
    
 
    Appending --preferred 1 is needed here since the DeepSparse Engine is being bound to CPUs on the second socket.
    
-
    Note that using more than two sockets may not offer improvements over two sockets; if you have options, try different scenarios to see which setup is ideal for your use case. For batch size considerations, use an amount that is evenly divisible by the number of sockets you intend to use.
    
+
    Note: When running on multiple sockets using a batch size that is evenly divisible by the number of sockets will yield the best performance.
    
 
    
 
    DeepSparse Engine and Thread PinningΒΆ
    
 
    When using numactl to specify which CPUs/sockets the engine is allowed to run on, there is no restriction as to which CPU a particular computation thread is executed on. A single thread of computation may run on one or more CPUs during the course of execution. This is desirable if the system is being shared between multiple processes so that idle CPU threads are not prevented from doing other work.
    
diff --git a/deepsparse/genindex.html b/deepsparse/genindex.html
index 01453f7f562..2c5ba1a1863 100644
--- a/deepsparse/genindex.html
+++ b/deepsparse/genindex.html
@@ -182,345 +182,8 @@
 
    Index
    
 
 
    
- A
- | B
- | C
- | D
- | E
- | G
- | I
- | L
- | M
- | N
- | O
- | R
- | T
- | V
  
 
    
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-
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-  
-
    
-
-
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-
-  
-  
-
    
-
-
    D
    
-
-  
-  
-
      
-      
    • 
-    deepsparse
-
-      
      • 
-      
    • 
-    deepsparse.benchmark
-
-      
      • 
-      
    • 
-    deepsparse.cpu
-
-      
      • 
-      
    • 
-    deepsparse.engine
-
-      
      • 
-      
    • 
-    deepsparse.lib
-
-      
      • 
-  
      
-      
    • 
-    deepsparse.utils
-
-      
      • 
-      
    • 
-    deepsparse.utils.data
-
-      
      • 
-      
    • 
-    deepsparse.utils.log
-
-      
      • 
-      
    • 
-    deepsparse.utils.onnx
-
-      
      • 
-      
    • 
-    deepsparse.version
-
-      
      • 
-  
    
-
-
    E
    
-
-  
-  
-
    
-
-
    G
    
-
-  
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-
    
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-
-  
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-  
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-
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-  
-  
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-
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-
    
-
 
 
            
    
diff --git a/deepsparse/index.html b/deepsparse/index.html
index 3d849433c18..b71b4e5c885 100644
--- a/deepsparse/index.html
+++ b/deepsparse/index.html
@@ -293,12 +293,12 @@ 
    Release Historydeepsparse package
 
 
diff --git a/deepsparse/objects.inv b/deepsparse/objects.inv
index 2317906ff63f18a549714478fcb51cfad97e8a2d..7d9fbee3eae96d3a072c05be5d558fb424049324 100644
GIT binary patch
delta 393
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diff --git a/deepsparse/quicktour.html b/deepsparse/quicktour.html
index df0091d8ae5..b02f1994631 100644
--- a/deepsparse/quicktour.html
+++ b/deepsparse/quicktour.html
@@ -228,7 +228,7 @@ 
    Quickstart with SparseZoo ONNX Modelsfrom sparsezoo.models import classification
 
 model = classification.resnet_50()
-print(Zoo.search_optimized_models(model))
+print(Zoo.search_optimized_models(model))
 
    
 
    
 
    Output:
    
@@ -258,7 +258,7 @@ 
    Quickstart with SparseZoo ONNX Modelsbatch_size=batch_size,
 )
 benchmarks_base = engine_base.benchmark(sample_inputs)
-print(benchmarks_base)
+print(benchmarks_base)
 
 # run sparse benchmarking
 engine_sparse = compile_model(
@@ -266,11 +266,11 @@ 
    Quickstart with SparseZoo ONNX Modelsbatch_size=batch_size,
 )
 if not engine_sparse.cpu_vnni:
-    print("WARNING: VNNI instructions not detected, quantization speedup not well supported")
+    print("WARNING: VNNI instructions not detected, quantization speedup not well supported")
 benchmarks_sparse = engine_sparse.benchmark(sample_inputs)
-print(benchmarks_sparse)
+print(benchmarks_sparse)
 
-print(f"Speedup: {benchmarks_sparse.items_per_second / benchmarks_base.items_per_second:.2f}x")
+print(f"Speedup: {benchmarks_sparse.items_per_second / benchmarks_base.items_per_second:.2f}x")
    diff --git a/deepsparse/searchindex.js b/deepsparse/searchindex.js index cb63ab698b3..74bd83bf31e 100644 --- a/deepsparse/searchindex.js +++ b/deepsparse/searchindex.js @@ -1 +1 @@ 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+Search.setIndex({docnames:["api/deepsparse","api/deepsparse.utils","api/modules","debugging-optimizing/diagnostics-debugging","debugging-optimizing/example-log","debugging-optimizing/index","debugging-optimizing/numactl-utility","hardware","index","installation","quicktour"],envversion:{"sphinx.domains.c":2,"sphinx.domains.changeset":1,"sphinx.domains.citation":1,"sphinx.domains.cpp":3,"sphinx.domains.index":1,"sphinx.domains.javascript":2,"sphinx.domains.math":2,"sphinx.domains.python":2,"sphinx.domains.rst":2,"sphinx.domains.std":1,"sphinx.ext.intersphinx":1,"sphinx.ext.viewcode":1,sphinx:56},filenames:["api/deepsparse.rst","api/deepsparse.utils.rst","api/modules.rst","debugging-optimizing/diagnostics-debugging.md","debugging-optimizing/example-log.md","debugging-optimizing/index.rst","debugging-optimizing/numactl-utility.md","hardware.md","index.rst","installation.md","quicktour.md"],objects:{},objnames:{},objtypes:{},terms:{"100":10,"104":4,"112":4,"121":4,"122":[3,4],"124":4,"126":4,"129":4,"130":4,"132":4,"140":4,"157":4,"224":[3,4,10],"242":4,"25690112":4,"265":[3,4],"276":4,"321":[3,4],"33918976":4,"478":[3,4],"512":7,"595":4,"604":4,"644":4,"652":4,"667":4,"672":4,"679":4,"684":4,"706":[3,4],"715":[3,4],"723":[3,4],"757396":4,"7f4fbbd3f740":[3,4],"96ce2f6cb23b8ab377012ed9ef38d3da3b9f5313":4,"class":8,"const":[3,4],"default":[3,4],"export":[3,4,6,8],"final":8,"float":[3,4],"import":10,"new":[3,4],"super":[3,4],"try":10,"while":8,For:[3,6,8,10],Ice:7,Its:3,One:6,The:[3,4,6,7,8,10],Then:[3,9],There:3,Using:[5,8],about:6,abov:6,acceler:8,accept:10,accuraci:[8,10],achiev:6,activ:[7,8],add:3,addit:[5,8,9],addition:8,advantag:8,advis:6,after:[3,6],against:3,aggress:10,agreement:3,algorithm:7,all:[3,6,8],alloc:[3,6],allocate_buffers_pass:4,allow:[3,6,8],along:8,also:6,altern:[3,8],amd:[6,7],amount:[5,8],analyz:3,ani:[6,9],anoth:6,api:8,append:6,appli:8,applic:3,approach:8,architectur:[3,6],art:10,assign:3,associ:3,astyp:10,augment:10,avail:[3,6,7,10],avx2:7,avx512:4,avx:7,backend:8,base:10,baselin:[8,10],basi:3,batch:[4,5,6],batch_siz:10,been:6,befor:3,begin:[3,4],behavior:3,being:6,below:3,benchmark:[2,8,10],benchmarks_bas:10,benchmarks_spars:10,benefit:3,best:6,better:6,between:[3,6],bia:[3,4],binari:4,bind:[3,6],block:3,blog:8,boost:7,bound:[6,8],broadwel:7,bsd300:4,buffer:4,bug:8,build:[3,8],calc:[3,4],can:[3,6,8,10],cannon:7,cannot:4,captur:3,care:6,cascad:7,certain:3,choos:10,classif:10,clone:9,close:10,code:[3,4,8],com:[3,10],command:3,common:3,commun:3,compar:10,compat:10,compil:[4,5,10],compile_model:10,complex:3,complic:3,comput:[6,8],compute_func:[3,4],conflict:3,connect:3,consecut:6,consent:3,conserv:10,constant:[3,4],construct:4,construct_subgraph:4,consult:3,contain:3,content:[2,3,8],control:[5,8],conv1:[3,4],conv2:[3,4],conv3:[3,4],conv4:[3,4],conv:[3,4],convolut:3,cooper:7,core:[4,5,6],correctli:8,could:6,cours:6,cpu:[2,6,7,8,10],cpu_vnni:10,cpunodebind:6,creat:[3,4,8],current:6,custom:8,data:[0,2,3],data_input:10,dataset:[3,8],debian:9,debug:8,decid:3,decis:3,deep:8,deepspars:[5,7,9,10],deepsparseengin:[3,6],defens:3,degrad:[3,6],deliv:8,dens:10,depend:9,deploi:8,deploy:[3,8],describ:[3,6],design:3,desir:6,detail:[3,6,7],detect:10,determin:5,dev:8,diagnos:[3,5,8],diagnost:[5,8],differ:[3,4,6,7],direct:8,disabl:[3,6],displai:[3,6],divis:6,doc:8,document:8,doe:6,doing:6,download:[8,10],driven:8,due:3,dure:6,dynam:3,each:[5,6],easili:8,ecosystem:3,edit:8,effect:8,elementwis:[3,4],empti:4,emul:7,enabl:[5,6,7,8,10],encod:8,encompass:8,end:[3,4,6],engin:[2,4,5,7,8,10],engine_bas:10,engine_spars:10,entir:3,environ:[3,6,9],error:3,evenli:6,everyth:8,exampl:[5,6,8,9],execut:[4,5,6,10],exist:8,expedit:10,explain:[3,4],explor:[9,10],extens:7,extra:8,faster:[8,10],fatal:3,featur:8,fetch:10,few:8,fft:8,file:[3,10],filter:4,find:[5,10],fine:6,finish:4,first:[3,6],fit:8,float32:10,flow:8,focus:8,follow:[3,4,6],forc:6,format:8,found:8,four:6,fp32:10,framework:8,from:[3,4,6,8,10],full:8,further:6,gener:[3,4,8,10],generate_random_input:10,get:[3,8],getcap:4,github:[8,10],give:8,given:6,gpu:8,grain:6,graph:[4,5],graph_util:[3,4],graphview:[3,4],greater:[3,4],guid:3,guidanc:[5,8],hardwar:[6,8,10],has:6,haswel:7,help:8,here:[6,7,10],highli:7,hit:3,home:[3,4],host:[8,10],how:[3,8,10],howev:6,hpp:4,http:[3,10],hurt:3,hyper:6,hyperthread:6,ideal:3,idl:6,ignor:4,imagenet:10,implement:8,improv:[6,8],includ:[3,4,8,10],increas:3,indic:3,induc:8,infer:[3,8,10],inferenc:8,inference_tim:10,info:4,inform:[3,8],ingest:8,initi:3,input:[3,4,10],input_data:4,instal:8,instanc:3,instruct:[7,10],int8:10,intak:[3,4],intel:[6,7],inventori:6,issu:3,items_per_second:10,jdoe:[3,4],jit:[3,4],just:8,keep:9,kera:8,kernel:[3,4,7],lake:7,larger:6,learn:3,legal:3,level:[3,5,8],lib:[2,8],like:[3,6,9],limit:8,line:[3,8],linux:[7,9],list:3,load:3,locat:[3,6],log:[0,2,5,8],logic:6,look:3,machin:[3,8,10],macro:3,made:3,magic:[3,8],mai:[3,6],main:3,major:[3,6],make:3,man:6,manag:3,mani:[3,8],manual:3,map:6,master:10,match:4,maxim:3,maximum:6,membind:6,memori:[6,8],metric:8,microarchitectur:7,migrat:[3,6],mobilenet:10,mobilenetv2:10,model:[3,4,6,8],moder:10,modul:[2,8],monitor:3,monopol:3,more:6,multi:6,multipl:6,name_of_log:3,natur:8,nearli:[8,10],need:6,network:[3,4,8],neural:[3,8],neuralmag:[3,4],neuralmagic_cr:4,neuralmagic_execut:4,newer:7,nightli:8,nm_bind_threads_to_cor:[3,6],nm_exec_test_it:4,nm_execution_provid:[3,4],nm_logging_level:[3,4],nm_ogging_level:3,nm_ort:[3,4],nm_subgraph:3,nm_subgraph_1:[3,4],nmexecutionprovid:4,node:[4,5],non:4,none:[4,10],normal:3,notabl:3,note:[3,5,8],notebook:9,notic:8,numactl:[5,8],number:[5,6],numpi:10,nyann:[3,4],obtain:5,occur:8,offici:8,onc:3,one:[3,6,8],onli:[3,4,6,8],onnx:[0,2,4,8],onnx_filenam:4,onnx_filepath:10,onnxruntime_neuralmag:[3,4],openmp:3,oper:[3,4,7],ops:[3,4],optim:[4,6,7,8,10],order:[3,9],ort:[3,4],other:[3,6,8,10],our:5,out:[3,6],output:[3,4,10],output_data:4,outsid:6,over:[7,8],overprecis:8,own:6,packag:[2,8,10],pad:[3,4],page:6,paramet:[3,6],parameter:8,pars:[4,5,8],part:3,particular:6,pattern:4,per:[3,6],percentag:3,perform:[5,6,8,10],physcpubind:6,physic:6,pin:[3,5,8],pinpoint:3,pip:9,pipelin:[3,8],planner:4,plu:8,plug:10,point:3,polici:3,pool:3,portion:[3,4],possibl:3,practic:3,pre:10,predict:10,prefer:6,prepar:8,prevent:[3,6],print:[3,4,10],privaci:3,process:[3,6,8],produc:[5,8],product:8,provid:[3,4],prune:[8,10],pruned_qu:10,pypi:8,python:[3,9],pytorch:[8,10],quant:10,quantiz:[7,8,10],quick:8,quickli:[8,10],quickstart:8,randn:10,random:[4,10],rang:6,ratio:4,raw:10,real:[3,10],recip:[8,10],recommend:[3,7,9],recov:[8,10],reduc:8,redund:8,relu:[3,4],remov:8,repeat:10,repo:4,report:3,repositori:[8,9],request:8,requir:[4,6,8,9],reshap:[3,4],resnet:10,resnet_50:10,resnet_v1:10,resolut:[3,4],resourc:[3,5],respect:10,restrict:6,result:[3,6,8],reveal:3,review:3,run:[3,4,6,7,10],run_model:3,runtim:[4,5,8],same:[6,8],sampl:[3,10],sample_batch:10,sample_input:10,save:10,scale:8,scarc:3,scienc:3,script:3,seamlessli:8,search_optimized_model:10,second:6,section:10,see:[3,6,10],seek:3,select:6,self:3,separ:6,serv:3,set:[3,6,10],sever:3,shape:[3,4],share:[3,6,10],shell:3,ship:3,should:6,show:[3,6],significantli:8,similarli:6,simpl:8,simpli:10,simplif:3,sinc:6,singl:6,size:[4,5,6],skylak:7,smaller:8,smt:6,socket:6,softwar:3,solut:10,some:[3,7],spars:[7,8,10],sparseml:[8,10],sparsezoo:8,sparsif:10,sparsifi:[8,10],sparsiti:[7,8],specif:[6,7],specifi:[3,6],speedup:10,split:3,src:[3,4],stabl:8,standard:6,start:[3,4,6,8],startup:6,state:[3,10],statement:3,statist:5,stderr:3,step:8,straightforward:6,stride:[3,4],stub:10,subgraph:[4,5],submodul:[2,8],subpackag:[2,8],suit:8,super_resolut:4,support:[4,5,8,10],supported_subgraph:[3,4],system:[3,4,6,7,9],tabl:7,tag:10,take:8,target:10,tbb:3,technic:3,techniqu:[8,10],tensor:3,tensorflow:8,test:[4,9],test_1:4,than:[3,4,6,10],thei:3,them:3,thi:[3,6,8,9,10],thread:[3,5,8],through:6,tiger:7,time:5,timed_run:10,too:10,top:8,torch:[3,4],total:4,tour:8,tradit:3,train:[3,8,10],translat:[3,4],transpos:[3,4],troubleshoot:3,truncat:3,tune:[5,8],two:[6,10],txt:3,type:3,uniqu:3,unit:4,unlik:3,unoptim:3,unsupport:[3,4],use:[3,6,10],used:6,using:[3,4,6,8,9,10],usual:6,util:[0,2,3,4,5,8,10],valid:7,validate_minimum_supported_fract:[3,4],valu:[3,4],variabl:[3,6],variou:3,verbos:[3,5,8],veri:[3,10],version:[2,4,8,10],via:8,view:5,virtual:9,vision:10,vnni:[7,10],wai:6,wand:4,want:3,warn:[3,4,10],websit:8,weight:[3,4],well:[6,8,10],wget:10,what:[3,10],when:[6,8,10],where:[3,4,6],whether:3,which:[3,6],whole:5,winograd:8,within:[3,8],work:[6,7,8],workload:8,would:[3,6,9],x86:7,yield:6,you:[3,6,8,9,10],your:[3,8,9,10],zen:7,zoo:10},titles:["deepsparse package","deepsparse.utils package","deepsparse","Logging Guidance for Diagnostics and Debugging","Example Log, Verbose Level = diagnose","Debugging and Optimizing","Using the numactl Utility to Control Resource Utilization with the DeepSparse Engine","Hardware Support","DeepSparse 0.1","Installation","Quick Tour"],titleterms:{Using:6,addit:6,amount:3,batch:3,benchmark:0,compat:8,compil:3,content:[0,1],control:[3,6],core:3,cpu:0,custom:10,data:1,debug:[3,5],deepspars:[0,1,2,3,6,8],determin:3,diagnos:4,diagnost:3,each:3,enabl:3,engin:[0,3,6],exampl:[3,4],execut:3,find:3,graph:3,guidanc:3,hardwar:7,histori:8,instal:9,learn:8,level:4,lib:0,log:[1,3,4],model:10,modul:[0,1],more:8,node:3,note:6,numactl:6,number:3,obtain:3,onnx:[1,10],optim:[3,5],our:3,overview:8,packag:[0,1],pars:3,perform:3,pin:6,produc:3,quick:10,quickstart:10,releas:8,resourc:[6,8],runtim:3,size:3,sparsezoo:10,sparsif:8,statist:3,subgraph:3,submodul:[0,1],subpackag:0,support:[3,7],thread:6,time:3,tour:10,tune:3,util:[1,6],verbos:4,version:0,view:3,whole:3}}) \ No newline at end of file diff --git a/sparseml/_modules/index.html b/sparseml/_modules/index.html index ef30f3ad87b..b6278da3788 100644 --- a/sparseml/_modules/index.html +++ b/sparseml/_modules/index.html @@ -173,7 +173,15 @@

    All modules for which code is available

    -
  • analyze_module() (in module sparseml.tensorflow_v1.optim.analyzer_module)
    • - - +
  • coco_2017_yolo() (in module sparseml.pytorch.datasets.detection.coco) +
    • +
  • coco_mapping() (in module sparseml.pytorch.utils.callbacks) +
    • +
  • coco_yolo_2017_mapping() (in module sparseml.pytorch.utils.callbacks)
  • CocoDetectionDataset (class in sparseml.pytorch.datasets.detection.coco)
    • @@ -553,9 +571,15 @@

    C

  • corrected_lr_info() (sparseml.optim.learning_rate.LearningRate method)
    • -
  • create() (sparseml.pytorch.datasets.registry.DatasetRegistry static method) +
  • create() (sparseml.keras.datasets.registry.DatasetRegistry static method)
  • create_activation() (in module sparseml.pytorch.nn.activations) -
    • -
  • create_dirs() (in module sparseml.utils.helpers)
  • create_unique_dir() (in module sparseml.utils.helpers)
    • -
  • create_zoo_model() (sparseml.pytorch.models.registry.ModelRegistry static method) +
  • create_zoo_model() (sparseml.keras.models.registry.ModelRegistry static method)
    • -
  • creator() (sparseml.tensorflow_v1.datasets.classification.imagefolder.ImageFolderDataset method) +
  • creator() (sparseml.keras.datasets.classification.imagefolder.ImageFolderDataset method)
    • @@ -743,17 +773,23 @@

    D

  • DataLoader (class in sparseml.onnx.utils.data)
    • -
  • Dataset (class in sparseml.tensorflow_v1.datasets.dataset) +
  • Dataset (class in sparseml.keras.datasets.dataset) + +
  • dataset_size() (sparseml.utils.datasets.imagenette.ImagenetteDownloader property)
    • -
  • DatasetRegistry (class in sparseml.pytorch.datasets.registry) +
  • DatasetRegistry (class in sparseml.keras.datasets.registry)
    • @@ -787,12 +823,20 @@

    D

  • DefaultBoxes (class in sparseml.pytorch.utils.ssd_helpers)
    • -
  • dense_block() (in module sparseml.tensorflow_v1.nn.layers) +
  • delete_initializers() (sparseml.onnx.utils.graph_editor.ONNXGraph method)
    • -
  • density() (sparseml.onnx.utils.helpers.SparsityMeasurement property) +
  • delete_node() (sparseml.onnx.utils.graph_editor.ONNXGraph method) +
    • +
  • delete_nodes() (sparseml.onnx.utils.graph_editor.ONNXGraph method)
    • - + +
  • export_to_zoo() (sparseml.pytorch.utils.exporter.ModuleExporter method) +
    • +
  • export_torchscript() (sparseml.pytorch.utils.exporter.ModuleExporter method) +
  • extra_repr() (sparseml.pytorch.nn.fatrelu.FATReLU method)
  • extract_node_id() (in module sparseml.onnx.utils.helpers) @@ -1127,7 +1173,7 @@

    F

  • (sparseml.utils.datasets.imagenette.ImagenetteSize attribute)
    • -
  • fuse_module_conv_bn_relus() (in module sparseml.pytorch.optim.quantization.helpers) +
  • fuse_module_conv_bn_relus() (in module sparseml.pytorch.utils.quantization.helpers)
    • @@ -1184,7 +1230,11 @@

    G

  • get_init_by_name() (in module sparseml.onnx.utils.helpers) + +
  • get_inputs() (sparseml.pytorch.utils.loss.KDLossWrapper method)
  • get_kernel_shape() (in module sparseml.onnx.utils.helpers) @@ -1230,6 +1280,8 @@

    G

  • get_node_attributes() (in module sparseml.onnx.utils.helpers)
  • get_node_by_id() (in module sparseml.onnx.utils.helpers) +
    • +
  • get_node_children() (sparseml.onnx.utils.graph_editor.ONNXGraph method)
  • get_node_input_nodes() (in module sparseml.onnx.utils.helpers)
    • @@ -1240,15 +1292,17 @@

    G

  • get_node_outputs() (in module sparseml.onnx.utils.helpers)
  • get_node_params() (in module sparseml.onnx.utils.helpers) +
    • +
  • get_node_parents() (sparseml.onnx.utils.graph_editor.ONNXGraph method)
  • get_nodes_by_input_id() (in module sparseml.onnx.utils.helpers)
  • get_nodes_by_output_id() (in module sparseml.onnx.utils.helpers) -
    • -
  • get_numpy_dtype() (in module sparseml.onnx.utils.helpers)
    • +
  • get_tensor_dim_shape() (in module sparseml.onnx.utils.helpers) +
  • get_tensor_var() (in module sparseml.tensorflow_v1.utils.variable)
  • get_terminal_layers() (in module sparseml.pytorch.utils.helpers) @@ -1401,25 +1457,43 @@

