From a73fe94b4c451dd5fb5e6eeb9669799639e5ed58 Mon Sep 17 00:00:00 2001 From: pytorchbot Date: Mon, 9 Dec 2024 22:59:24 +0000 Subject: [PATCH] auto-generating sphinx docs --- .../tensordict_module.zip | Bin 33264 -> 33264 bytes .../export.zip | Bin 26494 -> 26494 bytes .../tensordict_keys.zip | Bin 23454 -> 23454 bytes .../tutorials_python.zip | Bin 107199 -> 107199 bytes .../tensorclass_imagenet.zip | Bin 35149 -> 35149 bytes .../tensordict_shapes.zip | Bin 32082 -> 32082 bytes .../tensorclass_fashion.zip | Bin 19775 -> 19775 bytes .../tensordict_memory.zip | Bin 13262 -> 13262 bytes .../tensordict_preallocation.zip | Bin 7260 -> 7260 bytes .../tutorials_jupyter.zip | Bin 132939 -> 132939 bytes .../data_fashion.zip | Bin 19247 -> 19247 bytes .../streamed_tensordict.zip | Bin 21938 -> 21938 bytes .../tensordict_slicing.zip | Bin 8411 -> 8411 bytes main/_sources/sg_execution_times.rst.txt | 18 +- main/_sources/tutorials/data_fashion.rst.txt | 226 +++++++-------- main/_sources/tutorials/export.rst.txt | 18 +- .../tutorials/sg_execution_times.rst.txt | 18 +- .../tutorials/streamed_tensordict.rst.txt | 2 +- .../tutorials/tensorclass_fashion.rst.txt | 234 ++++++++-------- .../tutorials/tensorclass_imagenet.rst.txt | 20 +- .../tutorials/tensordict_keys.rst.txt | 2 +- .../tutorials/tensordict_memory.rst.txt | 2 +- .../tutorials/tensordict_module.rst.txt | 14 +- .../tutorials/tensordict_shapes.rst.txt | 18 +- .../generated/tensordict.NonTensorStack.html | 3 +- main/searchindex.js | 2 +- main/sg_execution_times.html | 18 +- main/tutorials/data_fashion.html | 226 +++++++-------- main/tutorials/export.html | 18 +- main/tutorials/sg_execution_times.html | 18 +- main/tutorials/streamed_tensordict.html | 2 +- main/tutorials/tensorclass_fashion.html | 258 +++++++++--------- main/tutorials/tensorclass_imagenet.html | 21 +- main/tutorials/tensordict_keys.html | 2 +- main/tutorials/tensordict_memory.html | 2 +- main/tutorials/tensordict_module.html | 14 +- 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================= -**02:31.166** total execution time for 11 files **from all galleries**: +**02:29.990** total execution time for 11 files **from all galleries**: .. container:: @@ -33,25 +33,25 @@ Computation times - Time - Mem (MB) * - :ref:`sphx_glr_tutorials_tensorclass_fashion.py` (``reference/generated/tutorials/tensorclass_fashion.py``) - - 01:00.839 + - 01:00.862 - 0.0 * - :ref:`sphx_glr_tutorials_data_fashion.py` (``reference/generated/tutorials/data_fashion.py``) - - 00:55.706 + - 00:54.911 - 0.0 * - :ref:`sphx_glr_tutorials_tensordict_module.py` (``reference/generated/tutorials/tensordict_module.py``) - - 00:20.006 + - 00:19.686 - 0.0 * - :ref:`sphx_glr_tutorials_streamed_tensordict.py` (``reference/generated/tutorials/streamed_tensordict.py``) - - 00:11.020 + - 00:11.022 - 0.0 * - :ref:`sphx_glr_tutorials_export.py` (``reference/generated/tutorials/export.py``) - - 00:01.864 + - 00:01.824 - 0.0 * - :ref:`sphx_glr_tutorials_tensorclass_imagenet.py` (``reference/generated/tutorials/tensorclass_imagenet.py``) - - 00:01.699 + - 00:01.657 - 0.0 * - :ref:`sphx_glr_tutorials_tensordict_keys.py` (``reference/generated/tutorials/tensordict_keys.py``) - - 00:00.010 + - 00:00.009 - 0.0 * - :ref:`sphx_glr_tutorials_tensordict_shapes.py` (``reference/generated/tutorials/tensordict_shapes.py``) - 00:00.008 @@ -60,7 +60,7 @@ Computation times - 00:00.005 - 0.0 * - :ref:`sphx_glr_tutorials_tensordict_memory.py` (``reference/generated/tutorials/tensordict_memory.py``) - - 00:00.005 + - 00:00.004 - 0.0 * - :ref:`sphx_glr_tutorials_tensordict_preallocation.py` (``reference/generated/tutorials/tensordict_preallocation.py``) - 00:00.003 diff --git a/main/_sources/tutorials/data_fashion.rst.txt b/main/_sources/tutorials/data_fashion.rst.txt index 27f7b1bed..04f72df57 100644 --- a/main/_sources/tutorials/data_fashion.rst.txt +++ b/main/_sources/tutorials/data_fashion.rst.txt @@ -423,156 +423,156 @@ adjust how we unpack the data to the more explicit key-based retrieval offered b is_shared=False) Epoch 1 ------------------------- - loss: 2.308235 [ 0/60000] - loss: 2.290428 [ 6400/60000] - loss: 2.272404 [12800/60000] - loss: 2.270692 [19200/60000] - loss: 2.250867 [25600/60000] - loss: 2.219301 [32000/60000] - loss: 2.237770 [38400/60000] - loss: 2.193873 [44800/60000] - loss: 2.195773 [51200/60000] - loss: 2.177800 