    I

  • (sparseml.optim.sensitivity.PruningSensitivityResult property)
    • -
  • image_size() (sparseml.tensorflow_v1.datasets.classification.imagefolder.ImageFolderDataset property) +
  • image_size() (sparseml.keras.datasets.classification.imagefolder.ImageFolderDataset property) + +
    • +
  • ImageFolderDataset (class in sparseml.keras.datasets.classification.imagefolder)
    • -
  • imagenet_normalizer() (in module sparseml.tensorflow_v1.datasets.classification.imagefolder) +
  • imagenet_label_mapping() (in module sparseml.pytorch.utils.callbacks)
    • -
  • ImageNetDataset (class in sparseml.pytorch.datasets.classification.imagenet) +
  • imagenet_normalizer() (in module sparseml.keras.datasets.classification.imagefolder) + +
    • +
  • ImageNetDataset (class in sparseml.keras.datasets.classification.imagenet)
    • -
  • ImagenetteDataset (class in sparseml.pytorch.datasets.classification.imagenette) +
  • imagenette_label_mapping() (in module sparseml.pytorch.utils.callbacks) +
    • +
  • ImagenetteDataset (class in sparseml.keras.datasets.classification.imagenette)
    • @@ -1497,6 +1571,8 @@

    I

  • (sparseml.pytorch.optim.modifier.Modifier method)
    • + + - - +
  • num_default_boxes() (sparseml.pytorch.utils.ssd_helpers.DefaultBoxes property)
    • -
  • num_images() (sparseml.tensorflow_v1.datasets.classification.imagefolder.ImageFolderDataset property) +
  • num_images() (sparseml.keras.datasets.classification.imagefolder.ImageFolderDataset property) + +
  • NumpyArrayBatcher (class in sparseml.utils.helpers)
    • @@ -2577,6 +2701,8 @@

    O

  • onnx_nodes_sparsities() (in module sparseml.onnx.utils.helpers)
  • onnx_path() (sparseml.tensorflow_v1.utils.exporter.GraphExporter property) +
    • +
  • ONNXGraph (class in sparseml.onnx.utils.graph_editor)
  • ONNXQuantizer (class in sparseml.onnx.optim.quantization.quantize)
    • @@ -2607,11 +2733,11 @@

    O

  • op_vars() (sparseml.tensorflow_v1.optim.sensitivity_pruning.SparsePruningOpVars property)
  • OP_WEIGHT_UPDATE (sparseml.tensorflow_v1.optim.mask_pruning.PruningScope attribute) -
    • -
  • OpenVINOModelRunner (class in sparseml.onnx.utils.model)
  • pool2d() (in module sparseml.tensorflow_v1.nn.layers)
    • -
  • post_resize_transforms() (sparseml.tensorflow_v1.datasets.classification.imagefolder.ImageFolderDataset property) +
  • post_resize_transforms() (sparseml.keras.datasets.classification.imagefolder.ImageFolderDataset property) + +
  • postprocess_yolo() (in module sparseml.pytorch.utils.yolo_helpers)
    • -
  • pre_resize_transforms() (sparseml.tensorflow_v1.datasets.classification.imagefolder.ImageFolderDataset property) +
  • pre_resize_transforms() (sparseml.keras.datasets.classification.imagefolder.ImageFolderDataset property) + +
  • PREDICT (sparseml.keras.utils.logger.LoggingMode attribute)
    • @@ -2824,9 +2958,13 @@

    P

  • process_batch() (sparseml.onnx.optim.quantization.calibration.CalibrationSession method)
    • -
  • processor() (sparseml.tensorflow_v1.datasets.classification.imagefolder.ImageFolderDataset method) +
  • processor() (sparseml.keras.datasets.classification.imagefolder.ImageFolderDataset method)
    • @@ -2944,21 +3082,23 @@

    Q

  • QuantizationModifier (class in sparseml.pytorch.optim.modifier_quantization)
    • -
  • QuantizationParams (class in sparseml.pytorch.optim.quantization.quantize_qat_export) +
  • QuantizationParams (class in sparseml.pytorch.utils.quantization.quantize_qat_export)
  • quantize() (in module sparseml.onnx.optim.quantization.quantize)
  • quantize_data() (in module sparseml.onnx.optim.quantization.quantize)
    • - - + +
  • results_std() (sparseml.pytorch.optim.analyzer_as.ModuleASAnalyzer method)
    • -
  • root() (sparseml.tensorflow_v1.datasets.classification.imagefolder.ImageFolderDataset property) +
  • root() (sparseml.keras.datasets.classification.imagefolder.ImageFolderDataset property) + +
  • run() (sparseml.onnx.utils.model.DeepSparseAnalyzeModelRunner method)
    • +
  • script_model() (in module sparseml.pytorch.utils.model) +
  • serializable() (sparseml.keras.optim.modifier.ModifierProp property)
    • + + - - -
  • SplitsTransforms (class in sparseml.tensorflow_v1.datasets.classification.imagefolder) +
  • SplitsTransforms (class in sparseml.keras.datasets.classification.imagefolder) + +
  • SqueezeExcite (class in sparseml.pytorch.nn.se)
  • SSD300 (class in sparseml.pytorch.models.detection.ssd) @@ -4541,8 +4856,6 @@

    S

  • start_epoch (sparseml.optim.modifier.BaseScheduled attribute) -
    • -
  • start_epoch() (sparseml.keras.optim.modifier.ScheduledModifier property)
  • start_pending() (sparseml.pytorch.optim.modifier.ScheduledModifier method)
    • @@ -4582,7 +4895,7 @@

    T

    - + -
  • update() (sparseml.pytorch.optim.manager.ScheduledModifierManager method) +
  • update() (sparseml.onnx.utils.graph_editor.ONNXGraph method)
  • update_model_param() (in module sparseml.onnx.utils.graph_editor) +
    • +
  • update_node_input() (sparseml.onnx.utils.graph_editor.ONNXGraph method)
  • update_ready() (sparseml.keras.optim.modifier_pruning.ConstantPruningModifier property) @@ -4804,9 +5127,11 @@

    V

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    Python Module Index

        sparseml.keras + + +     + sparseml.keras.datasets + + + +     + sparseml.keras.datasets.classification + + + +     + sparseml.keras.datasets.classification.imagefolder + + + +     + sparseml.keras.datasets.classification.imagenet + + + +     + sparseml.keras.datasets.classification.imagenette + + + +     + sparseml.keras.datasets.dataset + + + +     + sparseml.keras.datasets.helpers + + + +     + sparseml.keras.datasets.registry + + + +     + sparseml.keras.models + + + +     + sparseml.keras.models.classification + + + +     + sparseml.keras.models.classification.resnet + + + +     + sparseml.keras.models.external + + + +     + sparseml.keras.models.external.keras_applications + + + +     + sparseml.keras.models.registry +     @@ -257,6 +327,11 @@

    Python Module Index

        sparseml.keras.utils.callbacks + + +     + sparseml.keras.utils.compat +     @@ -670,72 +745,77 @@

    Python Module Index

        - sparseml.pytorch.optim.quantization + sparseml.pytorch.optim.sensitivity_as     - sparseml.pytorch.optim.quantization.helpers + sparseml.pytorch.optim.sensitivity_lr     - sparseml.pytorch.optim.quantization.quantize_qat_export + sparseml.pytorch.optim.sensitivity_pruning     - sparseml.pytorch.optim.sensitivity_as + sparseml.pytorch.utils     - sparseml.pytorch.optim.sensitivity_lr + sparseml.pytorch.utils.benchmarker     - sparseml.pytorch.optim.sensitivity_pruning + sparseml.pytorch.utils.callbacks     - sparseml.pytorch.utils + sparseml.pytorch.utils.exporter     - sparseml.pytorch.utils.benchmarker + sparseml.pytorch.utils.helpers     - sparseml.pytorch.utils.exporter + sparseml.pytorch.utils.logger     - sparseml.pytorch.utils.helpers + sparseml.pytorch.utils.loss     - sparseml.pytorch.utils.logger + sparseml.pytorch.utils.model     - sparseml.pytorch.utils.loss + sparseml.pytorch.utils.module     - sparseml.pytorch.utils.model + sparseml.pytorch.utils.quantization     - sparseml.pytorch.utils.module + sparseml.pytorch.utils.quantization.helpers + + + +     + sparseml.pytorch.utils.quantization.quantize_qat_export @@ -957,6 +1037,16 @@

    Python Module Index

        sparseml.utils.datasets + + +     + sparseml.utils.datasets.cifar + + + +     + sparseml.utils.datasets.coco +     @@ -972,6 +1062,11 @@

    Python Module Index

        sparseml.utils.datasets.imagenette + + +     + sparseml.utils.datasets.voc +     diff --git a/sparseml/searchindex.js b/sparseml/searchindex.js index 251633b80c6..330bccfc7b7 100644 --- a/sparseml/searchindex.js +++ b/sparseml/searchindex.js @@ -1 +1 @@ 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package","sparseml.keras package","sparseml.keras.datasets package","sparseml.keras.datasets.classification package","sparseml.keras.models package","sparseml.keras.models.classification package","sparseml.keras.models.external package","sparseml.keras.optim package","sparseml.keras.utils package","sparseml.onnx package","sparseml.onnx.optim package","sparseml.onnx.optim.quantization package","sparseml.onnx.utils package","sparseml.optim package","sparseml.pytorch package","sparseml.pytorch.datasets package","sparseml.pytorch.datasets.classification package","sparseml.pytorch.datasets.detection package","sparseml.pytorch.datasets.recommendation package","sparseml.pytorch.datasets.video package","sparseml.pytorch.models package","sparseml.pytorch.models.classification package","sparseml.pytorch.models.detection package","sparseml.pytorch.models.external package","sparseml.pytorch.models.recommendation package","sparseml.pytorch.nn package","sparseml.pytorch.optim package","sparseml.pytorch.utils package","sparseml.pytorch.utils.quantization package","sparseml.tensorflow_v1 package","sparseml.tensorflow_v1.datasets package","sparseml.tensorflow_v1.datasets.classification package","sparseml.tensorflow_v1.models package","sparseml.tensorflow_v1.models.classification package","sparseml.tensorflow_v1.nn package","sparseml.tensorflow_v1.optim package","sparseml.tensorflow_v1.utils package","sparseml.utils package","sparseml.utils.datasets package","SparseML 0.1","Installation","Quick Tour","Sparsification Recipes"],titleterms:{"export":[9,28,37,42],activ:26,analyz:14,analyzer_a:27,analyzer_model:11,analyzer_modul:[27,36],analyzer_prun:27,base:42,benchmark:28,calibr:12,callback:[9,28],cifar:[17,32,39],classif:[4,6,17,22,32,34],coco:[18,39],compat:9,constantpruningmodifi:43,content:[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39],darknet:22,data:13,dataset:[3,4,16,17,18,19,20,31,32,39],detect:[18,23],efficientnet:22,epoch:43,estim:[33,42],extern:[7,24],fatrelu:26,framework:38,gener:16,gmpruningmodifi:43,graph_editor:13,graph_optim:13,helper:[3,13,18,28,29,31,37,38,39],histori:40,imagefold:[4,17,32],imagenet:[4,17,32,39],imagenett:[4,17,32,39],inception_v3:22,instal:41,intro:43,kera:[2,3,4,5,6,7,8,9,42],keras_appl:7,layer:35,learn:[40,43],learning_r:14,learningratemodifi:43,log:1,logger:[9,28],loss:[13,28,37],manag:[8,14,27,36],mask_creator_prun:[27,36],mask_prun:[8,27,36],mask_pruning_cr:8,mnist:[17,22,34],mobilenet:[22,34],mobilenet_v2:[22,34],model:[5,6,7,9,13,21,22,23,24,25,28,33,34],modifi:[8,14,27,36,43],modifier_a:27,modifier_epoch:[8,27,36],modifier_lr:[8,27,36],modifier_param:[8,27,36],modifier_prun:[8,27,36],modifier_quant:27,modifier_regular:27,modul:[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39],more:40,nets_util:37,onnx:[10,11,12,13,42],optim:[8,11,12,14,27,36,42,43],overview:40,packag:[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39],param:43,pipelin:42,prune:43,pytorch:[15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,42],quantiz:[12,29,43],quantize_model_post_train:12,quantize_qat_export:29,quick:42,rate:43,recip:43,recommend:[19,25],registri:[3,5,16,21,31,33],releas:40,resnet:[6,22,34],resourc:40,schedule_lr:36,sensit:14,sensitivity_a:27,sensitivity_lr:27,sensitivity_prun:[11,27,36],session:42,setlearningratemodifi:43,setweightdecaymodifi:43,singleton:38,sparse_tensor:13,sparseml:[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40],sparsif:[40,42,43],ssd:23,ssd_helper:28,ssd_lite:23,ssd_mobilenet:23,ssd_resnet:23,submodul:[1,3,4,5,6,7,8,9,11,12,13,14,16,17,18,21,22,23,24,26,27,28,29,31,32,33,34,35,36,37,38,39],subpackag:[1,2,3,5,10,11,15,16,21,28,30,31,33,38],summari:37,tensorflow:42,tensorflow_v1:[30,31,32,33,34,35,36,37],torchvis:24,tour:42,train:43,trainableparamsmodifi:43,util:[8,9,13,28,29,37,38,39],variabl:[37,43],vgg:[22,34],video:20,voc:[18,39],worker:38,wrapper:38,yolo_help:28,yolo_v3:23}}) \ No newline at end of file diff --git a/sparsezoo/_modules/sparsezoo/requests/authentication.html b/sparsezoo/_modules/sparsezoo/requests/authentication.html index 489fc497051..de9fbb4ba66 100644 --- a/sparsezoo/_modules/sparsezoo/requests/authentication.html +++ b/sparsezoo/_modules/sparsezoo/requests/authentication.html @@ -217,9 +217,9 @@

    Source code for sparsezoo.requests.authentication

    PUBLIC_AUTH_TYPE = "public" CREDENTIALS_YAML = os.path.abspath( - os.getenv("NM_SPARSE_ZOO_CREDENTIALS") - if os.getenv("NM_SPARSE_ZOO_CREDENTIALS") - else clean_path(os.path.join("~", ".cache", "nm_models", "credentials.yaml")) + os.getenv("SPARSEZOO_CREDENTIALS") + if os.getenv("SPARSEZOO_CREDENTIALS") + else clean_path(os.path.join("~", ".cache", "sparsezoo", "credentials.yaml")) ) CREDENTIALS_YAML_TOKEN_KEY = "nm_api_token" diff --git a/sparsezoo/_modules/sparsezoo/requests/base.html b/sparsezoo/_modules/sparsezoo/requests/base.html index 0b449cb1c2a..abf13c561cb 100644 --- a/sparsezoo/_modules/sparsezoo/requests/base.html +++ b/sparsezoo/_modules/sparsezoo/requests/base.html @@ -194,12 +194,22 @@

    Source code for sparsezoo.requests.base

     Code related to base functionality for making requests
 """
 
+import os
 from typing import Any, List, Union
 
+from sparsezoo.utils import convert_to_bool
 
-__all__ = ["BASE_API_URL", "ModelArgs"]
 
-BASE_API_URL = "https://api.neuralmagic.com/models"
+__all__ = ["BASE_API_URL", "ModelArgs", "MODELS_API_URL", "SPARSEZOO_TEST_MODE"]
+
+SPARSEZOO_TEST_MODE = convert_to_bool(os.getenv("SPARSEZOO_TEST_MODE"))
+
+BASE_API_URL = (
+    os.getenv("SPARSEZOO_API_URL")
+    if os.getenv("SPARSEZOO_API_URL")
+    else "https://api.neuralmagic.com"
+)
+MODELS_API_URL = f"{BASE_API_URL}/models"
 
 
 
    [docs]class ModelArgs:
diff --git a/sparsezoo/_modules/sparsezoo/requests/download.html b/sparsezoo/_modules/sparsezoo/requests/download.html
index abda564e707..d77fcb498db 100644
--- a/sparsezoo/_modules/sparsezoo/requests/download.html
+++ b/sparsezoo/_modules/sparsezoo/requests/download.html
@@ -200,7 +200,7 @@ 
    Source code for sparsezoo.requests.download
     import requests
 
 from sparsezoo.requests.authentication import get_auth_header
-from sparsezoo.requests.base import BASE_API_URL, ModelArgs
+from sparsezoo.requests.base import MODELS_API_URL, SPARSEZOO_TEST_MODE, ModelArgs
 
 
 __all__ = ["download_get_request", "DOWNLOAD_PATH"]
@@ -225,16 +225,23 @@ 
    Source code for sparsezoo.requests.download
         """
     header = get_auth_header(force_token_refresh=force_token_refresh)
     path = args if isinstance(args, str) else args.stub
-    url = f"{BASE_API_URL}/{DOWNLOAD_PATH}/{path}"
+    url = f"{MODELS_API_URL}/{DOWNLOAD_PATH}/{path}"
 
     if file_name:
         url = f"{url}/{file_name}"
 
+    download_args = []
+
     if hasattr(args, "release_version") and args.release_version:
-        url = f"{url}?release_version={args.release_version}"
+        download_args.append(f"release_version={args.release_version}")
 
-    _LOGGER.debug(f"GET download from {url}")
+    if SPARSEZOO_TEST_MODE:
+        download_args.append("increment_download=False")
 
+    if download_args:
+        url = f"{url}?{'&'.join(download_args)}"
+
+    _LOGGER.debug(f"GET download from {url}")
     response = requests.get(url=url, headers=header)
     response.raise_for_status()
     response_json = response.json()
diff --git a/sparsezoo/_modules/sparsezoo/requests/search.html b/sparsezoo/_modules/sparsezoo/requests/search.html
index 6398446f30d..84da3df5027 100644
--- a/sparsezoo/_modules/sparsezoo/requests/search.html
+++ b/sparsezoo/_modules/sparsezoo/requests/search.html
@@ -200,7 +200,7 @@ 
    Source code for sparsezoo.requests.search
     import requests
 
 from sparsezoo.requests.authentication import get_auth_header
-from sparsezoo.requests.base import BASE_API_URL, ModelArgs
+from sparsezoo.requests.base import MODELS_API_URL, ModelArgs
 
 
 __all__ = ["search_get_request", "SEARCH_PATH"]
@@ -237,10 +237,10 @@ 
    Source code for sparsezoo.requests.search
         search_args.extend([f"page={page}", f"page_length={page_length}"])
 
     if args.release_version:
-        search_args.extend(f"release_version={args.release_version}")
+        search_args.append(f"release_version={args.release_version}")
 
     search_args = "&".join(search_args)
-    url = f"{BASE_API_URL}/{SEARCH_PATH}/{args.model_url_root}?{search_args}"
+    url = f"{MODELS_API_URL}/{SEARCH_PATH}/{args.model_url_root}?{search_args}"
 
     _LOGGER.info(f"Searching objects from {url}")
     response_json = requests.get(url=url, headers=header).json()
diff --git a/sparsezoo/_modules/sparsezoo/utils/helpers.html b/sparsezoo/_modules/sparsezoo/utils/helpers.html
index 3d1d51c8726..f195de4e214 100644
--- a/sparsezoo/_modules/sparsezoo/utils/helpers.html
+++ b/sparsezoo/_modules/sparsezoo/utils/helpers.html
@@ -196,7 +196,7 @@ 
    Source code for sparsezoo.utils.helpers
     
 import errno
 import os
-from typing import Union
+from typing import Any, Union
 
 from tqdm import auto, tqdm, tqdm_notebook
 
@@ -204,6 +204,7 @@ 
    Source code for sparsezoo.utils.helpers
     __all__ = [
     "CACHE_DIR",
     "clean_path",
+    "convert_to_bool",
     "create_dirs",
     "create_parent_dirs",
     "create_tqdm_auto_constructor",
@@ -221,6 +222,18 @@ 
    Source code for sparsezoo.utils.helpers
         return os.path.abspath(os.path.expanduser(path))
    
 
 
+
    [docs]def convert_to_bool(val: Any):
+    """
+    :param val: a value
+    :return: False if value is a Falsy value e.g. 0, f, false, None, otherwise True.
+    """
+    return (
+        bool(val)
+        if not isinstance(val, str)
+        else bool(val) and "f" not in val.lower() and "0" not in val.lower()
+    )
    
+
+
 
    [docs]def create_dirs(path: str):
     """
     :param path: the directory path to try and create
diff --git a/sparsezoo/_static/underscore-1.3.1.js b/sparsezoo/_static/underscore-1.3.1.js
deleted file mode 100644
index 208d4cd890c..00000000000
--- a/sparsezoo/_static/underscore-1.3.1.js
+++ /dev/null
@@ -1,999 +0,0 @@
-//     Underscore.js 1.3.1
-//     (c) 2009-2012 Jeremy Ashkenas, DocumentCloud Inc.
-//     Underscore is freely distributable under the MIT license.
-//     Portions of Underscore are inspired or borrowed from Prototype,
-//     Oliver Steele's Functional, and John Resig's Micro-Templating.
-//     For all details and documentation:
-//     http://documentcloud.github.com/underscore
-
-(function() {
-
-  // Baseline setup
-  // --------------
-
-  // Establish the root object, `window` in the browser, or `global` on the server.
-  var root = this;
-
-  // Save the previous value of the `_` variable.
-  var previousUnderscore = root._;
-
-  // Establish the object that gets returned to break out of a loop iteration.
-  var breaker = {};
-
-  // Save bytes in the minified (but not gzipped) version:
-  var ArrayProto = Array.prototype, ObjProto = Object.prototype, FuncProto = Function.prototype;
-
-  // Create quick reference variables for speed access to core prototypes.
-  var slice            = ArrayProto.slice,
-      unshift          = ArrayProto.unshift,
-      toString         = ObjProto.toString,
-      hasOwnProperty   = ObjProto.hasOwnProperty;
-
-  // All **ECMAScript 5** native function implementations that we hope to use
-  // are declared here.
-  var
-    nativeForEach      = ArrayProto.forEach,
-    nativeMap          = ArrayProto.map,
-    nativeReduce       = ArrayProto.reduce,
-    nativeReduceRight  = ArrayProto.reduceRight,
-    nativeFilter       = ArrayProto.filter,
-    nativeEvery        = ArrayProto.every,
-    nativeSome         = ArrayProto.some,
-    nativeIndexOf      = ArrayProto.indexOf,
-    nativeLastIndexOf  = ArrayProto.lastIndexOf,
-    nativeIsArray      = Array.isArray,
-    nativeKeys         = Object.keys,
-    nativeBind         = FuncProto.bind;
-
-  // Create a safe reference to the Underscore object for use below.
-  var _ = function(obj) { return new wrapper(obj); };
-
-  // Export the Underscore object for **Node.js**, with
-  // backwards-compatibility for the old `require()` API. If we're in
-  // the browser, add `_` as a global object via a string identifier,
-  // for Closure Compiler "advanced" mode.
-  if (typeof exports !== 'undefined') {
-    if (typeof module !== 'undefined' && module.exports) {
-      exports = module.exports = _;
-    }
-    exports._ = _;
-  } else {
-    root['_'] = _;
-  }
-
-  // Current version.
-  _.VERSION = '1.3.1';
-
-  // Collection Functions
-  // --------------------
-
-  // The cornerstone, an `each` implementation, aka `forEach`.
-  // Handles objects with the built-in `forEach`, arrays, and raw objects.
-  // Delegates to **ECMAScript 5**'s native `forEach` if available.
-  var each = _.each = _.forEach = function(obj, iterator, context) {
-    if (obj == null) return;
-    if (nativeForEach && obj.forEach === nativeForEach) {
-      obj.forEach(iterator, context);
-    } else if (obj.length === +obj.length) {
-      for (var i = 0, l = obj.length; i < l; i++) {
-        if (i in obj && iterator.call(context, obj[i], i, obj) === breaker) return;
-      }
-    } else {
-      for (var key in obj) {
-        if (_.has(obj, key)) {
-          if (iterator.call(context, obj[key], key, obj) === breaker) return;
-        }
-      }
-    }
-  };
-
-  // Return the results of applying the iterator to each element.
-  // Delegates to **ECMAScript 5**'s native `map` if available.
-  _.map = _.collect = function(obj, iterator, context) {
-    var results = [];
-    if (obj == null) return results;
-    if (nativeMap && obj.map === nativeMap) return obj.map(iterator, context);
-    each(obj, function(value, index, list) {
-      results[results.length] = iterator.call(context, value, index, list);
-    });
-    if (obj.length === +obj.length) results.length = obj.length;
-    return results;
-  };
-
-  // **Reduce** builds up a single result from a list of values, aka `inject`,
-  // or `foldl`. Delegates to **ECMAScript 5**'s native `reduce` if available.
-  _.reduce = _.foldl = _.inject = function(obj, iterator, memo, context) {
-    var initial = arguments.length > 2;
-    if (obj == null) obj = [];
-    if (nativeReduce && obj.reduce === nativeReduce) {
-      if (context) iterator = _.bind(iterator, context);
-      return initial ? obj.reduce(iterator, memo) : obj.reduce(iterator);
-    }
-    each(obj, function(value, index, list) {
-      if (!initial) {
-        memo = value;
-        initial = true;
-      } else {
-        memo = iterator.call(context, memo, value, index, list);
-      }
-    });
-    if (!initial) throw new TypeError('Reduce of empty array with no initial value');
-    return memo;
-  };
-
-  // The right-associative version of reduce, also known as `foldr`.
-  // Delegates to **ECMAScript 5**'s native `reduceRight` if available.
-  _.reduceRight = _.foldr = function(obj, iterator, memo, context) {
-    var initial = arguments.length > 2;
-    if (obj == null) obj = [];
-    if (nativeReduceRight && obj.reduceRight === nativeReduceRight) {
-      if (context) iterator = _.bind(iterator, context);
-      return initial ? obj.reduceRight(iterator, memo) : obj.reduceRight(iterator);
-    }
-    var reversed = _.toArray(obj).reverse();
-    if (context && !initial) iterator = _.bind(iterator, context);
-    return initial ? _.reduce(reversed, iterator, memo, context) : _.reduce(reversed, iterator);
-  };
-
-  // Return the first value which passes a truth test. Aliased as `detect`.
-  _.find = _.detect = function(obj, iterator, context) {
-    var result;
-    any(obj, function(value, index, list) {
-      if (iterator.call(context, value, index, list)) {
-        result = value;
-        return true;
-      }
-    });
-    return result;
-  };
-
-  // Return all the elements that pass a truth test.
-  // Delegates to **ECMAScript 5**'s native `filter` if available.
-  // Aliased as `select`.
-  _.filter = _.select = function(obj, iterator, context) {
-    var results = [];
-    if (obj == null) return results;
-    if (nativeFilter && obj.filter === nativeFilter) return obj.filter(iterator, context);
-    each(obj, function(value, index, list) {
-      if (iterator.call(context, value, index, list)) results[results.length] = value;
-    });
-    return results;
-  };
-
-  // Return all the elements for which a truth test fails.
-  _.reject = function(obj, iterator, context) {
-    var results = [];
-    if (obj == null) return results;
-    each(obj, function(value, index, list) {
-      if (!iterator.call(context, value, index, list)) results[results.length] = value;
-    });
-    return results;
-  };
-
-  // Determine whether all of the elements match a truth test.
-  // Delegates to **ECMAScript 5**'s native `every` if available.
-  // Aliased as `all`.
-  _.every = _.all = function(obj, iterator, context) {
-    var result = true;
-    if (obj == null) return result;
-    if (nativeEvery && obj.every === nativeEvery) return obj.every(iterator, context);
-    each(obj, function(value, index, list) {
-      if (!(result = result && iterator.call(context, value, index, list))) return breaker;
-    });
-    return result;
-  };
-
-  // Determine if at least one element in the object matches a truth test.
-  // Delegates to **ECMAScript 5**'s native `some` if available.
-  // Aliased as `any`.
-  var any = _.some = _.any = function(obj, iterator, context) {
-    iterator || (iterator = _.identity);
-    var result = false;
-    if (obj == null) return result;
-    if (nativeSome && obj.some === nativeSome) return obj.some(iterator, context);
-    each(obj, function(value, index, list) {
-      if (result || (result = iterator.call(context, value, index, list))) return breaker;
-    });
-    return !!result;
-  };
-
-  // Determine if a given value is included in the array or object using `===`.
-  // Aliased as `contains`.
-  _.include = _.contains = function(obj, target) {
-    var found = false;
-    if (obj == null) return found;
-    if (nativeIndexOf && obj.indexOf === nativeIndexOf) return obj.indexOf(target) != -1;
-    found = any(obj, function(value) {
-      return value === target;
-    });
-    return found;
-  };
-
-  // Invoke a method (with arguments) on every item in a collection.
-  _.invoke = function(obj, method) {
-    var args = slice.call(arguments, 2);
-    return _.map(obj, function(value) {
-      return (_.isFunction(method) ? method || value : value[method]).apply(value, args);
-    });
-  };
-
-  // Convenience version of a common use case of `map`: fetching a property.
-  _.pluck = function(obj, key) {
-    return _.map(obj, function(value){ return value[key]; });
-  };
-
-  // Return the maximum element or (element-based computation).
-  _.max = function(obj, iterator, context) {
-    if (!iterator && _.isArray(obj)) return Math.max.apply(Math, obj);
-    if (!iterator && _.isEmpty(obj)) return -Infinity;
-    var result = {computed : -Infinity};
-    each(obj, function(value, index, list) {
-      var computed = iterator ? iterator.call(context, value, index, list) : value;
-      computed >= result.computed && (result = {value : value, computed : computed});
-    });
-    return result.value;
-  };
-
-  // Return the minimum element (or element-based computation).
-  _.min = function(obj, iterator, context) {
-    if (!iterator && _.isArray(obj)) return Math.min.apply(Math, obj);
-    if (!iterator && _.isEmpty(obj)) return Infinity;
-    var result = {computed : Infinity};
-    each(obj, function(value, index, list) {
-      var computed = iterator ? iterator.call(context, value, index, list) : value;
-      computed < result.computed && (result = {value : value, computed : computed});
-    });
-    return result.value;
-  };
-
-  // Shuffle an array.
-  _.shuffle = function(obj) {
-    var shuffled = [], rand;
-    each(obj, function(value, index, list) {
-      if (index == 0) {
-        shuffled[0] = value;
-      } else {
-        rand = Math.floor(Math.random() * (index + 1));
-        shuffled[index] = shuffled[rand];
-        shuffled[rand] = value;
-      }
-    });
-    return shuffled;
-  };
-
-  // Sort the object's values by a criterion produced by an iterator.
-  _.sortBy = function(obj, iterator, context) {
-    return _.pluck(_.map(obj, function(value, index, list) {
-      return {
-        value : value,
-        criteria : iterator.call(context, value, index, list)
-      };
-    }).sort(function(left, right) {
-      var a = left.criteria, b = right.criteria;
-      return a < b ? -1 : a > b ? 1 : 0;
-    }), 'value');
-  };
-
-  // Groups the object's values by a criterion. Pass either a string attribute
-  // to group by, or a function that returns the criterion.
-  _.groupBy = function(obj, val) {
-    var result = {};
-    var iterator = _.isFunction(val) ? val : function(obj) { return obj[val]; };
-    each(obj, function(value, index) {
-      var key = iterator(value, index);
-      (result[key] || (result[key] = [])).push(value);
-    });
-    return result;
-  };
-
-  // Use a comparator function to figure out at what index an object should
-  // be inserted so as to maintain order. Uses binary search.
-  _.sortedIndex = function(array, obj, iterator) {
-    iterator || (iterator = _.identity);
-    var low = 0, high = array.length;
-    while (low < high) {
-      var mid = (low + high) >> 1;
-      iterator(array[mid]) < iterator(obj) ? low = mid + 1 : high = mid;
-    }
-    return low;
-  };
-
-  // Safely convert anything iterable into a real, live array.
-  _.toArray = function(iterable) {
-    if (!iterable)                return [];
-    if (iterable.toArray)         return iterable.toArray();
-    if (_.isArray(iterable))      return slice.call(iterable);
-    if (_.isArguments(iterable))  return slice.call(iterable);
-    return _.values(iterable);
-  };
-
-  // Return the number of elements in an object.
-  _.size = function(obj) {
-    return _.toArray(obj).length;
-  };
-
-  // Array Functions
-  // ---------------
-
-  // Get the first element of an array. Passing **n** will return the first N
-  // values in the array. Aliased as `head`. The **guard** check allows it to work
-  // with `_.map`.
-  _.first = _.head = function(array, n, guard) {
-    return (n != null) && !guard ? slice.call(array, 0, n) : array[0];
-  };
-
-  // Returns everything but the last entry of the array. Especcialy useful on
-  // the arguments object. Passing **n** will return all the values in
-  // the array, excluding the last N. The **guard** check allows it to work with
-  // `_.map`.
-  _.initial = function(array, n, guard) {
-    return slice.call(array, 0, array.length - ((n == null) || guard ? 1 : n));
-  };
-
-  // Get the last element of an array. Passing **n** will return the last N
-  // values in the array. The **guard** check allows it to work with `_.map`.
-  _.last = function(array, n, guard) {
-    if ((n != null) && !guard) {
-      return slice.call(array, Math.max(array.length - n, 0));
-    } else {
-      return array[array.length - 1];
-    }
-  };
-
-  // Returns everything but the first entry of the array. Aliased as `tail`.
-  // Especially useful on the arguments object. Passing an **index** will return
-  // the rest of the values in the array from that index onward. The **guard**
-  // check allows it to work with `_.map`.
-  _.rest = _.tail = function(array, index, guard) {
-    return slice.call(array, (index == null) || guard ? 1 : index);
-  };
-
-  // Trim out all falsy values from an array.
-  _.compact = function(array) {
-    return _.filter(array, function(value){ return !!value; });
-  };
-
-  // Return a completely flattened version of an array.
-  _.flatten = function(array, shallow) {
-    return _.reduce(array, function(memo, value) {
-      if (_.isArray(value)) return memo.concat(shallow ? value : _.flatten(value));
-      memo[memo.length] = value;
-      return memo;
-    }, []);
-  };
-
-  // Return a version of the array that does not contain the specified value(s).
-  _.without = function(array) {
-    return _.difference(array, slice.call(arguments, 1));
-  };
-
-  // Produce a duplicate-free version of the array. If the array has already
-  // been sorted, you have the option of using a faster algorithm.
-  // Aliased as `unique`.
-  _.uniq = _.unique = function(array, isSorted, iterator) {
-    var initial = iterator ? _.map(array, iterator) : array;
-    var result = [];
-    _.reduce(initial, function(memo, el, i) {
-      if (0 == i || (isSorted === true ? _.last(memo) != el : !_.include(memo, el))) {
-        memo[memo.length] = el;
-        result[result.length] = array[i];
-      }
-      return memo;
-    }, []);
-    return result;
-  };
-
-  // Produce an array that contains the union: each distinct element from all of
-  // the passed-in arrays.
-  _.union = function() {
-    return _.uniq(_.flatten(arguments, true));
-  };
-
-  // Produce an array that contains every item shared between all the
-  // passed-in arrays. (Aliased as "intersect" for back-compat.)
-  _.intersection = _.intersect = function(array) {
-    var rest = slice.call(arguments, 1);
-    return _.filter(_.uniq(array), function(item) {
-      return _.every(rest, function(other) {
-        return _.indexOf(other, item) >= 0;
-      });
-    });
-  };
-
-  // Take the difference between one array and a number of other arrays.
-  // Only the elements present in just the first array will remain.
-  _.difference = function(array) {
-    var rest = _.flatten(slice.call(arguments, 1));
-    return _.filter(array, function(value){ return !_.include(rest, value); });
-  };
-
-  // Zip together multiple lists into a single array -- elements that share
-  // an index go together.
-  _.zip = function() {
-    var args = slice.call(arguments);
-    var length = _.max(_.pluck(args, 'length'));
-    var results = new Array(length);
-    for (var i = 0; i < length; i++) results[i] = _.pluck(args, "" + i);
-    return results;
-  };
-
-  // If the browser doesn't supply us with indexOf (I'm looking at you, **MSIE**),
-  // we need this function. Return the position of the first occurrence of an
-  // item in an array, or -1 if the item is not included in the array.
-  // Delegates to **ECMAScript 5**'s native `indexOf` if available.
-  // If the array is large and already in sort order, pass `true`
-  // for **isSorted** to use binary search.
-  _.indexOf = function(array, item, isSorted) {
-    if (array == null) return -1;
-    var i, l;
-    if (isSorted) {
-      i = _.sortedIndex(array, item);
-      return array[i] === item ? i : -1;
-    }
-    if (nativeIndexOf && array.indexOf === nativeIndexOf) return array.indexOf(item);
-    for (i = 0, l = array.length; i < l; i++) if (i in array && array[i] === item) return i;
-    return -1;
-  };
-
-  // Delegates to **ECMAScript 5**'s native `lastIndexOf` if available.
-  _.lastIndexOf = function(array, item) {
-    if (array == null) return -1;
-    if (nativeLastIndexOf && array.lastIndexOf === nativeLastIndexOf) return array.lastIndexOf(item);
-    var i = array.length;
-    while (i--) if (i in array && array[i] === item) return i;
-    return -1;
-  };
-
-  // Generate an integer Array containing an arithmetic progression. A port of
-  // the native Python `range()` function. See
-  // [the Python documentation](http://docs.python.org/library/functions.html#range).
-  _.range = function(start, stop, step) {
-    if (arguments.length <= 1) {
-      stop = start || 0;
-      start = 0;
-    }
-    step = arguments[2] || 1;
-
-    var len = Math.max(Math.ceil((stop - start) / step), 0);
-    var idx = 0;
-    var range = new Array(len);
-
-    while(idx < len) {
-      range[idx++] = start;
-      start += step;
-    }
-
-    return range;
-  };
-
-  // Function (ahem) Functions
-  // ------------------
-
-  // Reusable constructor function for prototype setting.
-  var ctor = function(){};
-
-  // Create a function bound to a given object (assigning `this`, and arguments,
-  // optionally). Binding with arguments is also known as `curry`.
-  // Delegates to **ECMAScript 5**'s native `Function.bind` if available.
-  // We check for `func.bind` first, to fail fast when `func` is undefined.
-  _.bind = function bind(func, context) {
-    var bound, args;
-    if (func.bind === nativeBind && nativeBind) return nativeBind.apply(func, slice.call(arguments, 1));
-    if (!_.isFunction(func)) throw new TypeError;
-    args = slice.call(arguments, 2);
-    return bound = function() {
-      if (!(this instanceof bound)) return func.apply(context, args.concat(slice.call(arguments)));
-      ctor.prototype = func.prototype;
-      var self = new ctor;
-      var result = func.apply(self, args.concat(slice.call(arguments)));
-      if (Object(result) === result) return result;
-      return self;
-    };
-  };
-
-  // Bind all of an object's methods to that object. Useful for ensuring that
-  // all callbacks defined on an object belong to it.
-  _.bindAll = function(obj) {
-    var funcs = slice.call(arguments, 1);
-    if (funcs.length == 0) funcs = _.functions(obj);
-    each(funcs, function(f) { obj[f] = _.bind(obj[f], obj); });
-    return obj;
-  };
-
-  // Memoize an expensive function by storing its results.
-  _.memoize = function(func, hasher) {
-    var memo = {};
-    hasher || (hasher = _.identity);
-    return function() {
-      var key = hasher.apply(this, arguments);
-      return _.has(memo, key) ? memo[key] : (memo[key] = func.apply(this, arguments));
-    };
-  };
-
-  // Delays a function for the given number of milliseconds, and then calls
-  // it with the arguments supplied.
-  _.delay = function(func, wait) {
-    var args = slice.call(arguments, 2);
-    return setTimeout(function(){ return func.apply(func, args); }, wait);
-  };
-
-  // Defers a function, scheduling it to run after the current call stack has
-  // cleared.
-  _.defer = function(func) {
-    return _.delay.apply(_, [func, 1].concat(slice.call(arguments, 1)));
-  };
-
-  // Returns a function, that, when invoked, will only be triggered at most once
-  // during a given window of time.
-  _.throttle = function(func, wait) {
-    var context, args, timeout, throttling, more;
-    var whenDone = _.debounce(function(){ more = throttling = false; }, wait);
-    return function() {
-      context = this; args = arguments;
-      var later = function() {
-        timeout = null;
-        if (more) func.apply(context, args);
-        whenDone();
-      };
-      if (!timeout) timeout = setTimeout(later, wait);
-      if (throttling) {
-        more = true;
-      } else {
-        func.apply(context, args);
-      }
-      whenDone();
-      throttling = true;
-    };
-  };
-
-  // Returns a function, that, as long as it continues to be invoked, will not
-  // be triggered. The function will be called after it stops being called for
-  // N milliseconds.
-  _.debounce = function(func, wait) {
-    var timeout;
-    return function() {
-      var context = this, args = arguments;
-      var later = function() {
-        timeout = null;
-        func.apply(context, args);
-      };
-      clearTimeout(timeout);
-      timeout = setTimeout(later, wait);
-    };
-  };
-
-  // Returns a function that will be executed at most one time, no matter how
-  // often you call it. Useful for lazy initialization.
-  _.once = function(func) {
-    var ran = false, memo;
-    return function() {
-      if (ran) return memo;
-      ran = true;
-      return memo = func.apply(this, arguments);
-    };
-  };
-
-  // Returns the first function passed as an argument to the second,
-  // allowing you to adjust arguments, run code before and after, and
-  // conditionally execute the original function.
-  _.wrap = function(func, wrapper) {
-    return function() {
-      var args = [func].concat(slice.call(arguments, 0));
-      return wrapper.apply(this, args);
-    };
-  };
-
-  // Returns a function that is the composition of a list of functions, each
-  // consuming the return value of the function that follows.
-  _.compose = function() {
-    var funcs = arguments;
-    return function() {
-      var args = arguments;
-      for (var i = funcs.length - 1; i >= 0; i--) {
-        args = [funcs[i].apply(this, args)];
-      }
-      return args[0];
-    };
-  };
-
-  // Returns a function that will only be executed after being called N times.
-  _.after = function(times, func) {
-    if (times <= 0) return func();
-    return function() {
-      if (--times < 1) { return func.apply(this, arguments); }
-    };
-  };
-
-  // Object Functions
-  // ----------------
-
-  // Retrieve the names of an object's properties.
-  // Delegates to **ECMAScript 5**'s native `Object.keys`
-  _.keys = nativeKeys || function(obj) {
-    if (obj !== Object(obj)) throw new TypeError('Invalid object');
-    var keys = [];
-    for (var key in obj) if (_.has(obj, key)) keys[keys.length] = key;
-    return keys;
-  };
-
-  // Retrieve the values of an object's properties.
-  _.values = function(obj) {
-    return _.map(obj, _.identity);
-  };
-
-  // Return a sorted list of the function names available on the object.
-  // Aliased as `methods`
-  _.functions = _.methods = function(obj) {
-    var names = [];
-    for (var key in obj) {
-      if (_.isFunction(obj[key])) names.push(key);
-    }
-    return names.sort();
-  };
-
-  // Extend a given object with all the properties in passed-in object(s).
-  _.extend = function(obj) {
-    each(slice.call(arguments, 1), function(source) {
-      for (var prop in source) {
-        obj[prop] = source[prop];
-      }
-    });
-    return obj;
-  };
-
-  // Fill in a given object with default properties.
-  _.defaults = function(obj) {
-    each(slice.call(arguments, 1), function(source) {
-      for (var prop in source) {
-        if (obj[prop] == null) obj[prop] = source[prop];
-      }
-    });
-    return obj;
-  };
-
-  // Create a (shallow-cloned) duplicate of an object.
-  _.clone = function(obj) {
-    if (!_.isObject(obj)) return obj;
-    return _.isArray(obj) ? obj.slice() : _.extend({}, obj);
-  };
-
-  // Invokes interceptor with the obj, and then returns obj.
-  // The primary purpose of this method is to "tap into" a method chain, in
-  // order to perform operations on intermediate results within the chain.
-  _.tap = function(obj, interceptor) {
-    interceptor(obj);
-    return obj;
-  };
-
-  // Internal recursive comparison function.
-  function eq(a, b, stack) {
-    // Identical objects are equal. `0 === -0`, but they aren't identical.
-    // See the Harmony `egal` proposal: http://wiki.ecmascript.org/doku.php?id=harmony:egal.
-    if (a === b) return a !== 0 || 1 / a == 1 / b;
-    // A strict comparison is necessary because `null == undefined`.
-    if (a == null || b == null) return a === b;
-    // Unwrap any wrapped objects.
-    if (a._chain) a = a._wrapped;
-    if (b._chain) b = b._wrapped;
-    // Invoke a custom `isEqual` method if one is provided.
-    if (a.isEqual && _.isFunction(a.isEqual)) return a.isEqual(b);
-    if (b.isEqual && _.isFunction(b.isEqual)) return b.isEqual(a);
-    // Compare `[[Class]]` names.
-    var className = toString.call(a);
-    if (className != toString.call(b)) return false;
-    switch (className) {
-      // Strings, numbers, dates, and booleans are compared by value.
-      case '[object String]':
-        // Primitives and their corresponding object wrappers are equivalent; thus, `"5"` is
-        // equivalent to `new String("5")`.
-        return a == String(b);
-      case '[object Number]':
-        // `NaN`s are equivalent, but non-reflexive. An `egal` comparison is performed for
-        // other numeric values.
-        return a != +a ? b != +b : (a == 0 ? 1 / a == 1 / b : a == +b);
-      case '[object Date]':
-      case '[object Boolean]':
-        // Coerce dates and booleans to numeric primitive values. Dates are compared by their
-        // millisecond representations. Note that invalid dates with millisecond representations
-        // of `NaN` are not equivalent.
-        return +a == +b;
-      // RegExps are compared by their source patterns and flags.
-      case '[object RegExp]':
-        return a.source == b.source &&
-               a.global == b.global &&
-               a.multiline == b.multiline &&
-               a.ignoreCase == b.ignoreCase;
-    }
-    if (typeof a != 'object' || typeof b != 'object') return false;
-    // Assume equality for cyclic structures. The algorithm for detecting cyclic
-    // structures is adapted from ES 5.1 section 15.12.3, abstract operation `JO`.
-    var length = stack.length;
-    while (length--) {
-      // Linear search. Performance is inversely proportional to the number of
-      // unique nested structures.
-      if (stack[length] == a) return true;
-    }
-    // Add the first object to the stack of traversed objects.
-    stack.push(a);
-    var size = 0, result = true;
-    // Recursively compare objects and arrays.
-    if (className == '[object Array]') {
-      // Compare array lengths to determine if a deep comparison is necessary.
-      size = a.length;
-      result = size == b.length;
-      if (result) {
-        // Deep compare the contents, ignoring non-numeric properties.
-        while (size--) {
-          // Ensure commutative equality for sparse arrays.
-          if (!(result = size in a == size in b && eq(a[size], b[size], stack))) break;
-        }
-      }
-    } else {
-      // Objects with different constructors are not equivalent.
-      if ('constructor' in a != 'constructor' in b || a.constructor != b.constructor) return false;
-      // Deep compare objects.
-      for (var key in a) {
-        if (_.has(a, key)) {
-          // Count the expected number of properties.
-          size++;
-          // Deep compare each member.
-          if (!(result = _.has(b, key) && eq(a[key], b[key], stack))) break;
-        }
-      }
-      // Ensure that both objects contain the same number of properties.
-      if (result) {
-        for (key in b) {
-          if (_.has(b, key) && !(size--)) break;
-        }
-        result = !size;
-      }
-    }
-    // Remove the first object from the stack of traversed objects.
-    stack.pop();
-    return result;
-  }
-
-  // Perform a deep comparison to check if two objects are equal.
-  _.isEqual = function(a, b) {
-    return eq(a, b, []);
-  };
-
-  // Is a given array, string, or object empty?
-  // An "empty" object has no enumerable own-properties.
-  _.isEmpty = function(obj) {
-    if (_.isArray(obj) || _.isString(obj)) return obj.length === 0;
-    for (var key in obj) if (_.has(obj, key)) return false;
-    return true;
-  };
-
-  // Is a given value a DOM element?
-  _.isElement = function(obj) {
-    return !!(obj && obj.nodeType == 1);
-  };
-
-  // Is a given value an array?
-  // Delegates to ECMA5's native Array.isArray
-  _.isArray = nativeIsArray || function(obj) {
-    return toString.call(obj) == '[object Array]';
-  };
-
-  // Is a given variable an object?
-  _.isObject = function(obj) {
-    return obj === Object(obj);
-  };
-
-  // Is a given variable an arguments object?
-  _.isArguments = function(obj) {
-    return toString.call(obj) == '[object Arguments]';
-  };
-  if (!_.isArguments(arguments)) {
-    _.isArguments = function(obj) {
-      return !!(obj && _.has(obj, 'callee'));
-    };
-  }
-
-  // Is a given value a function?
-  _.isFunction = function(obj) {
-    return toString.call(obj) == '[object Function]';
-  };
-
-  // Is a given value a string?
-  _.isString = function(obj) {
-    return toString.call(obj) == '[object String]';
-  };
-
-  // Is a given value a number?
-  _.isNumber = function(obj) {
-    return toString.call(obj) == '[object Number]';
-  };
-
-  // Is the given value `NaN`?
-  _.isNaN = function(obj) {
-    // `NaN` is the only value for which `===` is not reflexive.
-    return obj !== obj;
-  };
-
-  // Is a given value a boolean?
-  _.isBoolean = function(obj) {
-    return obj === true || obj === false || toString.call(obj) == '[object Boolean]';
-  };
-
-  // Is a given value a date?
-  _.isDate = function(obj) {
-    return toString.call(obj) == '[object Date]';
-  };
-
-  // Is the given value a regular expression?
-  _.isRegExp = function(obj) {
-    return toString.call(obj) == '[object RegExp]';
-  };
-
-  // Is a given value equal to null?
-  _.isNull = function(obj) {
-    return obj === null;
-  };
-
-  // Is a given variable undefined?
-  _.isUndefined = function(obj) {
-    return obj === void 0;
-  };
-
-  // Has own property?
-  _.has = function(obj, key) {
-    return hasOwnProperty.call(obj, key);
-  };
-
-  // Utility Functions
-  // -----------------
-
-  // Run Underscore.js in *noConflict* mode, returning the `_` variable to its
-  // previous owner. Returns a reference to the Underscore object.
-  _.noConflict = function() {
-    root._ = previousUnderscore;
-    return this;
-  };
-
-  // Keep the identity function around for default iterators.
-  _.identity = function(value) {
-    return value;
-  };
-
-  // Run a function **n** times.
-  _.times = function (n, iterator, context) {
-    for (var i = 0; i < n; i++) iterator.call(context, i);
-  };
-
-  // Escape a string for HTML interpolation.
-  _.escape = function(string) {
-    return (''+string).replace(/&/g, '&').replace(//g, '>').replace(/"/g, '"').replace(/'/g, ''').replace(/\//g,'/');
-  };
-
-  // Add your own custom functions to the Underscore object, ensuring that
-  // they're correctly added to the OOP wrapper as well.
-  _.mixin = function(obj) {
-    each(_.functions(obj), function(name){
-      addToWrapper(name, _[name] = obj[name]);
-    });
-  };
-
-  // Generate a unique integer id (unique within the entire client session).
-  // Useful for temporary DOM ids.
-  var idCounter = 0;
-  _.uniqueId = function(prefix) {
-    var id = idCounter++;
-    return prefix ? prefix + id : id;
-  };
-
-  // By default, Underscore uses ERB-style template delimiters, change the
-  // following template settings to use alternative delimiters.
-  _.templateSettings = {
-    evaluate    : /<%([\s\S]+?)%>/g,
-    interpolate : /<%=([\s\S]+?)%>/g,
-    escape      : /<%-([\s\S]+?)%>/g
-  };
-
-  // When customizing `templateSettings`, if you don't want to define an
-  // interpolation, evaluation or escaping regex, we need one that is
-  // guaranteed not to match.
-  var noMatch = /.^/;
-
-  // Within an interpolation, evaluation, or escaping, remove HTML escaping
-  // that had been previously added.
-  var unescape = function(code) {
-    return code.replace(/\\\\/g, '\\').replace(/\\'/g, "'");
-  };
-
-  // JavaScript micro-templating, similar to John Resig's implementation.
-  // Underscore templating handles arbitrary delimiters, preserves whitespace,
-  // and correctly escapes quotes within interpolated code.
-  _.template = function(str, data) {
-    var c  = _.templateSettings;
-    var tmpl = 'var __p=[],print=function(){__p.push.apply(__p,arguments);};' +
-      'with(obj||{}){__p.push(\'' +
-      str.replace(/\\/g, '\\\\')
-         .replace(/'/g, "\\'")
-         .replace(c.escape || noMatch, function(match, code) {
-           return "',_.escape(" + unescape(code) + "),'";
-         })
-         .replace(c.interpolate || noMatch, function(match, code) {
-           return "'," + unescape(code) + ",'";
-         })
-         .replace(c.evaluate || noMatch, function(match, code) {
-           return "');" + unescape(code).replace(/[\r\n\t]/g, ' ') + ";__p.push('";
-         })
-         .replace(/\r/g, '\\r')
-         .replace(/\n/g, '\\n')
-         .replace(/\t/g, '\\t')
-         + "');}return __p.join('');";
-    var func = new Function('obj', '_', tmpl);
-    if (data) return func(data, _);
-    return function(data) {
-      return func.call(this, data, _);
-    };
-  };
-
-  // Add a "chain" function, which will delegate to the wrapper.
-  _.chain = function(obj) {
-    return _(obj).chain();
-  };
-
-  // The OOP Wrapper
-  // ---------------
-
-  // If Underscore is called as a function, it returns a wrapped object that
-  // can be used OO-style. This wrapper holds altered versions of all the
-  // underscore functions. Wrapped objects may be chained.
-  var wrapper = function(obj) { this._wrapped = obj; };
-
-  // Expose `wrapper.prototype` as `_.prototype`
-  _.prototype = wrapper.prototype;
-
-  // Helper function to continue chaining intermediate results.
-  var result = function(obj, chain) {
-    return chain ? _(obj).chain() : obj;
-  };
-
-  // A method to easily add functions to the OOP wrapper.
-  var addToWrapper = function(name, func) {
-    wrapper.prototype[name] = function() {
-      var args = slice.call(arguments);
-      unshift.call(args, this._wrapped);
-      return result(func.apply(_, args), this._chain);
-    };
-  };
-
-  // Add all of the Underscore functions to the wrapper object.
-  _.mixin(_);
-
-  // Add all mutator Array functions to the wrapper.
-  each(['pop', 'push', 'reverse', 'shift', 'sort', 'splice', 'unshift'], function(name) {
-    var method = ArrayProto[name];
-    wrapper.prototype[name] = function() {
-      var wrapped = this._wrapped;
-      method.apply(wrapped, arguments);
-      var length = wrapped.length;
-      if ((name == 'shift' || name == 'splice') && length === 0) delete wrapped[0];
-      return result(wrapped, this._chain);
-    };
-  });
-
-  // Add all accessor Array functions to the wrapper.
-  each(['concat', 'join', 'slice'], function(name) {
-    var method = ArrayProto[name];
-    wrapper.prototype[name] = function() {
-      return result(method.apply(this._wrapped, arguments), this._chain);
-    };
-  });
-
-  // Start chaining a wrapped Underscore object.
-  wrapper.prototype.chain = function() {
-    this._chain = true;
-    return this;
-  };
-
-  // Extracts the result from a wrapped and chained object.
-  wrapper.prototype.value = function() {
-    return this._wrapped;
-  };
-
-}).call(this);
diff --git a/sparsezoo/api/sparsezoo.utils.html b/sparsezoo/api/sparsezoo.utils.html
index f9e88f92165..7e2a0b2ad7d 100644
--- a/sparsezoo/api/sparsezoo.utils.html
+++ b/sparsezoo/api/sparsezoo.utils.html
@@ -481,6 +481,19 @@ 
    Submodules
+
    
+sparsezoo.utils.helpers.convert_to_bool(val: Any)[source]ΒΆ
    
+
    
+
    Parameters
    
+
    val – a value
    
+
    
+
    Returns
    
+
    False if value is a Falsy value e.g. 0, f, false, None, otherwise True.
    
+
    
+
    
+
    
+
 
    
 
    
 sparsezoo.utils.helpers.create_dirs(path: str)[source]ΒΆ
    
diff --git a/sparsezoo/genindex.html b/sparsezoo/genindex.html
index 330413f1aad..c5cc3304a36 100644
--- a/sparsezoo/genindex.html
+++ b/sparsezoo/genindex.html
@@ -244,11 +244,13 @@ 
    C
  • chunk_size() (sparsezoo.utils.downloader.DownloadProgress property)
    • - - +
    • content_length() (sparsezoo.utils.downloader.DownloadProgress property) +
      • +
    • convert_to_bool() (in module sparsezoo.utils.helpers)
    • create_dirs() (in module sparsezoo.utils.helpers)
      • diff --git a/sparsezoo/objects.inv b/sparsezoo/objects.inv index 2f1de0f98b23d71221d2f3b7b6afe67a87ce78bd..f416814066e7162bcf71ae37b3e2067b0283f39e 100644 GIT binary patch delta 2103 zcmV-72*~%55u6c_e1A=In>ZN9@A(v-*}aBMns#TmH@8VUnN5?do9^!PqLD$i)nJKA zB8~g$S3)4b!GO^N2iq9L@2__~dX)(llKkX+mh9ecd6dRvb~eKa{Y@56f{oh7zu0G| zzs^oi$|qY)+29x5+pCm?igGqPZ+d_4MIMn@wrE-hZPM037=L3a>57IplkNo8-5<*j z$Vy*Q!W1KFQnA_}v^;B#@D_Pb-PdF4QWlbAl4NvBb-e2q1YeOXS-bN@pyYjt#9AQTz<8rEF&HAQL8@;A&B@7 z7ISP;DWnNOODqXm3A`mgxOhY>ZPeM$8c`b_!Rf37-+v;h(j^2u184VOX|TSO1dDKk zDji@LAlJQ^E&WNNG0`^JAldLlsr?#b0Td0{J*2N(2IwmP4LrX5rmKXu;f~xzOPMcR zn4$>=3f}3jyX?l{TBL^T#R@_}up&`Q*hP@9#`Tlo(VVg8aj0nh6CP|kb5PuE^ac!- z_2V@OLl!-r5P=mJNE;Ng7@Gs&LN*4eh=EWKyS$(7ZFVFR#b40iyW89U#$ck4 zU!k#!tM}LUSKicG?d02$C}6=SQ}cbQpa+-UW@I*|(mCon9B*rGU*q!tJe9hu>CJXw z_f9lJvR?E{sge^I0~Wddsb3&-q<<5-Pk#fkT3Xt`Dk6z)F=P@{qj12hqjm>@e+VKi`N`NP%*4(Z*aXrw|0J}+e;-IOZ0dk*Vp zU`$N23evBrgJl{+RtRt-?^UY8Yd}9Lftg(CmR?7yV3e)FGk~!p{Al?UYqkue>VG|7 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of file diff --git a/sparsify/.buildinfo b/sparsify/.buildinfo index c3ec77a0265..636037ed56f 100644 --- a/sparsify/.buildinfo +++ b/sparsify/.buildinfo @@ -1,4 +1,4 @@ # Sphinx build info version 1 # This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done. -config: cd6aecb3959fbdcdc01354dd6c526f1d +config: 1c59754a360c99e5ecdcbf7e391c9f66 tags: 645f666f9bcd5a90fca523b33c5a78b7 diff --git a/sparsify/_static/doctools.js b/sparsify/_static/doctools.js index 61ac9d266f9..144884ea651 100644 --- a/sparsify/_static/doctools.js +++ b/sparsify/_static/doctools.js @@ -29,14 +29,9 @@ if (!window.console || !console.firebug) { /** * small helper function to urldecode strings - * - * See https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/decodeURIComponent#Decoding_query_parameters_from_a_URL */ jQuery.urldecode = function(x) { - if (!x) { - return x - } - return decodeURIComponent(x.replace(/\+/g, ' ')); + return decodeURIComponent(x).replace(/\+/g, ' '); }; /** diff --git a/sparsify/_static/language_data.js b/sparsify/_static/language_data.js index 863704b310d..0e7dc7e9ef0 100644 --- a/sparsify/_static/language_data.js +++ b/sparsify/_static/language_data.js @@ -13,8 +13,7 @@ var stopwords = ["a","and","are","as","at","be","but","by","for","if","in","into","is","it","near","no","not","of","on","or","such","that","the","their","then","there","these","they","this","to","was","will","with"]; -/* Non-minified version is copied as a separate JS file, is available */ - +/* Non-minified version JS is _stemmer.js if file is provided */ /** * Porter Stemmer */ @@ -200,6 +199,7 @@ var Stemmer = function() { + var splitChars = (function() { var result = {}; var singles = [96, 180, 187, 191, 215, 247, 749, 885, 903, 907, 909, 930, 1014, 1648, diff --git a/sparsify/_static/pygments.css b/sparsify/_static/pygments.css index 691aeb82d00..20c4814dcf0 100644 --- a/sparsify/_static/pygments.css +++ b/sparsify/_static/pygments.css @@ -1,10 +1,5 @@ -pre { line-height: 125%; } -td.linenos .normal { color: inherit; background-color: transparent; padding-left: 5px; padding-right: 5px; } -span.linenos { color: inherit; background-color: transparent; padding-left: 5px; padding-right: 5px; } -td.linenos .special { color: #000000; background-color: #ffffc0; padding-left: 5px; padding-right: 5px; } -span.linenos.special { color: #000000; background-color: #ffffc0; padding-left: 5px; padding-right: 5px; } .highlight .hll { background-color: #ffffcc } -.highlight { background: #eeffcc; } +.highlight { background: #eeffcc; } .highlight .c { color: #408090; font-style: italic } /* Comment */ .highlight .err { border: 1px solid #FF0000 } /* Error */ .highlight .k { color: #007020; font-weight: bold } /* Keyword */ diff --git a/sparsify/_static/searchtools.js b/sparsify/_static/searchtools.js index 1a90152eb0e..6fc9e7f3338 100644 --- a/sparsify/_static/searchtools.js +++ b/sparsify/_static/searchtools.js @@ -248,7 +248,7 @@ var Search = { // results left, load the summary and display it if (results.length) { var item = results.pop(); - var listItem = $('
    • '); + var listItem = $('
    • '); var requestUrl = ""; var linkUrl = ""; if (DOCUMENTATION_OPTIONS.BUILDER === 'dirhtml') { @@ -273,9 +273,9 @@ var Search = { if (item[3]) { listItem.append($(' (' + item[3] + ')')); Search.output.append(listItem); - setTimeout(function() { + listItem.slideDown(5, function() { displayNextItem(); - }, 5); + }); } else if (DOCUMENTATION_OPTIONS.HAS_SOURCE) { $.ajax({url: requestUrl, dataType: "text", @@ -285,16 +285,16 @@ var Search = { listItem.append(Search.makeSearchSummary(data, searchterms, hlterms)); } Search.output.append(listItem); - setTimeout(function() { + listItem.slideDown(5, function() { displayNextItem(); - }, 5); + }); }}); } else { // no source available, just display title Search.output.append(listItem); - setTimeout(function() { + listItem.slideDown(5, function() { displayNextItem(); - }, 5); + }); } } // search finished, update title and status message @@ -379,13 +379,6 @@ var Search = { return results; }, - /** - * See https://developer.mozilla.org/en-US/docs/Web/JavaScript/Guide/Regular_Expressions - */ - escapeRegExp : function(string) { - return string.replace(/[.*+\-?^${}()|[\]\\]/g, '\\$&'); // $& means the whole matched string - }, - /** * search for full-text terms in the index */ @@ -409,14 +402,13 @@ var Search = { ]; // add support for partial matches if (word.length > 2) { - var word_regex = this.escapeRegExp(word); for (var w in terms) { - if (w.match(word_regex) && !terms[word]) { + if (w.match(word) && !terms[word]) { _o.push({files: terms[w], score: Scorer.partialTerm}) } } for (var w in titleterms) { - if (w.match(word_regex) && !titleterms[word]) { + if (w.match(word) && !titleterms[word]) { _o.push({files: titleterms[w], score: Scorer.partialTitle}) } } diff --git a/sparsify/_static/underscore.js b/sparsify/_static/underscore.js index 166240ef2dd..5b55f32beac 100644 --- a/sparsify/_static/underscore.js +++ b/sparsify/_static/underscore.js @@ -1,6 +1,31 @@ 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      sparsifysparsify.blueprints package
    • sparsify.models package
    • sparsify.schemas package
    • sparsify.utils package
    • sparsify.workers package

  • Submodules
    • -
  • sparsify.app module
    • -
  • sparsify.log module
    • -
  • Module contents
    • +
  • sparsify.app module
    • +
  • sparsify.log module
    • +
  • Module contents
    • diff --git a/sparsify/api/sparsify.blueprints.code_samples.html b/sparsify/api/sparsify.blueprints.code_samples.html index b37b48c11a0..050d64dc722 100644 --- a/sparsify/api/sparsify.blueprints.code_samples.html +++ b/sparsify/api/sparsify.blueprints.code_samples.html @@ -109,18 +109,18 @@
  • sparsify.blueprints package
  • sparsify.models package
    • @@ -130,9 +130,9 @@
  • Submodules
    • -
  • sparsify.app module
    • -
  • sparsify.log module
    • -
  • Module contents
    • +
  • sparsify.app module
    • +
  • sparsify.log module
    • +
  • Module contents
    • @@ -220,25 +220,14 @@

    Submodules

    sparsify.blueprints.code_samples.pytorch__integration moduleΒΆ

    -
    -

    sparsify.blueprints.code_samples.pytorch__training moduleΒΆ

    -
    -
    -sparsify.blueprints.code_samples.pytorch__training.train(working_dir: str, config_path: str, model: torch.nn.modules.module.Module, train_dataset: torch.utils.data.dataset.Dataset, val_dataset: torch.utils.data.dataset.Dataset, batch_size: int, optim_const: Callable[torch.nn.modules.module.Module, torch.optim.optimizer.Optimizer], loss: Union[sparseml.pytorch.utils.loss.LossWrapper, Callable[[Any, Any], torch.Tensor]], devices: str)[source]ΒΆ
    -

    Dataset setup

    -
    - -
    -
    -sparsify.blueprints.code_samples.pytorch__training.train_setup()[source]ΒΆ
    -
    - +
    +

    sparsify.blueprints.code_samples.pytorch__training moduleΒΆ

    sparsify.blueprints.code_samples.tensorflow__integration moduleΒΆ

    -
    -

    Module contentsΒΆ

    +
    +

    Module contentsΒΆ

    diff --git a/sparsify/api/sparsify.blueprints.html b/sparsify/api/sparsify.blueprints.html index 9ae170f8ea0..de570d11ef3 100644 --- a/sparsify/api/sparsify.blueprints.html +++ b/sparsify/api/sparsify.blueprints.html @@ -109,18 +109,18 @@
  • sparsify.blueprints package
  • sparsify.models package
    • @@ -130,9 +130,9 @@
  • Submodules
    • -
  • sparsify.app module
    • -
  • sparsify.log module
    • -
  • Module contents
    • +
  • sparsify.app module
    • +
  • sparsify.log module
    • +
  • Module contents
    • @@ -219,20 +219,20 @@

    Subpackagessparsify.blueprints.code_samples package
  • sparsify.blueprints.utils package
    • @@ -241,54 +241,41 @@

    Subpackages

    SubmodulesΒΆ

    -
    -

    sparsify.blueprints.errors moduleΒΆ

    -

    Flask blueprint setup for handling errors for the server application

    +
    +

    sparsify.blueprints.errors moduleΒΆ

    -
    -

    sparsify.blueprints.jobs moduleΒΆ

    -

    Server routes related to the jobs routes

    +
    +

    sparsify.blueprints.jobs moduleΒΆ

    -
    -

    sparsify.blueprints.model_repo moduleΒΆ

    -

    Server routes related to the model repo routes

    +
    +

    sparsify.blueprints.model_repo moduleΒΆ

    -
    -

    sparsify.blueprints.projects moduleΒΆ

    -

    Server routes related to projects

    +
    +

    sparsify.blueprints.projects moduleΒΆ

    -
    -

    sparsify.blueprints.projects_benchmarks moduleΒΆ

    -

    Server routes related to benchmarks

    +
    +

    sparsify.blueprints.projects_benchmarks moduleΒΆ

    -
    -

    sparsify.blueprints.projects_data moduleΒΆ

    -

    Server routes related to projects data files

    +
    +

    sparsify.blueprints.projects_data moduleΒΆ

    -
    -

    sparsify.blueprints.projects_model moduleΒΆ

    -

    Server routes related to the project’s model routes

    +
    +

    sparsify.blueprints.projects_model moduleΒΆ

    -
    -

    sparsify.blueprints.projects_optimizations moduleΒΆ

    -

    Server routes related to project optimizations and modifiers

    +
    +

    sparsify.blueprints.projects_optimizations moduleΒΆ

    -
    -

    sparsify.blueprints.projects_profiles moduleΒΆ

    -

    Server routes related to loss and performance profiles

    +
    +

    sparsify.blueprints.projects_profiles moduleΒΆ

    -
    -

    sparsify.blueprints.system moduleΒΆ

    -

    Server routes related to the system

    +
    +

    sparsify.blueprints.system moduleΒΆ

    -
    -

    sparsify.blueprints.ui moduleΒΆ

    -

    Flask blueprint setup for serving UI files for the server application

    +
    +

    sparsify.blueprints.ui moduleΒΆ

    -
    -

    Module contentsΒΆ

    -

    Flask blueprints setup for serving UI files and making api requests for the -server application

    +
    +

    Module contentsΒΆ

    diff --git a/sparsify/api/sparsify.blueprints.utils.html b/sparsify/api/sparsify.blueprints.utils.html index f468e19a5b5..8622b494f59 100644 --- a/sparsify/api/sparsify.blueprints.utils.html +++ b/sparsify/api/sparsify.blueprints.utils.html @@ -109,18 +109,18 @@
  • sparsify.blueprints package
  • sparsify.models package
    • @@ -130,9 +130,9 @@
  • Submodules
    • -
  • sparsify.app module
    • -
  • sparsify.log module
    • -
  • Module contents
    • +
  • sparsify.app module
    • +
  • sparsify.log module
    • +
  • Module contents
    • @@ -217,542 +217,26 @@

    sparsify.blueprints.utils package

    SubmodulesΒΆ

    -
    -

    sparsify.blueprints.utils.helpers moduleΒΆ

    -

    Helper functions and classes for flask blueprints

    -
    -
    -exception sparsify.blueprints.utils.helpers.HTTPNotFoundError(*args: object)[source]ΒΆ
    -

    Bases: Exception

    -

    Expected error raised when a 404 should be encountered by the user

    -
    - +
    +

    sparsify.blueprints.utils.helpers moduleΒΆ

    -
    -

    sparsify.blueprints.utils.projects moduleΒΆ

    -

    Helper functions and classes for flask blueprints specific to projects

    -
    -
    -sparsify.blueprints.utils.projects.get_project_by_id(project_id: str) → sparsify.models.projects.Project[source]ΒΆ
    -

    Get a project by its project_id, with project model and project data joined.

    -
    -
    Parameters
    -

    project_id – project id of the project

    -
    -
    Returns
    -

    Project with the project id

    -
    -
    -
    - -
    -
    -sparsify.blueprints.utils.projects.get_project_model_by_project_id(project_id: str, raise_not_found: bool = True) → sparsify.models.projects_model.ProjectModel[source]ΒΆ
    -

    Get a project model by its project_id

    -
    -
    Parameters
    -
      -

    • project_id – project id of the project model

      • -

    • raise_not_found – if no model is found raise an HTTPNotFoundError, -otherwise return the result no matter what

      • -
    -
    -
    Returns
    -

    Project model with the project id

    -
    -
    -
    - +
    +

    sparsify.blueprints.utils.projects moduleΒΆ

    -
    -

    sparsify.blueprints.utils.projects_benchmark moduleΒΆ

    -

    Helper functions and classes for flask blueprints specific to project benchmark

    -
    -
    -sparsify.blueprints.utils.projects_benchmark.get_project_benchmark_by_ids(project_id: str, benchmark_id: str) → sparsify.models.projects_benchmark.ProjectBenchmark[source]ΒΆ
    -

    Get a project benchmark by its project_id and benchmark_id

    -
    -
    Parameters
    -
      -

    • project_id – project id of the optimizer

      • -

    • benchmark_id – benchmark id of the optimizer

      • -
    -
    -
    Returns
    -

    Project benchmark with provided ids

    -
    -
    -
    - +
    +

    sparsify.blueprints.utils.projects_benchmark moduleΒΆ

    -
    -

    sparsify.blueprints.utils.projects_data moduleΒΆ

    -

    Helper functions and classes for flask blueprints specific to projects data

    -
    -
    -sparsify.blueprints.utils.projects_data.get_project_data_by_ids(project_id: str, data_id: str) → sparsify.models.projects_data.ProjectData[source]ΒΆ
    -
    - -
    -
    -sparsify.blueprints.utils.projects_data.validate_model_data(data_path: str, model_path: str)[source]ΒΆ
    -
    - +
    +

    sparsify.blueprints.utils.projects_data moduleΒΆ

    -
    -

    sparsify.blueprints.utils.projects_optimizations moduleΒΆ

    -

    Helper functions and classes for flask blueprints specific to project optimizations

    -
    -
    -class sparsify.blueprints.utils.projects_optimizations.OptimEpochs(training_epochs, start_epoch, stabilization_epochs, pruning_epochs, fine_tuning_epochs, end_epoch, pruning_start_epoch, pruning_end_epoch, pruning_update_frequency, fine_tuning_start_epoch)ΒΆ
    -

    Bases: tuple

    -
    -
    -property end_epochΒΆ
    -

    Alias for field number 5

    -
    - -
    -
    -property fine_tuning_epochsΒΆ
    -

    Alias for field number 4

    -
    - -
    -
    -property fine_tuning_start_epochΒΆ
    -

    Alias for field number 9

    -
    - -
    -
    -property pruning_end_epochΒΆ
    -

    Alias for field number 7

    -
    - -
    -
    -property pruning_epochsΒΆ
    -

    Alias for field number 3

    -
    - -
    -
    -property pruning_start_epochΒΆ
    -

    Alias for field number 6

    -
    - -
    -
    -property pruning_update_frequencyΒΆ
    -

    Alias for field number 8

    -
    - -
    -
    -property stabilization_epochsΒΆ
    -

    Alias for field number 2

    -
    - -
    -
    -property start_epochΒΆ
    -

    Alias for field number 1

    -
    - -
    -
    -property training_epochsΒΆ
    -

    Alias for field number 0

    -
    - -
    - -
    -
    -sparsify.blueprints.utils.projects_optimizations.create_config(project: sparsify.models.projects.Project, optim: sparsify.models.projects_optimizations.ProjectOptimization, framework: str) → str[source]ΒΆ
    -

    Creates a optimization config yaml for a given project and optimization

    -
    -
    Parameters
    -
      -

    • project – project to create with

      • -

    • optim – project optimizer to create with

      • -

    • framework – the framework to create the config for

      • -
    -
    -
    -
    - -
    -
    -sparsify.blueprints.utils.projects_optimizations.default_epochs_distribution(training_epochs: Union[None, int]) → sparsify.blueprints.utils.projects_optimizations.OptimEpochs[source]ΒΆ
    -

    Create default epochs distribution for optimizing a model given a number -of training epochs.

    -
    -
    Parameters
    -

    training_epochs – the original training epochs, if not set will default to 100

    -
    -
    Returns
    -

    the default epochs distribution for optimizing a model

    -
    -
    -
    - -
    -
    -sparsify.blueprints.utils.projects_optimizations.default_pruning_settings()[source]ΒΆ
    -
    -
    Returns
    -

    the default pruning settings for optimizing a model

    -
    -
    -
    - -
    -
    -sparsify.blueprints.utils.projects_optimizations.get_profiles_by_id(profile_perf_id: Union[None, str], profile_loss_id: Union[None, str]) → Tuple[sparsify.models.projects_profiles.ProjectPerfProfile, sparsify.models.projects_profiles.ProjectLossProfile][source]ΒΆ
    -

    Get a performance and loss profile by their ids. -If not found will return None instead of raising not found.

    -
    -
    Parameters
    -
      -

    • profile_perf_id – id of the performance profile to get

      • -

    • profile_loss_id – id of the loss profile to get

      • -
    -
    -
    Returns
    -

    tuple containing (performance profile, loss profile)

    -
    -
    -
    - -
    -
    -sparsify.blueprints.utils.projects_optimizations.get_project_optimizer_by_ids(project_id: str, optim_id: str) → sparsify.models.projects_optimizations.ProjectOptimization[source]ΒΆ
    -

    Get a project optimizer by its project_id and optim_id

    -
    -
    Parameters
    -
      -

    • project_id – project id of the optimizer

      • -

    • optim_id – optim id of the optimizer

      • -
    -
    -
    Returns
    -

    Project optimizer with provided ids

    -
    -
    -
    - -
    -
    -sparsify.blueprints.utils.projects_optimizations.optim_lr_sched_default_mods(training_init_lr: Optional[float], training_final_lr: Optional[float], start_epoch: Optional[float], start_fine_tuning_epoch: Optional[float], end_epoch: Optional[float]) → List[Dict[str, Any]][source]ΒΆ
    -

    Default modifiers for an LR schedule for pruning a model. -If training_init_lr is set, adds a set LR modifier. -If training_init_lr and training_final_lr are set, adds a step LR modifier.

    -
    -
    Parameters
    -
      -

    • training_init_lr – the initial LR for training

      • -

    • training_final_lr – the final LR for training

      • -

    • start_epoch – the epoch training should start at

      • -

    • start_fine_tuning_epoch – the epoch fine tuning should start at

      • -

    • end_epoch – the final epoch for training

      • -
    -
    -
    Returns
    -

    the default modifiers for an LR schedule

    -
    -
    -
    - -
    -
    -sparsify.blueprints.utils.projects_optimizations.optim_lr_sched_updater(lr_sched: sparsify.models.projects_optimizations.ProjectOptimizationModifierLRSchedule, lr_mods: Union[None, List[Dict[str, Any]]] = None, global_start_epoch: Union[None, float] = None, global_end_epoch: Union[None, float] = None)[source]ΒΆ
    -

    Update an LR schedule DB model. -Will always update schedule level details from the contained lr_mods

    -
    -
    Parameters
    -
      -

    • lr_sched – the DB model

      • -

    • lr_mods – the mods to set, if any

      • -

    • global_start_epoch – the optim’s start epoch, -if set and greater than current start_epoch will set start_epoch to this

      • -

    • global_end_epoch – the optim’s end epoch, -if set and less than current end_epoch will set end_epoch to this

      • -
    -
    -
    -
    - -
    -
    -sparsify.blueprints.utils.projects_optimizations.optim_pruning_updater(pruning: sparsify.models.projects_optimizations.ProjectOptimizationModifierPruning, start_epoch: Union[None, float] = None, end_epoch: Union[None, float] = None, update_frequency: Union[None, float] = None, pruning_settings: Optional[sparsify.blueprints.utils.projects_optimizations_pruning.PruningSettings] = None, mask_type: Optional[str] = None, sparsity: Union[None, float] = None, balance_perf_loss: Union[None, float] = None, filter_min_sparsity: Union[None, float] = None, filter_min_perf_gain: Union[None, float] = None, filter_min_recovery: Union[None, float] = None, nodes: Union[None, List[Dict[str, Any]]] = None, model: Union[None, sparsify.models.projects_model.ProjectModel] = None, profile_perf: Union[None, sparsify.models.projects_profiles.ProjectPerfProfile] = None, profile_loss: Union[None, sparsify.models.projects_profiles.ProjectLossProfile] = None, global_start_epoch: Union[None, float] = None, global_end_epoch: Union[None, float] = None)[source]ΒΆ
    -

    Update a pruning DB model

    -
    -
    Parameters
    -
      -

    • pruning – the DB model

      • -

    • start_epoch – the start_epoch to set, if any

      • -

    • end_epoch – the end_epoch to set, if any

      • -

    • update_frequency – the update_frequency to set, if any

      • -

    • pruning_settings – the pruning_settings to use for updating / -automatically generating new sparsity levels for nodes. -If provided, overrides mask_type, sparsity, balance_perf_loss, -filter_min_sparsity, filter_min_perf_gain, and filter_min_recovery

      • -

    • mask_type – the mask_type to set, if any

      • -

    • sparsity – the sparsity level to set, if set will update / -automatically generate new sparsity levels for nodes

      • -

    • balance_perf_loss – the balance_perf_loss to set, if any

      • -

    • filter_min_sparsity – the filter_min_sparsity to set, if any

      • -

    • filter_min_perf_gain – the filter_min_perf_gain to set, if any

      • -

    • filter_min_recovery – the filter_min_recovery to set, if any

      • -

    • nodes – the nodes to set, if set will update -node and model metrics for perf and loss

      • -

    • model – the model to use to update values with

      • -

    • profile_perf – the performance profile to use to update values with, -if set will update nodes

      • -

    • profile_loss – the loss profile to use to update values with, -if set will update nodes

      • -

    • global_start_epoch – the optim’s start epoch, -if set and greater than current start_epoch will set start_epoch to this

      • -

    • global_end_epoch – the optim’s end epoch, -if set and less than current end_epoch will set end_epoch to this

      • -
    -
    -
    -
    - -
    -
    -sparsify.blueprints.utils.projects_optimizations.optim_trainable_default_nodes(default_trainable: bool, model_analysis: Dict, node_overrides: Union[None, List[Dict[str, Any]]] = None) → List[Dict[str, Any]][source]ΒΆ
    -

    Create the default trainable nodes for optimizing a model. -Creates a node for all prunable nodes in the model with trainable set to -default_trainable.

    -
    -
    Parameters
    -
      -

    • default_trainable – True to default all prunable nodes to trainable, -False otherwise

      • -

    • model_analysis – the analysis for the model

      • -

    • node_overrides – specific node overrides to use instead of default_trainable

      • -
    -
    -
    Returns
    -

    the default trainable nodes

    -
    -
    -
    - -
    -
    -sparsify.blueprints.utils.projects_optimizations.optim_trainable_updater(trainable: sparsify.models.projects_optimizations.ProjectOptimizationModifierTrainable, analysis: Dict[str, List], start_epoch: Union[None, float] = None, end_epoch: Union[None, float] = None, nodes: Union[None, List[Dict[str, Any]]] = None, default_trainable: Union[None, bool] = None, global_start_epoch: Union[None, float] = None, global_end_epoch: Union[None, float] = None)[source]ΒΆ
    -

    Update a trainable DB model

    -
    -
    Parameters
    -
      -

    • trainable – the DB model

      • -

    • analysis – model analysis

      • -

    • start_epoch – the start_epoch to set, if any

      • -

    • end_epoch – the end_epoch to set, if any

      • -

    • nodes – the nodes to set, if any

      • -

    • default_trainable – the default trainable to set, if any

      • -

    • global_start_epoch – the optim’s start epoch, -if set and greater than current start_epoch will set start_epoch to this

      • -

    • global_end_epoch – the optim’s end epoch, -if set and less than current end_epoch will set end_epoch to this

      • -
    -
    -
    -
    - -
    -
    -sparsify.blueprints.utils.projects_optimizations.optim_updater(optim: sparsify.models.projects_optimizations.ProjectOptimization, name: Optional[str] = None, profile_perf: Union[None, sparsify.models.projects_profiles.ProjectPerfProfile] = - 1, profile_loss: Union[None, sparsify.models.projects_profiles.ProjectLossProfile] = - 1, start_epoch: Union[None, float] = None, end_epoch: Union[None, float] = None, mod_start_epoch: Union[None, float] = None, mod_end_epoch: Union[None, float] = None)[source]ΒΆ
    -

    Update an optim DB model

    -
    -
    Parameters
    -
      -

    • optim – the DB model

      • -

    • name – the name to set, if any

      • -

    • profile_perf – the performance profile to set, if any

      • -

    • profile_loss – the loss profile to set, if any

      • -

    • start_epoch – the start_epoch to set, if any

      • -

    • end_epoch – the end_epoch to set, if any

      • -

    • mod_start_epoch – a contained modifier’s updated start epoch, -if set and less than current start_epoch will set start_epoch to this

      • -

    • mod_end_epoch – a contained modifier’s updated end epoch, -if set and greater than current end_epoch will set end_epoch to this

      • -
    -
    -
    -
    - -
    -
    -sparsify.blueprints.utils.projects_optimizations.optim_validate_and_get_project_by_id(project_id: str) → sparsify.models.projects.Project[source]ΒΆ
    -

    Get a project by project id and validate that it is setup correctly for optims. -Raises not found errors for no project -and validation errors for no project model, and no project analysis.

    -
    -
    Parameters
    -

    project_id – id of the project to get

    -
    -
    Returns
    -

    the retrieved project

    -
    -
    -
    - -
    -
    -sparsify.blueprints.utils.projects_optimizations.sparse_training_available(project: sparsify.models.projects.Project)[source]ΒΆ
    -
    - -
    -
    -sparsify.blueprints.utils.projects_optimizations.validate_pruning_nodes(project: sparsify.models.projects.Project, nodes: List[Dict[str, Any]])[source]ΒΆ
    -

    Validate a list of given nodes are prunable in the model. -Raises a validation error if nodes are set that are not prunable.

    -
    -
    Parameters
    -
      -

    • project – the project to validate with

      • -

    • nodes – the nodes to validate

      • -
    -
    -
    -
    - +
    +

    sparsify.blueprints.utils.projects_optimizations moduleΒΆ

    -
    -

    sparsify.blueprints.utils.projects_optimizations_pruning moduleΒΆ

    -

    Helper functions and classes for flask blueprints specific to project optimizations -for pruning

    -
    -
    -class sparsify.blueprints.utils.projects_optimizations_pruning.PruningModelEvaluator(model_analysis: Dict, perf_analysis: Union[None, Dict], loss_analysis: Union[None, Dict])[source]ΒΆ
    -

    Bases: object

    -

    Evaluator for a model for pruning. -Able to estimate the effect of pruning on a model and each prunable node in a model -for performance, loss, etc

    -
    -
    Parameters
    -
      -

    • model_analysis – analysis of the model

      • -

    • perf_analysis – performance analysis of the model, if any

      • -

    • loss_analysis – loss analysis of the model, if any

      • -
    -
    -
    -
    -
    -EVAL_SENSITIVITY_SPARSITY = 0.95ΒΆ
    -
    - -
    -
    -MAX_NODE_SPARSITY = 0.95ΒΆ
    -
    - -
    -
    -apply_node_overrides(node_overrides: List[Dict[str, Any]])[source]ΒΆ
    -

    Apply any node override sparsity levels to the current evaluated nodes. -Must be called after eval_pruning if eval_pruning is invoked at all -to have any effect.

    -
    -
    Parameters
    -

    node_overrides – the override sparsity levels for nodes to set with

    -
    -
    -
    - -
    -
    -eval_baseline(baseline_sparsity: float)[source]ΒΆ
    -

    Evaluate the baseline (no performance data, only loss) recommended sparsities -to assign for each node to best maximize recovery.

    -
    -
    Parameters
    -

    baseline_sparsity – the baseline_sparsity to use and evaluate with

    -
    -
    -
    - -
    -
    -eval_pruning(settings: sparsify.blueprints.utils.projects_optimizations_pruning.PruningSettings)[source]ΒΆ
    -

    Evaluate the model to assign the evaluate sparsity levels for each node -in the model given the input pruning settings.

    -
    -
    Parameters
    -

    settings – the pruning settings to use and evaluate with

    -
    -
    -
    - -
    -
    -to_dict_values() → Tuple[List[Dict[str, Any]], Dict[str, Any]][source]ΒΆ
    -

    Create the dictionary values containing the recommended sparsity levels -for pruning and their estimated times. -eval_baseline and (eval_pruning and/or apply_node_overrides) -must be called before

    -
    -
    Returns
    -

    a tuple containing (model info, list of node info)

    -
    -
    -
    - -
    - -
    -
    -class sparsify.blueprints.utils.projects_optimizations_pruning.PruningSettings(mask_type, sparsity, balance_perf_loss, filter_min_sparsity, filter_min_perf_gain, filter_min_recovery)ΒΆ
    -

    Bases: tuple

    -
    -
    -property balance_perf_lossΒΆ
    -

    Alias for field number 2

    -
    - -
    -
    -property filter_min_perf_gainΒΆ
    -

    Alias for field number 4

    -
    - -
    -
    -property filter_min_recoveryΒΆ
    -

    Alias for field number 5

    -
    - -
    -
    -property filter_min_sparsityΒΆ
    -

    Alias for field number 3

    -
    - -
    -
    -property mask_typeΒΆ
    -

    Alias for field number 0

    -
    - -
    -
    -property sparsityΒΆ
    -

    Alias for field number 1

    -
    - -
    - +
    +

    sparsify.blueprints.utils.projects_optimizations_pruning moduleΒΆ

    -
    -

    Module contentsΒΆ

    -

    Utility functions and classes for flask blueprints

    +
    +

    Module contentsΒΆ

    diff --git a/sparsify/api/sparsify.html b/sparsify/api/sparsify.html index e8d20609eb0..7c346665af7 100644 --- a/sparsify/api/sparsify.html +++ b/sparsify/api/sparsify.html @@ -114,9 +114,9 @@
  • Submodules
    • -
  • sparsify.app module
    • -
  • sparsify.log module
    • -
  • Module contents
    • +
  • sparsify.app module
    • +
  • sparsify.log module
    • +
  • Module contents
    • @@ -203,84 +203,84 @@

    Subpackagessparsify.blueprints.code_samples package
  • sparsify.blueprints.utils package
  • Submodules
    • -
  • sparsify.blueprints.errors module
    • -
  • sparsify.blueprints.jobs module
    • -
  • sparsify.blueprints.model_repo module
    • -
  • sparsify.blueprints.projects module
    • -
  • sparsify.blueprints.projects_benchmarks module
    • -
  • sparsify.blueprints.projects_data module
    • -
  • sparsify.blueprints.projects_model module
    • -
  • sparsify.blueprints.projects_optimizations module
    • -
  • sparsify.blueprints.projects_profiles module
    • -
  • sparsify.blueprints.system module
    • -
  • sparsify.blueprints.ui module
    • -
  • Module contents
    • +
  • sparsify.blueprints.errors module
    • +
  • sparsify.blueprints.jobs module
    • +
  • sparsify.blueprints.model_repo module
    • +
  • sparsify.blueprints.projects module
    • +
  • sparsify.blueprints.projects_benchmarks module
    • +
  • sparsify.blueprints.projects_data module
    • +
  • sparsify.blueprints.projects_model module
    • +
  • sparsify.blueprints.projects_optimizations module
    • +
  • sparsify.blueprints.projects_profiles module
    • +
  • sparsify.blueprints.system module
    • +
  • sparsify.blueprints.ui module
    • +
  • Module contents
  • sparsify.models package
  • sparsify.schemas package
  • sparsify.utils package
  • sparsify.workers package
    • @@ -289,61 +289,14 @@

    Subpackages

    SubmodulesΒΆ

    -
    -

    sparsify.app moduleΒΆ

    -
    -
    -sparsify.app.main()[source]ΒΆ
    -
    - -
    -
    -sparsify.app.run(working_dir: str, host: str, port: int, debug: bool, logging_level: str, ui_path: Optional[str])[source]ΒΆ
    -
    - +
    +

    sparsify.app moduleΒΆ

    -
    -

    sparsify.log moduleΒΆ

    -

    Root logging file to handle standard logging setups for the package

    -
    -
    -sparsify.log.get_main_logger() → logging.Logger[source]ΒΆ
    -
    -
    Returns
    -

    a main logger that can be used in external scripts for logging -in a standard format that is consistent with other loggers in sparsify

    -
    -
    -
    - -
    -
    -sparsify.log.get_root_logger() → logging.Logger[source]ΒΆ
    -
    -
    Returns
    -

    the logger used for the sparsify root package that all -other loggers in that namespace are created from

    -
    -
    -
    - -
    -
    -sparsify.log.set_logging_level(level: int)[source]ΒΆ
    -

    Set the logging level for the MAIN and ROOT loggers along with all -loggers created in the sparsify namespace

    -
    -
    Parameters
    -

    level – the log level to set; ex: logging.INFO

    -
    -
    -
    - +
    +

    sparsify.log moduleΒΆ

    -
    -

    Module contentsΒΆ

    -

    Code for handling the server portions of sparsify to benchmark and optimize -neural networks

    +
    +

    Module contentsΒΆ

    diff --git a/sparsify/api/sparsify.models.html b/sparsify/api/sparsify.models.html index 9e042949060..37ace2355ba 100644 --- a/sparsify/api/sparsify.models.html +++ b/sparsify/api/sparsify.models.html @@ -109,16 +109,16 @@
  • sparsify.blueprints package
  • sparsify.models package
  • sparsify.schemas package
    • @@ -127,9 +127,9 @@
  • Submodules
    • -
  • sparsify.app module
    • -
  • sparsify.log module
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  • Module contents
    • +
  • sparsify.app module
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  • sparsify.log module
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  • Module contents
    • @@ -212,1539 +212,35 @@

    sparsify.models package

    SubmodulesΒΆ

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    sparsify.models.base moduleΒΆ

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    Base DB model classes for the server

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    -class sparsify.models.base.BaseCreatedModifiedModel(*args, **kwargs)[source]ΒΆ
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    Bases: sparsify.models.base.BaseModel

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    Base peewee model that includes created and modified timestamp functionality

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    -DoesNotExistΒΆ
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    alias of sparsify.models.base.BaseCreatedModifiedModelDoesNotExist

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    -created = <DateTimeField: BaseCreatedModifiedModel.created>ΒΆ
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    -id = <AutoField: BaseCreatedModifiedModel.id>ΒΆ
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    -modified = <DateTimeField: BaseCreatedModifiedModel.modified>ΒΆ
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    -save(*args, **kwargs)[source]ΒΆ
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    -class sparsify.models.base.BaseModel(*args, **kwargs)[source]ΒΆ
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    Bases: peewee.Model

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    Base peewee model all DB models must extend from

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    -DoesNotExistΒΆ
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    alias of sparsify.models.base.BaseModelDoesNotExist

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    -id = <AutoField: BaseModel.id>ΒΆ
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    -refresh()[source]ΒΆ
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    Refresh the data for the model instance from the DB

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    -class sparsify.models.base.CSVField(null=False, index=False, unique=False, column_name=None, default=None, primary_key=False, constraints=None, sequence=None, collation=None, unindexed=False, choices=None, help_text=None, verbose_name=None, index_type=None, db_column=None, _hidden=False)[source]ΒΆ
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    Bases: peewee.TextField

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    CSV field for handling lists of strings in a peewee database

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    -db_value(value)[source]ΒΆ
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    -python_value(value)[source]ΒΆ
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    -class sparsify.models.base.CSVFloatField(null=False, index=False, unique=False, column_name=None, default=None, primary_key=False, constraints=None, sequence=None, collation=None, unindexed=False, choices=None, help_text=None, verbose_name=None, index_type=None, db_column=None, _hidden=False)[source]ΒΆ
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    Bases: sparsify.models.base.CSVField

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    CSV field for handling lists of floats in a peewee database

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    -python_value(value)[source]ΒΆ
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    -class sparsify.models.base.CSVIntField(null=False, index=False, unique=False, column_name=None, default=None, primary_key=False, constraints=None, sequence=None, collation=None, unindexed=False, choices=None, help_text=None, verbose_name=None, index_type=None, db_column=None, _hidden=False)[source]ΒΆ
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    Bases: sparsify.models.base.CSVField

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    CSV field for handling lists of integers in a peewee database

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    -python_value(value)[source]ΒΆ
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    -class sparsify.models.base.FileStorage[source]ΒΆ
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    Bases: object

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    Class for handling local file storage and the path that is located at. -Used for storing large files that would not be good in the DB -such as model and data files.

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    -init(root_path: str)[source]ΒΆ
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    Initialize the file storage class for a given path

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    Parameters
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    root_path – the root path on the local file system -for where to store files

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    -property root_pathΒΆ
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    the root path on the local file system for where to store files

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    Type
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    return

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    -class sparsify.models.base.ListObjField(json_dumps=None, json_loads=None, **kwargs)[source]ΒΆ
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    Bases: playhouse.sqlite_ext.JSONField

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    Field for handling lists of objects in a peewee database

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    -db_value(value)[source]ΒΆ
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    -python_value(value)[source]ΒΆ
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    sparsify.models.base moduleΒΆ

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    sparsify.models.jobs moduleΒΆ

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    DB model classes for jobs

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    -class sparsify.models.jobs.Job(*args, **kwargs)[source]ΒΆ
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    Bases: sparsify.models.base.BaseModel

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    DB model for a project’s job.

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    -DoesNotExistΒΆ
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    alias of sparsify.models.jobs.JobDoesNotExist

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    -baseprojectprofile_setΒΆ
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    -created = <DateTimeField: Job.created>ΒΆ
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    -error = <TextField: Job.error>ΒΆ
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    -job_id = <CharField: Job.job_id>ΒΆ
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    -modified = <DateTimeField: Job.modified>ΒΆ
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    -progress = <JSONField: Job.progress>ΒΆ
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    -project_id = <CharField: Job.project_id>ΒΆ
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    -projectbenchmark_setΒΆ
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    -projectdata_setΒΆ
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    -projectlossprofile_setΒΆ
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    -projectmodel_setΒΆ
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    -projectperfprofile_setΒΆ
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    -save(*args, **kwargs)[source]ΒΆ
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    Override for peewee save function to update the modified date

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    -status = <JobStatusField: Job.status>ΒΆ
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    -type_ = <CharField: Job.type_>ΒΆ
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    -worker_ack = <BooleanField: Job.worker_ack>ΒΆ
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    -worker_args = <JSONField: Job.worker_args>ΒΆ
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    -class sparsify.models.jobs.JobStatus(value)[source]ΒΆ
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    Bases: enum.Enum

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    Enumerator class for tracking the status of jobs

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    -canceled = 'canceled'ΒΆ
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    -canceling = 'canceling'ΒΆ
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    -completed = 'completed'ΒΆ
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    -error = 'error'ΒΆ
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    -pending = 'pending'ΒΆ
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    -started = 'started'ΒΆ
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    -class sparsify.models.jobs.JobStatusField(null=False, index=False, unique=False, column_name=None, default=None, primary_key=False, constraints=None, sequence=None, collation=None, unindexed=False, choices=None, help_text=None, verbose_name=None, index_type=None, db_column=None, _hidden=False)[source]ΒΆ
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    Bases: peewee.Field

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    peewee DB field for saving and loading JobStatus from the database

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    -db_value(value: sparsify.models.jobs.JobStatus)[source]ΒΆ
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    -field_type = 'VARCHAR'ΒΆ
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    -python_value(value: str)[source]ΒΆ
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    sparsify.models.jobs moduleΒΆ

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    sparsify.models.projects moduleΒΆ

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    DB model classes for a project and it’s nested files

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    -class sparsify.models.projects.BaseProjectModel(*args, **kwargs)[source]ΒΆ
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    Bases: sparsify.models.base.BaseModel

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    -DoesNotExistΒΆ
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    alias of sparsify.models.projects.BaseProjectModelDoesNotExist

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    -abstract delete_filesystem()[source]ΒΆ
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    Delete the state from the local file system

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    -id = <AutoField: BaseProjectModel.id>ΒΆ
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    -abstract setup_filesystem()[source]ΒΆ
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    Setup the local file system so that it can be used with the data

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    -abstract validate_filesystem()[source]ΒΆ
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    Validate that the local file system and expected files are correct and exist

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    -class sparsify.models.projects.Project(*args, **kwargs)[source]ΒΆ
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    Bases: sparsify.models.projects.BaseProjectModel

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    DB model for a project’s data file. -A project may have multiple data files stored in the DB.

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    -DoesNotExistΒΆ
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    alias of sparsify.models.projects.ProjectDoesNotExist

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    -benchmarksΒΆ
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    -created = <DateTimeField: Project.created>ΒΆ
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    -dataΒΆ
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    -delete_filesystem()[source]ΒΆ
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    Delete the folder from the local file system -containing all of the files for the project

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    -description = <TextField: Project.description>ΒΆ
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    -property dir_pathΒΆ
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    the local directory path for where project’s files are stored

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    Type
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    return

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    -property dir_sizeΒΆ
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    Size of the folder on the local file system -containing all of the files for the project

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    -modelsΒΆ
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    -modified = <DateTimeField: Project.modified>ΒΆ
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    -name = <TextField: Project.name>ΒΆ
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    -optimsΒΆ
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    -profiles_lossΒΆ
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    -profiles_perfΒΆ
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    -project_id = <CharField: Project.project_id>ΒΆ
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    -save(*args, **kwargs)[source]ΒΆ
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    Override for peewee save function to update the modified date

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    -setup_filesystem()[source]ΒΆ
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    Setup the local file system so that it can be used with the data

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    -training_epochs = <IntegerField: Project.training_epochs>ΒΆ
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    -training_lr_final = <FloatField: Project.training_lr_final>ΒΆ
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    -training_lr_init = <FloatField: Project.training_lr_init>ΒΆ
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    -training_optimizer = <TextField: Project.training_optimizer>ΒΆ
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    -validate_filesystem()[source]ΒΆ
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    Validate that the local file system and expected files are correct and exist

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    sparsify.models.projects moduleΒΆ

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    sparsify.models.projects_benchmark moduleΒΆ

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    DB model classes for project’s benchmark

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    -class sparsify.models.projects_benchmark.ProjectBenchmark(*args, **kwargs)[source]ΒΆ
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    Bases: sparsify.models.base.BaseCreatedModifiedModel

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    DB model for a project’s benchmark

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    -DoesNotExistΒΆ
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    alias of sparsify.models.projects_benchmark.ProjectBenchmarkDoesNotExist

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    -batch_sizes = <JSONField: ProjectBenchmark.batch_sizes>ΒΆ
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    -benchmark_id = <CharField: ProjectBenchmark.benchmark_id>ΒΆ
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    -core_counts = <JSONField: ProjectBenchmark.core_counts>ΒΆ
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    -created = <DateTimeField: ProjectBenchmark.created>ΒΆ
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    -inference_models = <ListObjField: ProjectBenchmark.inference_models>ΒΆ
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    -instruction_sets = <JSONField: ProjectBenchmark.instruction_sets>ΒΆ
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    -iterations_per_check = <IntegerField: ProjectBenchmark.iterations_per_check>ΒΆ
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    -job = <ForeignKeyField: ProjectBenchmark.job>ΒΆ
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    -job_id = <ForeignKeyField: ProjectBenchmark.job>ΒΆ
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    -modified = <DateTimeField: ProjectBenchmark.modified>ΒΆ
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    -name = <TextField: ProjectBenchmark.name>ΒΆ
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    -project = <ForeignKeyField: ProjectBenchmark.project>ΒΆ
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    -project_id = <ForeignKeyField: ProjectBenchmark.project>ΒΆ
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    -result = <JSONField: ProjectBenchmark.result>ΒΆ
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    -source = <TextField: ProjectBenchmark.source>ΒΆ
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    -warmup_iterations_per_check = <IntegerField: ProjectBenchmark.warmup_iterations_per_check>ΒΆ
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    sparsify.models.projects_benchmark moduleΒΆ

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    sparsify.models.projects_data moduleΒΆ

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    DB model classes for a project’s sample data files

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    -class sparsify.models.projects_data.ProjectData(*args, **kwargs)[source]ΒΆ
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    Bases: sparsify.models.projects.BaseProjectModel

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    DB model for a project’s data file. -A project may have multiple data files stored in the DB.

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    -DoesNotExistΒΆ
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    alias of sparsify.models.projects_data.ProjectDataDoesNotExist

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    -created = <DateTimeField: ProjectData.created>ΒΆ
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    -data_id = <CharField: ProjectData.data_id>ΒΆ
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    -delete_filesystem()[source]ΒΆ
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    Delete the data file from the local file system

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    -property dir_pathΒΆ
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    the local directory path for where the data is stored

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    Type
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    return

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    -file = <TextField: ProjectData.file>ΒΆ
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    -property file_pathΒΆ
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    the local file path to the data file

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    Type
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    return

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    -job = <ForeignKeyField: ProjectData.job>ΒΆ
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    -job_id = <ForeignKeyField: ProjectData.job>ΒΆ
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    -project = <ForeignKeyField: ProjectData.project>ΒΆ
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    -project_id = <ForeignKeyField: ProjectData.project>ΒΆ
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    -setup_filesystem()[source]ΒΆ
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    Setup the local file system so that it can be used with the data

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    -source = <TextField: ProjectData.source>ΒΆ
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    -validate_filesystem()[source]ΒΆ
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    Validate that the local file system and expected files are correct and exist

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    sparsify.models.projects_data moduleΒΆ

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    sparsify.models.projects_model moduleΒΆ

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    DB model classes for a project’s model file

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    -class sparsify.models.projects_model.ProjectModel(*args, **kwargs)[source]ΒΆ
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    Bases: sparsify.models.projects.BaseProjectModel

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    DB model for a project’s model file. -A project must have only one model file stored in the DB.

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    -DoesNotExistΒΆ
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    alias of sparsify.models.projects_model.ProjectModelDoesNotExist

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    -analysis = <JSONField: ProjectModel.analysis>ΒΆ
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    -created = <DateTimeField: ProjectModel.created>ΒΆ
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    -delete_filesystem()[source]ΒΆ
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    Delete the model file from the local file system

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    -property dir_pathΒΆ
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    the local directory path for where the model file is stored

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    Type
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    return

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    -file = <TextField: ProjectModel.file>ΒΆ
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    -property file_pathΒΆ
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    the local file path to the data file

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    Type
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    return

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    -job = <ForeignKeyField: ProjectModel.job>ΒΆ
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    -job_id = <ForeignKeyField: ProjectModel.job>ΒΆ
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    -model_id = <CharField: ProjectModel.model_id>ΒΆ
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    -project = <ForeignKeyField: ProjectModel.project>ΒΆ
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    -project_id = <ForeignKeyField: ProjectModel.project>ΒΆ
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    -setup_filesystem()[source]ΒΆ
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    Setup the local file system so that it can be used with the data

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    -source = <TextField: ProjectModel.source>ΒΆ
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    -validate_filesystem()[source]ΒΆ
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    Validate that the local file system and expected files are correct and exist

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    sparsify.models.projects_model moduleΒΆ

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    sparsify.models.projects_optimizations moduleΒΆ

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    DB model classes for project’s optimizations and modifiers

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    -class sparsify.models.projects_optimizations.ProjectOptimization(*args, **kwargs)[source]ΒΆ
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    Bases: sparsify.models.base.BaseCreatedModifiedModel

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    DB model for a project’s optimization (stores modifier settings). -A project may have multiple optimizations stored in the DB.

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    -DoesNotExistΒΆ
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    alias of sparsify.models.projects_optimizations.ProjectOptimizationDoesNotExist

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    -created = <DateTimeField: ProjectOptimization.created>ΒΆ
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    -end_epoch = <FloatField: ProjectOptimization.end_epoch>ΒΆ
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    -lr_schedule_modifiersΒΆ
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    -modified = <DateTimeField: ProjectOptimization.modified>ΒΆ
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    -name = <TextField: ProjectOptimization.name>ΒΆ
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    -notes = <TextField: ProjectOptimization.notes>ΒΆ
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    -optim_id = <CharField: ProjectOptimization.optim_id>ΒΆ
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    -profile_loss = <ForeignKeyField: ProjectOptimization.profile_loss>ΒΆ
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    -profile_loss_id = <ForeignKeyField: ProjectOptimization.profile_loss>ΒΆ
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    -profile_perf = <ForeignKeyField: ProjectOptimization.profile_perf>ΒΆ
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    -profile_perf_id = <ForeignKeyField: ProjectOptimization.profile_perf>ΒΆ
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    -project = <ForeignKeyField: ProjectOptimization.project>ΒΆ
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    -project_id = <ForeignKeyField: ProjectOptimization.project>ΒΆ
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    -pruning_modifiersΒΆ
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    -quantization_modifiersΒΆ
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    -start_epoch = <FloatField: ProjectOptimization.start_epoch>ΒΆ
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    -trainable_modifiersΒΆ
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    -class sparsify.models.projects_optimizations.ProjectOptimizationModifierLRSchedule(*args, **kwargs)[source]ΒΆ
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    Bases: sparsify.models.base.BaseCreatedModifiedModel

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    DB model for a project’s learning rate schedule modifier.

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    -DoesNotExistΒΆ
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    alias of sparsify.models.projects_optimizations.ProjectOptimizationModifierLRScheduleDoesNotExist

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    -created = <DateTimeField: ProjectOptimizationModifierLRSchedule.created>ΒΆ
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    -end_epoch = <FloatField: ProjectOptimizationModifierLRSchedule.end_epoch>ΒΆ
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    -final_lr = <FloatField: ProjectOptimizationModifierLRSchedule.final_lr>ΒΆ
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    -init_lr = <FloatField: ProjectOptimizationModifierLRSchedule.init_lr>ΒΆ
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    -lr_mods = <ListObjField: ProjectOptimizationModifierLRSchedule.lr_mods>ΒΆ
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    -modified = <DateTimeField: ProjectOptimizationModifierLRSchedule.modified>ΒΆ
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    -modifier_id = <CharField: ProjectOptimizationModifierLRSchedule.modifier_id>ΒΆ
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    -optim = <ForeignKeyField: ProjectOptimizationModifierLRSchedule.optim>ΒΆ
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    -optim_id = <ForeignKeyField: ProjectOptimizationModifierLRSchedule.optim>ΒΆ
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    -start_epoch = <FloatField: ProjectOptimizationModifierLRSchedule.start_epoch>ΒΆ
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    -class sparsify.models.projects_optimizations.ProjectOptimizationModifierPruning(*args, **kwargs)[source]ΒΆ
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    Bases: sparsify.models.base.BaseCreatedModifiedModel

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    DB model for a project’s optimization pruning modifier.

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    -DoesNotExistΒΆ
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    alias of sparsify.models.projects_optimizations.ProjectOptimizationModifierPruningDoesNotExist

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    -balance_perf_loss = <FloatField: ProjectOptimizationModifierPruning.balance_perf_loss>ΒΆ
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    -compression = <FloatField: ProjectOptimizationModifierPruning.compression>ΒΆ
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    -created = <DateTimeField: ProjectOptimizationModifierPruning.created>ΒΆ
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    -end_epoch = <FloatField: ProjectOptimizationModifierPruning.end_epoch>ΒΆ
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    -est_loss_sensitivity = <FloatField: ProjectOptimizationModifierPruning.est_loss_sensitivity>ΒΆ
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    -est_perf_sensitivity = <FloatField: ProjectOptimizationModifierPruning.est_perf_sensitivity>ΒΆ
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    -est_recovery = <FloatField: ProjectOptimizationModifierPruning.est_recovery>ΒΆ
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    - -
    -
    -est_time = <FloatField: ProjectOptimizationModifierPruning.est_time>ΒΆ
    -
    - -
    -
    -est_time_baseline = <FloatField: ProjectOptimizationModifierPruning.est_time_baseline>ΒΆ
    -
    - -
    -
    -est_time_gain = <FloatField: ProjectOptimizationModifierPruning.est_time_gain>ΒΆ
    -
    - -
    -
    -filter_min_perf_gain = <FloatField: ProjectOptimizationModifierPruning.filter_min_perf_gain>ΒΆ
    -
    - -
    -
    -filter_min_recovery = <FloatField: ProjectOptimizationModifierPruning.filter_min_recovery>ΒΆ
    -
    - -
    -
    -filter_min_sparsity = <FloatField: ProjectOptimizationModifierPruning.filter_min_sparsity>ΒΆ
    -
    - -
    -
    -flops = <FloatField: ProjectOptimizationModifierPruning.flops>ΒΆ
    -
    - -
    -
    -flops_baseline = <FloatField: ProjectOptimizationModifierPruning.flops_baseline>ΒΆ
    -
    - -
    -
    -flops_gain = <FloatField: ProjectOptimizationModifierPruning.flops_gain>ΒΆ
    -
    - -
    -
    -mask_type = <TextField: ProjectOptimizationModifierPruning.mask_type>ΒΆ
    -
    - -
    -
    -modified = <DateTimeField: ProjectOptimizationModifierPruning.modified>ΒΆ
    -
    - -
    -
    -modifier_id = <CharField: ProjectOptimizationModifierPruning.modifier_id>ΒΆ
    -
    - -
    -
    -nodes = <ListObjField: ProjectOptimizationModifierPruning.nodes>ΒΆ
    -
    - -
    -
    -optim = <ForeignKeyField: ProjectOptimizationModifierPruning.optim>ΒΆ
    -
    - -
    -
    -optim_id = <ForeignKeyField: ProjectOptimizationModifierPruning.optim>ΒΆ
    -
    - -
    -
    -params = <FloatField: ProjectOptimizationModifierPruning.params>ΒΆ
    -
    - -
    -
    -params_baseline = <FloatField: ProjectOptimizationModifierPruning.params_baseline>ΒΆ
    -
    - -
    -
    -sparsity = <FloatField: ProjectOptimizationModifierPruning.sparsity>ΒΆ
    -
    - -
    -
    -start_epoch = <FloatField: ProjectOptimizationModifierPruning.start_epoch>ΒΆ
    -
    - -
    -
    -update_frequency = <FloatField: ProjectOptimizationModifierPruning.update_frequency>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.models.projects_optimizations.ProjectOptimizationModifierQuantization(*args, **kwargs)[source]ΒΆ
    -

    Bases: sparsify.models.base.BaseCreatedModifiedModel

    -

    DB model for a project’s optimization quantization modifier.

    -
    -
    -DoesNotExistΒΆ
    -

    alias of sparsify.models.projects_optimizations.ProjectOptimizationModifierQuantizationDoesNotExist

    -
    - -
    -
    -balance_perf_loss = <FloatField: ProjectOptimizationModifierQuantization.balance_perf_loss>ΒΆ
    -
    - -
    -
    -compression = <FloatField: ProjectOptimizationModifierQuantization.compression>ΒΆ
    -
    - -
    -
    -created = <DateTimeField: ProjectOptimizationModifierQuantization.created>ΒΆ
    -
    - -
    -
    -end_epoch = <FloatField: ProjectOptimizationModifierQuantization.end_epoch>ΒΆ
    -
    - -
    -
    -est_loss_sensitivity = <FloatField: ProjectOptimizationModifierQuantization.est_loss_sensitivity>ΒΆ
    -
    - -
    -
    -est_perf_sensitivity = <FloatField: ProjectOptimizationModifierQuantization.est_perf_sensitivity>ΒΆ
    -
    - -
    -
    -est_recovery = <FloatField: ProjectOptimizationModifierQuantization.est_recovery>ΒΆ
    -
    - -
    -
    -est_time = <FloatField: ProjectOptimizationModifierQuantization.est_time>ΒΆ
    -
    - -
    -
    -est_time_baseline = <FloatField: ProjectOptimizationModifierQuantization.est_time_baseline>ΒΆ
    -
    - -
    -
    -est_time_gain = <FloatField: ProjectOptimizationModifierQuantization.est_time_gain>ΒΆ
    -
    - -
    -
    -filter_min_perf_gain = <FloatField: ProjectOptimizationModifierQuantization.filter_min_perf_gain>ΒΆ
    -
    - -
    -
    -filter_min_recovery = <FloatField: ProjectOptimizationModifierQuantization.filter_min_recovery>ΒΆ
    -
    - -
    -
    -flops = <FloatField: ProjectOptimizationModifierQuantization.flops>ΒΆ
    -
    - -
    -
    -flops_baseline = <FloatField: ProjectOptimizationModifierQuantization.flops_baseline>ΒΆ
    -
    - -
    -
    -flops_gain = <FloatField: ProjectOptimizationModifierQuantization.flops_gain>ΒΆ
    -
    - -
    -
    -level = <TextField: ProjectOptimizationModifierQuantization.level>ΒΆ
    -
    - -
    -
    -modified = <DateTimeField: ProjectOptimizationModifierQuantization.modified>ΒΆ
    -
    - -
    -
    -modifier_id = <CharField: ProjectOptimizationModifierQuantization.modifier_id>ΒΆ
    -
    - -
    -
    -nodes = <ListObjField: ProjectOptimizationModifierQuantization.nodes>ΒΆ
    -
    - -
    -
    -optim = <ForeignKeyField: ProjectOptimizationModifierQuantization.optim>ΒΆ
    -
    - -
    -
    -optim_id = <ForeignKeyField: ProjectOptimizationModifierQuantization.optim>ΒΆ
    -
    - -
    -
    -params = <FloatField: ProjectOptimizationModifierQuantization.params>ΒΆ
    -
    - -
    -
    -params_baseline = <FloatField: ProjectOptimizationModifierQuantization.params_baseline>ΒΆ
    -
    - -
    -
    -start_epoch = <FloatField: ProjectOptimizationModifierQuantization.start_epoch>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.models.projects_optimizations.ProjectOptimizationModifierTrainable(*args, **kwargs)[source]ΒΆ
    -

    Bases: sparsify.models.base.BaseCreatedModifiedModel

    -

    DB model for a project’s optimization trainable modifier.

    -
    -
    -DoesNotExistΒΆ
    -

    alias of sparsify.models.projects_optimizations.ProjectOptimizationModifierTrainableDoesNotExist

    -
    - -
    -
    -created = <DateTimeField: ProjectOptimizationModifierTrainable.created>ΒΆ
    -
    - -
    -
    -end_epoch = <FloatField: ProjectOptimizationModifierTrainable.end_epoch>ΒΆ
    -
    - -
    -
    -modified = <DateTimeField: ProjectOptimizationModifierTrainable.modified>ΒΆ
    -
    - -
    -
    -modifier_id = <CharField: ProjectOptimizationModifierTrainable.modifier_id>ΒΆ
    -
    - -
    -
    -nodes = <ListObjField: ProjectOptimizationModifierTrainable.nodes>ΒΆ
    -
    - -
    -
    -optim = <ForeignKeyField: ProjectOptimizationModifierTrainable.optim>ΒΆ
    -
    - -
    -
    -optim_id = <ForeignKeyField: ProjectOptimizationModifierTrainable.optim>ΒΆ
    -
    - -
    -
    -start_epoch = <FloatField: ProjectOptimizationModifierTrainable.start_epoch>ΒΆ
    -
    - -
    - +
    +

    sparsify.models.projects_optimizations moduleΒΆ

    -
    -

    sparsify.models.projects_profiles moduleΒΆ

    -

    DB model classes for project’s profiles such as performance and loss

    -
    -
    -class sparsify.models.projects_profiles.BaseProjectProfile(*args, **kwargs)[source]ΒΆ
    -

    Bases: sparsify.models.base.BaseModel

    -

    Base DB model for project’s profiles such as loss and perf

    -
    -
    -DoesNotExistΒΆ
    -

    alias of sparsify.models.projects_profiles.BaseProjectProfileDoesNotExist

    -
    - -
    -
    -analysis = <JSONField: BaseProjectProfile.analysis>ΒΆ
    -
    - -
    -
    -created = <DateTimeField: BaseProjectProfile.created>ΒΆ
    -
    - -
    -
    -job = <ForeignKeyField: BaseProjectProfile.job>ΒΆ
    -
    - -
    -
    -job_id = <ForeignKeyField: BaseProjectProfile.job>ΒΆ
    -
    - -
    -
    -name = <TextField: BaseProjectProfile.name>ΒΆ
    -
    - -
    -
    -profile_id = <CharField: BaseProjectProfile.profile_id>ΒΆ
    -
    - -
    -
    -source = <TextField: BaseProjectProfile.source>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.models.projects_profiles.ProjectLossProfile(*args, **kwargs)[source]ΒΆ
    -

    Bases: sparsify.models.projects_profiles.BaseProjectProfile

    -

    DB model for a project’s loss profile. -A project may have multiple loss profiles stored in the DB.

    -
    -
    -DoesNotExistΒΆ
    -

    alias of sparsify.models.projects_profiles.ProjectLossProfileDoesNotExist

    -
    - -
    -
    -analysis = <JSONField: ProjectLossProfile.analysis>ΒΆ
    -
    - -
    -
    -created = <DateTimeField: ProjectLossProfile.created>ΒΆ
    -
    - -
    -
    -job = <ForeignKeyField: ProjectLossProfile.job>ΒΆ
    -
    - -
    -
    -job_id = <ForeignKeyField: ProjectLossProfile.job>ΒΆ
    -
    - -
    -
    -name = <TextField: ProjectLossProfile.name>ΒΆ
    -
    - -
    -
    -profile_id = <CharField: ProjectLossProfile.profile_id>ΒΆ
    -
    - -
    -
    -project = <ForeignKeyField: ProjectLossProfile.project>ΒΆ
    -
    - -
    -
    -project_id = <ForeignKeyField: ProjectLossProfile.project>ΒΆ
    -
    - -
    -
    -projectoptimization_setΒΆ
    -
    - -
    -
    -pruning_estimation_type = <TextField: ProjectLossProfile.pruning_estimation_type>ΒΆ
    -
    - -
    -
    -pruning_estimations = <BooleanField: ProjectLossProfile.pruning_estimations>ΒΆ
    -
    - -
    -
    -pruning_structure = <TextField: ProjectLossProfile.pruning_structure>ΒΆ
    -
    - -
    -
    -quantized_estimation_type = <TextField: ProjectLossProfile.quantized_estimation_type>ΒΆ
    -
    - -
    -
    -quantized_estimations = <BooleanField: ProjectLossProfile.quantized_estimations>ΒΆ
    -
    - -
    -
    -source = <TextField: ProjectLossProfile.source>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.models.projects_profiles.ProjectPerfProfile(*args, **kwargs)[source]ΒΆ
    -

    Bases: sparsify.models.projects_profiles.BaseProjectProfile

    -

    DB model for a project’s performance profile. -A project may have multiple perf profiles stored in the DB

    -
    -
    -DoesNotExistΒΆ
    -

    alias of sparsify.models.projects_profiles.ProjectPerfProfileDoesNotExist

    -
    - -
    -
    -analysis = <JSONField: ProjectPerfProfile.analysis>ΒΆ
    -
    - -
    -
    -batch_size = <IntegerField: ProjectPerfProfile.batch_size>ΒΆ
    -
    - -
    -
    -core_count = <IntegerField: ProjectPerfProfile.core_count>ΒΆ
    -
    - -
    -
    -created = <DateTimeField: ProjectPerfProfile.created>ΒΆ
    -
    - -
    -
    -instruction_sets = <CSVField: ProjectPerfProfile.instruction_sets>ΒΆ
    -
    - -
    -
    -iterations_per_check = <IntegerField: ProjectPerfProfile.iterations_per_check>ΒΆ
    -
    - -
    -
    -job = <ForeignKeyField: ProjectPerfProfile.job>ΒΆ
    -
    - -
    -
    -job_id = <ForeignKeyField: ProjectPerfProfile.job>ΒΆ
    -
    - -
    -
    -name = <TextField: ProjectPerfProfile.name>ΒΆ
    -
    - -
    -
    -profile_id = <CharField: ProjectPerfProfile.profile_id>ΒΆ
    -
    - -
    -
    -project = <ForeignKeyField: ProjectPerfProfile.project>ΒΆ
    -
    - -
    -
    -project_id = <ForeignKeyField: ProjectPerfProfile.project>ΒΆ
    -
    - -
    -
    -projectoptimization_setΒΆ
    -
    - -
    -
    -pruning_estimations = <BooleanField: ProjectPerfProfile.pruning_estimations>ΒΆ
    -
    - -
    -
    -quantized_estimations = <BooleanField: ProjectPerfProfile.quantized_estimations>ΒΆ
    -
    - -
    -
    -source = <TextField: ProjectPerfProfile.source>ΒΆ
    -
    - -
    -
    -warmup_iterations_per_check = <IntegerField: ProjectPerfProfile.warmup_iterations_per_check>ΒΆ
    -
    - -
    - +
    +

    sparsify.models.projects_profiles moduleΒΆ

    -
    -

    sparsify.models.utils moduleΒΆ

    -
    -
    -sparsify.models.utils.database_setup(working_dir: str, app: Optional[flask.app.Flask] = None)[source]ΒΆ
    -
    - +
    +

    sparsify.models.utils moduleΒΆ

    -
    -

    Module contentsΒΆ

    -

    DB models and objects for working with sparsify server

    +
    +

    Module contentsΒΆ

    diff --git a/sparsify/api/sparsify.schemas.html b/sparsify/api/sparsify.schemas.html index 37dc61415be..d9130fdd756 100644 --- a/sparsify/api/sparsify.schemas.html +++ b/sparsify/api/sparsify.schemas.html @@ -110,18 +110,18 @@
  • sparsify.models package
  • sparsify.schemas package
  • sparsify.utils package
    • @@ -129,9 +129,9 @@
  • Submodules
    • -
  • sparsify.app module
    • -
  • sparsify.log module
    • -
  • Module contents
    • +
  • sparsify.app module
    • +
  • sparsify.log module
    • +
  • Module contents
    • @@ -214,1335 +214,41 @@

    sparsify.schemas package

    SubmodulesΒΆ

    -
    -

    sparsify.schemas.errors moduleΒΆ

    -

    Schemas for anything related to errors occurring in the flask app

    -
    -
    -class sparsify.schemas.errors.ErrorSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Error schema to return in the event of an error encountered while running the app

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - +
    +

    sparsify.schemas.errors moduleΒΆ

    -
    -

    sparsify.schemas.helpers moduleΒΆ

    -

    Helper values and classes for marshmallow schemas

    -
    -
    -class sparsify.schemas.helpers.EnumField(enum_class: Any, *args, **kwargs)[source]ΒΆ
    -

    Bases: marshmallow.fields.String

    -

    Custom schema field for handling serializing and deserializing enums

    -
    -
    Parameters
    -
      -

    • enum_class – the enum class to use for deserializing

      • -

    • args – args to pass to the field

      • -

    • kwargs – the kwargs to pass to the field

      • -
    -
    -
    -
    -
    -deserialize(value: Any, attr: Optional[str] = None, data: Optional[Mapping[str, Any]] = None, **kwargs)[source]ΒΆ
    -

    Deserialize value.

    -
    -
    Parameters
    -
      -

    • value – The value to deserialize.

      • -

    • attr – The attribute/key in data to deserialize.

      • -

    • data – The raw input data passed to Schema.load.

      • -

    • kwargs – Field-specific keyword arguments.

      • -
    -
    -
    Raises
    -

    ValidationError – If an invalid value is passed or if a required value -is missing.

    -
    -
    -
    - -
    - -
    -
    -sparsify.schemas.helpers.data_dump_and_validation(schema: marshmallow.schema.Schema, data: Any) → Dict[source]ΒΆ
    -

    Use a marshmallow schema to dump and validate input data

    -
    -
    Parameters
    -
      -

    • schema – the schema to use to dump an object and validate it

      • -

    • data – the data to dump and validate

      • -
    -
    -
    Returns
    -

    the resulting dumped data from marshmallow

    -
    -
    -
    - +
    +

    sparsify.schemas.helpers moduleΒΆ

    -
    -

    sparsify.schemas.jobs moduleΒΆ

    -

    Schemas for anything related to job routes, database models, and workers

    -
    -
    -class sparsify.schemas.jobs.JobProgressSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for the progress of a Job object, used in the workers to report progress

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.jobs.JobSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for a job object as stored in the DB and returned in the server routes

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.jobs.ResponseJobSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for returning a response with a single job

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.jobs.ResponseJobsSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for returning a response with multiple jobs

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.jobs.SearchJobsSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Expected schema to use for querying jobs

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - +
    +

    sparsify.schemas.jobs moduleΒΆ

    -
    -

    sparsify.schemas.model_repo moduleΒΆ

    -

    Schemas for anything related to model repo routes, database models, and

    -
    -
    -class sparsify.schemas.model_repo.ModelRepoArchitectureSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for a model repo architecture

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.model_repo.ModelRepoDatasetSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for a model repo dataset

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.model_repo.ModelRepoDomainSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for a model repo domain

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.model_repo.ModelRepoModelDescSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for a model repo desc

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.model_repo.ModelRepoModelMetricSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for reporting a metric for a model repo model

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.model_repo.ModelRepoModelPerfSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for reporting the performance for a model repo model

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.model_repo.ModelRepoModelSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for a model repo model

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.model_repo.ResponseModelRepoModels(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for the response for searching for models in the model repo

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.model_repo.SearchModelRepoModels(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for searching and filtering models in the model repo

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - +
    +

    sparsify.schemas.model_repo moduleΒΆ

    -
    -

    sparsify.schemas.projects moduleΒΆ

    -

    Schemas for anything related to project routes, database models, and workers

    -
    -
    -class sparsify.schemas.projects.CreateUpdateProjectSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Expected schema to use for creating or updating a project

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects.DeleteProjectSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Expected schema to use for deleting a project

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects.ProjectExtSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: sparsify.schemas.projects.ProjectSchema

    -

    Schema for a project object including model and data -as stored in the DB and returned in the server routes

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects.ProjectSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for a project object as stored in the DB and returned in the server routes

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects.ResponseProjectDeletedSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for returning a response after deleting a project

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects.ResponseProjectExtSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for returning a response with a single project and its -associated model and data

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects.ResponseProjectSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for returning a response with a single project

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects.ResponseProjectsSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for returning a response with multiple project

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects.SearchProjectsSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Expected schema to use for querying projects

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - +
    +

    sparsify.schemas.projects moduleΒΆ

    -
    -

    sparsify.schemas.projects_benchmarks moduleΒΆ

    -

    Schemas for anything related to project benchmark routes, database models, and workers

    -
    -
    -class sparsify.schemas.projects_benchmarks.CreateProjectBenchmarkSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Expected schema to use for creating a project benchmark

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_benchmarks.ProjectBenchmarkResultSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for a project benchmark object’s metadata as stored in the DB

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_benchmarks.ProjectBenchmarkResultsSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for a project benchmark object’s measured results as stored in the DB

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_benchmarks.ProjectBenchmarkSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for a project benchmark object (metadata and result) as stored in the DB and -returned in the server routes

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_benchmarks.ResponseProjectBenchmarkDeletedSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Expected schema to use for deleting a project benchmark

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_benchmarks.ResponseProjectBenchmarkSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for returning a response containing a benchmark project

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_benchmarks.ResponseProjectBenchmarksSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for returning a response containing multiple benchmark projects

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_benchmarks.SearchProjectBenchmarksSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema to use for querying project benchmarks

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - +
    +

    sparsify.schemas.projects_benchmarks moduleΒΆ

    -
    -

    sparsify.schemas.projects_data moduleΒΆ

    -

    Schemas for anything related to project data routes, database models, and workers

    -
    -
    -class sparsify.schemas.projects_data.CreateUpdateProjectDataSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for creating a data file for a project

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_data.ProjectDataSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for a project data object as stored in the DB and -returned in the server routes

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_data.ResponseProjectDataDeletedSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for returning a response after deleting a project’s data object and file

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_data.ResponseProjectDataSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for returning a response with all of the project’s data objects

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_data.ResponseProjectDataSingleSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for returning a response with a project’s data object

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_data.SearchProjectDataSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema to use for querying project data

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_data.SetProjectDataFromSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Expected schema to use for setting a project’s data for -upload from path or upload from url

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - +
    +

    sparsify.schemas.projects_data moduleΒΆ

    -
    -

    sparsify.schemas.projects_model moduleΒΆ

    -

    Schemas for anything related to project model routes and database

    -
    -
    -class sparsify.schemas.projects_model.CreateUpdateProjectModelSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for creating a model for a project

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_model.DeleteProjectModelSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for deleting a project’s model

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_model.ProjectModelAnalysisSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for the analysis of a project’s model and all the nodes contained

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_model.ProjectModelSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for a project model object as stored in the DB an returned in server routes

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_model.ResponseProjectModelAnalysisSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for returning a response with a project model’s analysis

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_model.ResponseProjectModelDeletedSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for returning a response on deletion of a project’s model

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_model.ResponseProjectModelSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for returning a response with a single project model

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_model.SetProjectModelFromSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for setting a project’s model from some loadable uri

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - +
    +

    sparsify.schemas.projects_model moduleΒΆ

    -
    -

    sparsify.schemas.projects_optimizations moduleΒΆ

    -

    Schemas for anything related to project optims routes, database models, and workers

    -
    -
    -class sparsify.schemas.projects_optimizations.CreateProjectOptimizationSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: sparsify.schemas.projects_optimizations.GetProjectOptimizationBestEstimatedResultsSchema

    -

    Schema to use for creating a project optimization

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_optimizations.CreateUpdateProjectOptimizationModifiersLRScheduleSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema to use for creating or updating a project optimization lr schedule modifier

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_optimizations.CreateUpdateProjectOptimizationModifiersPruningSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema to use for creating or updating a project optimization pruning modifier

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_optimizations.CreateUpdateProjectOptimizationModifiersQuantizationSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema to use for creating or updating a project optimization quantization modifier

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_optimizations.CreateUpdateProjectOptimizationModifiersTrainableSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema to use for creating or updating a project optimization trainable modifier

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_optimizations.GetProjectOptimizationBestEstimatedResultsSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema to use for getting a projects best estimated optimization results

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_optimizations.ProjectAvailableModelModificationsSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for the available modifiers for a project

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_optimizations.ProjectOptimizationModifierLRExponentialArgsSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for the args for an exponential LR modifier

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_optimizations.ProjectOptimizationModifierLRMultiStepArgsSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for the args for a multi step LR modifier

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_optimizations.ProjectOptimizationModifierLRScheduleSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for an LR schedule modifier including metadata and settings

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_optimizations.ProjectOptimizationModifierLRSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for an LR modifier

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_optimizations.ProjectOptimizationModifierLRSetArgsSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for the args for a set LR modifier

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_optimizations.ProjectOptimizationModifierLRStepArgsSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for the args for a step LR modifier

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_optimizations.ProjectOptimizationModifierPruningNodeSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: sparsify.schemas.projects_optimizations.ProjectOptimizationModifierPruningNodeMetadataSchema, sparsify.schemas.projects_optimizations.ProjectOptimizationModifierEstimationsSchema

    -

    Schema for a pruning node containing metadata and estimated values

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_optimizations.ProjectOptimizationModifierPruningSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: sparsify.schemas.projects_optimizations.ProjectOptimizationModifierEstimationsSchema

    -

    Schema for a pruning modifier including metadata, settings, and estimated values

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_optimizations.ProjectOptimizationModifierQuantizationNodeSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for a quantization node containing metadata

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_optimizations.ProjectOptimizationModifierQuantizationSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for a quantization modifier including metadata, settings, -and estimated values

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_optimizations.ProjectOptimizationModifierTrainableNodeSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for a trainable node containing metadata

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_optimizations.ProjectOptimizationModifierTrainableSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for a trainable modifier containing metadata and settings

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_optimizations.ProjectOptimizationSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for a project optimization containing metadata and modifiers

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_optimizations.ResponseProjectOptimizationDeletedSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for returning the results of deleting a project optimization

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_optimizations.ResponseProjectOptimizationFrameworksAvailableSamplesSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for returning the available code samples for a framework -for project optimization

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_optimizations.ResponseProjectOptimizationFrameworksAvailableSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for returning the available frameworks for project optimization

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_optimizations.ResponseProjectOptimizationModifierDeletedSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for returning the results of deleting a project optimization modifier

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_optimizations.ResponseProjectOptimizationModifiersAvailable(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for returning the available modifiers for project optimization

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_optimizations.ResponseProjectOptimizationModifiersBestEstimated(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: sparsify.schemas.projects_optimizations.ProjectOptimizationModifierEstimationsSchema

    -

    Schema for returning the best estimated results for project optimization

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_optimizations.ResponseProjectOptimizationSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for returning a project optimization

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_optimizations.ResponseProjectOptimizationsSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for returning multiple project optimizations

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_optimizations.SearchProjectOptimizationsSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema to use for querying project optimizations

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_optimizations.UpdateProjectOptimizationSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema to use for updating a project optimization

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - +
    +

    sparsify.schemas.projects_optimizations moduleΒΆ

    -
    -

    sparsify.schemas.projects_profiles moduleΒΆ

    -

    Schemas for anything related to project profile routes, database models, and workers

    -
    -
    -class sparsify.schemas.projects_profiles.CreateProjectLossProfileSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Expected schema to use for creating a loss profile for a project

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_profiles.CreateProjectPerfProfileSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Expected schema to use for creating a performance profile for a project

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_profiles.ProjectLossProfileSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: sparsify.schemas.projects_profiles.ProjectProfileSchema

    -

    Schema for a projects loss profile object as stored in the DB -and returned in the server routes

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_profiles.ProjectPerfProfileSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: sparsify.schemas.projects_profiles.ProjectProfileSchema

    -

    Schema for a projects performance profile object as stored in the DB -and returned in the server routes

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_profiles.ProjectProfileAnalysisSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for an analysis for a profiles model and all ops in it. -Includes baseline measurements, pruning measurements, and quantization measurements

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_profiles.ProjectProfileMeasurementSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for a profile measurement

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_profiles.ProjectProfileMeasurementsSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for profile measurements including baseline

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_profiles.ProjectProfileModelOpsBaselineMeasurementsSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for baseline measurements for a profiles model and all ops in it

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_profiles.ProjectProfileModelOpsMeasurementsSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for measurements for a profiles model and all ops in it

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_profiles.ProjectProfileOpBaselineMeasurementSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: sparsify.schemas.projects_profiles.ProjectProfileMeasurementSchema, sparsify.schemas.projects_profiles.ProjectProfileOpSchema

    -

    Schema for baseline measurements for a profiles op or node in a model

    -
    -
    -dump_fields: typing.Dict[str, ma_fields.Field]ΒΆ
    -
    - -
    -
    -fields: typing.Dict[str, ma_fields.Field]ΒΆ
    -

    Dictionary mapping field_names -> Field objects

    -
    - -
    -
    -load_fields: typing.Dict[str, ma_fields.Field]ΒΆ
    -
    - -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_profiles.ProjectProfileOpMeasurementsSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: sparsify.schemas.projects_profiles.ProjectProfileMeasurementsSchema, sparsify.schemas.projects_profiles.ProjectProfileOpSchema

    -

    Schema for measurements for a profile op or node in a model

    -
    -
    -dump_fields: typing.Dict[str, ma_fields.Field]ΒΆ
    -
    - -
    -
    -fields: typing.Dict[str, ma_fields.Field]ΒΆ
    -

    Dictionary mapping field_names -> Field objects

    -
    - -
    -
    -load_fields: typing.Dict[str, ma_fields.Field]ΒΆ
    -
    - -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_profiles.ProjectProfileOpSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for a profile op or node in a model

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_profiles.ProjectProfileSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Base schema for a projects profile such as loss or perf

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_profiles.ResponseProjectLossProfileSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for returning a response with a single loss profile

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_profiles.ResponseProjectLossProfilesSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for returning a response with multiple loss profiles

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_profiles.ResponseProjectPerfProfileSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for returning a response with a single performance profile

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_profiles.ResponseProjectPerfProfilesSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for returning a response with a multiple performance profiles

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_profiles.ResponseProjectProfileDeletedSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for returning a response after deleting a profile

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.projects_profiles.SearchProjectProfilesSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Expected schema to use for querying project profiles

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - +
    +

    sparsify.schemas.projects_profiles moduleΒΆ

    -
    -

    sparsify.schemas.system moduleΒΆ

    -

    Schemas for anything related to system routes

    -
    -
    -class sparsify.schemas.system.ResponseSystemInfo(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for returning a response with the system info

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.system.SystemInfo(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -

    Schema for the system info the server is currently running on

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - -
    -
    -class sparsify.schemas.system.VersionInfoSchema(*, only: Optional[Union[Sequence[str], Set[str]]] = None, exclude: Union[Sequence[str], Set[str]] = (), many: bool = False, context: Optional[Dict] = None, load_only: Union[Sequence[str], Set[str]] = (), dump_only: Union[Sequence[str], Set[str]] = (), partial: Union[bool, Sequence[str], Set[str]] = False, unknown: Optional[str] = None)[source]ΒΆ
    -

    Bases: marshmallow.schema.Schema

    -
    -
    -opts: SchemaOpts = <marshmallow.schema.SchemaOpts object>ΒΆ
    -
    - -
    - +
    +

    sparsify.schemas.system moduleΒΆ

    -
    -

    Module contentsΒΆ

    -

    Schemas for working with the sparsify server

    +
    +

    Module contentsΒΆ

    diff --git a/sparsify/api/sparsify.utils.html b/sparsify/api/sparsify.utils.html index d686d2f64f9..373def83396 100644 --- a/sparsify/api/sparsify.utils.html +++ b/sparsify/api/sparsify.utils.html @@ -111,17 +111,17 @@
  • sparsify.schemas package
  • sparsify.utils package
  • sparsify.workers package
  • Submodules
    • -
  • sparsify.app module
    • -
  • sparsify.log module
    • -
  • Module contents
    • +
  • sparsify.app module
    • +
  • sparsify.log module
    • +
  • Module contents
    • @@ -204,46 +204,11 @@

    sparsify.utils package

    SubmodulesΒΆ

    -
    -

    sparsify.utils.system moduleΒΆ

    -

    Utilities for ONNX based ML system info and validation

    -
    -
    -sparsify.utils.system.available_ml_engines() → List[str][source]ΒΆ
    -
    -
    Returns
    -

    List of available inference providers on current system. Potential values -include [β€˜deepsparse’, β€˜ort_cpu’, β€˜ort_gpu’]

    -
    -
    -
    - -
    -
    -sparsify.utils.system.get_ml_sys_info() → Dict[str, Any][source]ΒΆ
    -
    -
    Returns
    -

    a dictionary containing info for the system and ML engines on the system. -Such as number of cores, instruction sets, available engines, etc

    -
    -
    -
    - -
    -
    -sparsify.utils.system.ml_engines_errors() → Dict[str, Exception][source]ΒΆ
    -
    -
    Returns
    -

    a dictionary containing any errors encountered when importing ML engines -on the current system

    -
    -
    -
    - +
    +

    sparsify.utils.system moduleΒΆ

    -
    -

    Module contentsΒΆ

    -

    Utility functions for sparsify

    +
    +

    Module contentsΒΆ

    diff --git a/sparsify/api/sparsify.workers.html b/sparsify/api/sparsify.workers.html index 0a10490f4c6..30a2056dff2 100644 --- a/sparsify/api/sparsify.workers.html +++ b/sparsify/api/sparsify.workers.html @@ -111,21 +111,21 @@
  • sparsify.utils package
  • sparsify.workers package
  • Submodules
    • -
  • sparsify.app module
    • -
  • sparsify.log module
    • -
  • Module contents
    • +
  • sparsify.app module
    • +
  • sparsify.log module
    • +
  • Module contents
    • @@ -208,740 +208,26 @@

    sparsify.workers package

    SubmodulesΒΆ

    -
    -

    sparsify.workers.base moduleΒΆ

    -

    Code related to the base implementations for job workers

    -
    -
    -class sparsify.workers.base.JobWorker(job_id: str, project_id: str)[source]ΒΆ
    -

    Bases: object

    -

    The base job worker instance all job workers must extend

    -
    -
    Parameters
    -
      -

    • job_id – the id of the job the worker is being run for

      • -

    • project_id – the id of the project the job belongs to

      • -
    -
    -
    -
    -
    -abstract classmethod format_args(**kwargs) → Dict[str, Any][source]ΒΆ
    -

    Format a given args into proper args to be stored for later use -in the constructor for the job worker.

    -
    -
    Parameters
    -

    kwargs – the args to format

    -
    -
    Returns
    -

    the formatted args to be stored for later use

    -
    -
    -
    - -
    -
    -classmethod get_type() → str[source]ΒΆ
    -
    -
    Returns
    -

    the type of job worker

    -
    -
    -
    - -
    -
    -property job_idΒΆ
    -

    the id of the job the worker is being run for

    -
    -
    Type
    -

    return

    -
    -
    -
    - -
    -
    -property project_idΒΆ
    -

    the id of the project the job belongs to

    -
    -
    Type
    -

    return

    -
    -
    -
    - -
    -
    -abstract run() → Iterator[Dict[str, Any]][source]ΒΆ
    -

    Perform the work for the job. -Must be implemented as an iterator that returns a -dictionary containing the progress object on each progress step.

    -
    -
    Returns
    -

    an iterator containing progress update information

    -
    -
    -
    - -
    - -
    -
    -class sparsify.workers.base.JobWorkerRegistry(name, bases, attrs)[source]ΒΆ
    -

    Bases: type

    -

    Registry class for handling and storing BaseJobWorker sub class instances. -All subclasses are added to the the REGISTRY property

    -
    -
    -REGISTRY = {'BaseProfileJobWorker': <class 'sparsify.workers.projects_profiles.BaseProfileJobWorker'>, 'CreateBenchmarkJobWorker': <class 'sparsify.workers.projects_benchmark.CreateBenchmarkJobWorker'>, 'CreateLossProfileJobWorker': <class 'sparsify.workers.projects_profiles.CreateLossProfileJobWorker'>, 'CreatePerfProfileJobWorker': <class 'sparsify.workers.projects_profiles.CreatePerfProfileJobWorker'>, 'DataFromPathJobWorker': <class 'sparsify.workers.projects_data.DataFromPathJobWorker'>, 'DataFromRepoJobWorker': <class 'sparsify.workers.projects_data.DataFromRepoJobWorker'>, 'JobWorker': <class 'sparsify.workers.base.JobWorker'>, 'ModelFromPathJobWorker': <class 'sparsify.workers.projects_model.ModelFromPathJobWorker'>, 'ModelFromRepoJobWorker': <class 'sparsify.workers.projects_model.ModelFromRepoJobWorker'>, '_DataLoaderJobWorker': <class 'sparsify.workers.projects_data._DataLoaderJobWorker'>, '_ModelLoaderJobWorker': <class 'sparsify.workers.projects_model._ModelLoaderJobWorker'>}ΒΆ
    -
    - -
    -
    -static create_worker(job)[source]ΒΆ
    -
    - -
    - +
    +

    sparsify.workers.base moduleΒΆ

    -
    -

    sparsify.workers.manager moduleΒΆ

    -

    Code related to managing jobs in the server

    -
    -
    -exception sparsify.workers.manager.JobCancelationFailureError(*args: object)[source]ΒΆ
    -

    Bases: Exception

    -

    Error raised if a job could not be canceled

    -
    - -
    -
    -exception sparsify.workers.manager.JobNotFoundError(*args: object)[source]ΒΆ
    -

    Bases: Exception

    -

    Error raised if a job is not found in the database

    -
    - -
    -
    -class sparsify.workers.manager.JobWorkerManager(*args, **kwargs)[source]ΒΆ
    -

    Bases: object

    -

    Manager class for handling running job workers in the background. -Only one job worker can run at once. -Once one completes, the next oldest one marked as pending in the db is launched.

    -
    -
    Parameters
    -

    max_workers – The maximum number of workers to allow the ThreadPoolExecutor -to work with in parallel

    -
    -
    -
    -
    -cancel_job(job_id: str)[source]ΒΆ
    -

    Cancel a job with the given job_id so it won’t be run.

    -
    -
    Parameters
    -

    job_id – the job_id to cancel

    -
    -
    Raises
    -
    -
    -
    -
    - -
    -
    -refresh()[source]ΒΆ
    -

    Refresh the available jobs and put any pending ones since last refresh -onto the ThreadPoolExecutor.

    -

    Otherwise will exit out without doing anything and -subsequent jobs will be launched after the current one completes.

    -
    - -
    -
    -shutdown()[source]ΒΆ
    -

    Shutdown the JobWorkerManager to stop processing any background jobs

    -
    - -
    -
    -start()[source]ΒΆ
    -

    Start the JobWorkerManager to begin processing any background jobs present

    -
    - -
    - +
    +

    sparsify.workers.manager moduleΒΆ

    -
    -

    sparsify.workers.projects_benchmark moduleΒΆ

    -

    Code related to the benchmark implementations for job workers

    -
    -
    -class sparsify.workers.projects_benchmark.CreateBenchmarkJobWorker(job_id: str, project_id: str, model_id: str, benchmark_id: str, core_counts: List[int], batch_sizes: List[int], instruction_sets: List[str], inference_models: List[Dict[str, Optional[str]]], warmup_iterations_per_check: int, iterations_per_check: int)[source]ΒΆ
    -

    Bases: sparsify.workers.base.JobWorker

    -

    A job worker for running and saving a benchmark for a given project -and configuration.

    -
    -
    Parameters
    -
      -

    • job_id – the id of the job this worker is running under

      • -

    • project_id – the id of the project the worker is running for

      • -

    • model_id – id of the model to run the loss profile for

      • -

    • benchmark_id – the benchmark id that should be updated

      • -

    • core_counts – list of core count to run on for benchmarking. --1 will use the maximum cores available

      • -

    • batch_sizes – list of batch sizes to use for benchmarking

      • -

    • instruction_sets – list of instruction sets

      • -

    • inference_models – list of inference model to use for comparison with -fields inference_engine and inference_model_optimization

      • -

    • warmup_iterations_per_check – the number of warmup iterations to run for -before checking performance / timing

      • -

    • iterations_per_check – the number of iterations to run for each performance -check / timing

      • -
    -
    -
    Returns
    -

    the formatted args to be stored for later use

    -
    -
    -
    -
    -property batch_sizesΒΆ
    -

    list of batch sizes to use for benchmarking

    -
    -
    Type
    -

    return

    -
    -
    -
    - -
    -
    -property benchmark_idΒΆ
    -

    id of the benchmark

    -
    -
    Type
    -

    return

    -
    -
    -
    - -
    -
    -property core_countsΒΆ
    -

    list of core count to run on for benchmarking. --1 will use the maximum cores available

    -
    -
    Type
    -

    return

    -
    -
    -
    - -
    -
    -classmethod format_args(model_id: str, benchmark_id: str, core_counts: List[int], batch_sizes: List[int], instruction_sets: List[str], inference_models: List[Dict[str, Optional[str]]], warmup_iterations_per_check: int, iterations_per_check: int)[source]ΒΆ
    -

    Format a given args into proper args to be stored for later use -in the constructor for the job worker.

    -
    -
    Parameters
    -
      -

    • model_id – id of the model to run the loss profile for

      • -

    • benchmark_id – the benchmark id that should be updated

      • -

    • core_counts – list of core count to run on for benchmarking. --1 will use the maximum cores available

      • -

    • batch_sizes – list of batch sizes to use for benchmarking

      • -

    • instruction_sets – list of instruction sets

      • -

    • inference_models – list of inference model to use for comparison with -fields inference_engine and inference_model_optimization

      • -

    • warmup_iterations_per_check – the number of warmup iterations to run -for before checking performance / timing

      • -

    • iterations_per_check – the number of iterations to run for each -performance check / timing

      • -
    -
    -
    Returns
    -

    the formatted args to be stored for later use

    -
    -
    -
    - -
    -
    -property inference_modelsΒΆ
    -

    list of inference model to use for comparison with -fields inference_engine and inference_model_optimization

    -
    -
    Type
    -

    return

    -
    -
    -
    - -
    -
    -property instruction_setsΒΆ
    -

    list of instruction sets

    -
    -
    Type
    -

    return

    -
    -
    -
    - -
    -
    -property iterations_per_checkΒΆ
    -

    the number of iterations to run for each performance check / timing

    -
    -
    Type
    -

    return

    -
    -
    -
    - -
    -
    -property model_idΒΆ
    -

    id of the model to run the loss profile for

    -
    -
    Type
    -

    return

    -
    -
    -
    - -
    -
    -run() → Iterator[Dict[str, Any]][source]ΒΆ
    -

    Perform the work for the job. -Runs and saves the appropriate benchmark based on the configuration

    -
    -
    Returns
    -

    an iterator containing progress update information

    -
    -
    -
    - -
    -
    -property warmup_iterations_per_checkΒΆ
    -

    the number of warmup iterations to run for before checking -performance / timing

    -
    -
    Type
    -

    return

    -
    -
    -
    - -
    - +
    +

    sparsify.workers.projects_benchmark moduleΒΆ

    -
    -

    sparsify.workers.projects_data moduleΒΆ

    -

    Code related to the project_data implementations for job workers

    -
    -
    -class sparsify.workers.projects_data.DataFromPathJobWorker(job_id: str, project_id: str, data_id: str, uri: str)[source]ΒΆ
    -

    Bases: sparsify.workers.projects_data._DataLoaderJobWorker

    -

    A job worker for retrieving .npz data files from a given uri. -The uri can be either a local file path or a public url.

    -
    -
    Parameters
    -
      -

    • job_id – the id of the job this worker is running under

      • -

    • project_id – the id of the project the worker is running for

      • -

    • data_id – the id of the data the worker is running for

      • -

    • uri – the uri to retrieve

      • -
    -
    -
    -
    -
    -run() → Iterator[Dict[str, Any]][source]ΒΆ
    -

    Perform the work for the job. -Downloads the data files from a public url if the uri is a public url. -Copies the data if the uri is accessible through the local file system. -If the uri points to tar file, extract and save any additional data objects

    -
    -
    Returns
    -

    an iterator containing progress update information

    -
    -
    -
    - -
    - -
    -
    -class sparsify.workers.projects_data.DataFromRepoJobWorker(job_id: str, project_id: str, data_id: str, uri: str)[source]ΒΆ
    -

    Bases: sparsify.workers.projects_data._DataLoaderJobWorker

    -

    A job worker for retrieving .npz data files from a given uri. -The uri can be either a local file path or a public url.

    -
    -
    Parameters
    -
      -

    • job_id – the id of the job this worker is running under

      • -

    • project_id – the id of the project the worker is running for

      • -

    • data_id – the id of the data the worker is running for

      • -

    • uri – the uri to retrieve

      • -
    -
    -
    -
    -
    -run() → Iterator[Dict[str, Any]][source]ΒΆ
    -

    Perform the work for the job.

    -
    -
    Returns
    -

    an iterator containing progress update information

    -
    -
    -
    - -
    - +
    +

    sparsify.workers.projects_data moduleΒΆ

    -
    -

    sparsify.workers.projects_model moduleΒΆ

    -

    Code related to the base implementations for job workers

    -
    -
    -class sparsify.workers.projects_model.ModelFromPathJobWorker(job_id: str, project_id: str, model_id: str, uri: str)[source]ΒΆ
    -

    Bases: sparsify.workers.projects_model._ModelLoaderJobWorker

    -

    A job worker for retrieving a model (currently ONNX) from a given uri. -The uri can be either a local file path or a public url.

    -
    -
    Parameters
    -
      -

    • job_id – the id of the job this worker is running under

      • -

    • project_id – the id of the project the worker is running for

      • -

    • model_id – the id of the model the worker is running for

      • -

    • uri – the uri to retrieve

      • -
    -
    -
    -
    -
    -run() → Iterator[Dict[str, Any]][source]ΒΆ
    -

    Perform the work for the job. -Downloads the model from a public url if the uri is a public url. -Copies the model if the uri is accessible through the local file system.

    -
    -
    Returns
    -

    an iterator containing progress update information

    -
    -
    -
    - -
    - -
    -
    -class sparsify.workers.projects_model.ModelFromRepoJobWorker(job_id: str, project_id: str, model_id: str, uri: str)[source]ΒΆ
    -

    Bases: sparsify.workers.projects_model._ModelLoaderJobWorker

    -

    A job worker for retrieving a model (currently ONNX) from a given uri -from within the Neural Magic model repo.

    -
    -
    Parameters
    -
      -

    • job_id – the id of the job this worker is running under

      • -

    • project_id – the id of the project the worker is running for

      • -

    • model_id – the id of the model the worker is running for

      • -

    • uri – the uri to retrieve

      • -
    -
    -
    -
    -
    -run() → Iterator[Dict[str, Any]][source]ΒΆ
    -

    Perform the work for the job. -Downloads the model from the model repo.

    -
    -
    Returns
    -

    an iterator containing progress update information

    -
    -
    -
    - -
    - +
    +

    sparsify.workers.projects_model moduleΒΆ

    -
    -

    sparsify.workers.projects_profiles moduleΒΆ

    -

    Job workers for running profiles within a project

    -
    -
    -class sparsify.workers.projects_profiles.CreateLossProfileJobWorker(job_id: str, project_id: str, model_id: str, profile_id: str, pruning_estimations: bool, pruning_estimation_type: str, pruning_structure: str, quantized_estimations: bool)[source]ΒΆ
    -

    Bases: sparsify.workers.projects_profiles.BaseProfileJobWorker

    -

    A job worker for running and saving a loss profile for a given project -and configuration.

    -
    -
    Parameters
    -
      -

    • job_id – the id of the job this worker is running under

      • -

    • project_id – the id of the project the worker is running for

      • -

    • model_id – id of the model to run the profile for

      • -

    • profile_id – the profile id of the profile that should be updated

      • -

    • pruning_estimations – True to include pruning profile information

      • -

    • pruning_estimation_type – loss analysis type to run, -weight_magnitude or one_shot

      • -

    • pruning_structure – type of pruning to use, (unstructured, block_4…)

      • -

    • quantized_estimations – True to include quantized information in the profile

      • -
    -
    -
    -
    -
    -classmethod format_args(model_id: str, profile_id: str, pruning_estimations: bool, pruning_estimation_type: str, pruning_structure: str, quantized_estimations: bool, **kwargs) → Union[None, Dict[str, Any]][source]ΒΆ
    -

    Format a given args into proper args to be stored for later use -in the constructor for the job worker.

    -
    -
    Parameters
    -
      -

    • model_id – id of the model to run the loss profile for

      • -

    • profile_id – the profile id of the loss profile that should be updated

      • -

    • pruning_estimations – True to include pruning profile information

      • -

    • pruning_estimation_type – loss analysis type to run, -weight_magnitude or one_shot

      • -

    • pruning_structure – type of pruning to use, (unstructured, block_4…)

      • -

    • quantized_estimations – True to include quantized information -in the profile, False otherwise

      • -
    -
    -
    Returns
    -

    the formatted args to be stored for later use

    -
    -
    -
    - -
    -
    -property model_idΒΆ
    -

    id of the model to run the loss profile for

    -
    -
    Type
    -

    return

    -
    -
    -
    - -
    -
    -property profile_idΒΆ
    -

    the profile id of the loss profile that should be updated

    -
    -
    Type
    -

    return

    -
    -
    -
    - -
    -
    -property pruning_estimation_typeΒΆ
    -

    loss analysis type to run, -weight_magnitude or one_shot

    -
    -
    Type
    -

    return

    -
    -
    -
    - -
    -
    -property pruning_estimationsΒΆ
    -

    True to include pruning profile information

    -
    -
    Type
    -

    return

    -
    -
    -
    - -
    -
    -property pruning_structureΒΆ
    -

    type of pruning to use, (unstructured, block_4…)

    -
    -
    Type
    -

    return

    -
    -
    -
    - -
    -
    -property quantized_estimationsΒΆ
    -

    True to include quantized information -in the profile, False otherwise

    -
    -
    Type
    -

    return

    -
    -
    -
    - -
    -
    -run() → Iterator[Dict[str, Any]][source]ΒΆ
    -

    Perform the work for the job. -Runs and saves the appropriate loss profile based on the configuration

    -
    -
    Returns
    -

    an iterator containing progress update information

    -
    -
    -
    - -
    - -
    -
    -class sparsify.workers.projects_profiles.CreatePerfProfileJobWorker(job_id: str, project_id: str, model_id: str, profile_id: str, batch_size: int, core_count: int, pruning_estimations: bool, quantized_estimations: bool, iterations_per_check: int, warmup_iterations_per_check: int)[source]ΒΆ
    -

    Bases: sparsify.workers.projects_profiles.BaseProfileJobWorker

    -

    A job worker for running and saving a perf profile for a given project -and configuration.

    -
    -
    Parameters
    -
      -

    • job_id – the id of the job this worker is running under

      • -

    • project_id – the id of the project the worker is running for

      • -

    • model_id – id of the model to run the profile for

      • -

    • profile_id – the profile id of the profile that should be updated

      • -

    • batch_size – batch size to use for perf analysis

      • -

    • core_count – number of cores to run on for perf analysis. -1 will use -the maximum cores available

      • -

    • pruning_estimations – True to include pruning measurements

      • -

    • quantized_estimations – True to include quantization measurements

      • -

    • iterations_per_check – number of iterations of the batch size to -run for each measurement check

      • -

    • warmup_iterations_per_check – number of warmup iterations of the batch -size to run before each measurement check

      • -
    -
    -
    -
    -
    -property batch_sizeΒΆ
    -

    batch size to use for perf analysis

    -
    -
    Type
    -

    return

    -
    -
    -
    - -
    -
    -property core_countΒΆ
    -

    number of cores to run on for perf analysis. --1 will use the maximum cores available

    -
    -
    Type
    -

    return

    -
    -
    -
    - -
    -
    -classmethod format_args(model_id: str, profile_id: str, batch_size: int, core_count: int, pruning_estimations: bool, quantized_estimations: bool, iterations_per_check: int, warmup_iterations_per_check: int, **kwargs) → Union[None, Dict[str, Any]][source]ΒΆ
    -

    Format a given args into proper args to be stored for later use -in the constructor for the job worker.

    -
    -
    Parameters
    -
      -

    • model_id – id of the model to run the loss profile for

      • -

    • profile_id – the profile id of the loss profile that should be updated

      • -

    • batch_size – batch size to use for perf analysis

      • -

    • core_count – number of cores to run on for perf analysis. --1 will use the maximum cores available

      • -

    • pruning_estimations – True to include pruning measurements

      • -

    • quantized_estimations – True to include quantization measurements

      • -

    • iterations_per_check – number of iterations of the batch size to -run for each measurement check

      • -

    • warmup_iterations_per_check – number of warmup iterations of the batch -size to run before each measurement check

      • -
    -
    -
    Returns
    -

    the formatted args to be stored for later use

    -
    -
    -
    - -
    -
    -property iterations_per_checkΒΆ
    -

    number of iterations of the batch size to -run for each measurement check

    -
    -
    Type
    -

    return

    -
    -
    -
    - -
    -
    -property pruning_estimationsΒΆ
    -

    True to include pruning profile information

    -
    -
    Type
    -

    return

    -
    -
    -
    - -
    -
    -property quantized_estimationsΒΆ
    -

    True to include quantized information -in the profile, False otherwise

    -
    -
    Type
    -

    return

    -
    -
    -
    - -
    -
    -run() → Iterator[Dict[str, Any]][source]ΒΆ
    -

    Perform the work for the job. -Runs and saves the appropriate perf profile based on the configuration

    -
    -
    Returns
    -

    an iterator containing progress update information

    -
    -
    -
    - -
    -
    -property warmup_iterations_per_checkΒΆ
    -

    number of warmup iterations of the batch -size to run before each measurement check

    -
    -
    Type
    -

    return

    -
    -
    -
    - -
    - +
    +

    sparsify.workers.projects_profiles moduleΒΆ

    -
    -

    Module contentsΒΆ

    -

    Code for running background jobs

    +
    +

    Module contentsΒΆ

    diff --git a/sparsify/genindex.html b/sparsify/genindex.html index 5ebcc01bb0c..83170ff7cd2 100644 --- a/sparsify/genindex.html +++ b/sparsify/genindex.html @@ -178,1998 +178,8 @@

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    diff --git a/sparsify/index.html b/sparsify/index.html index 2dab35e4966..7eaece5160b 100644 --- a/sparsify/index.html +++ b/sparsify/index.html @@ -313,9 +313,9 @@

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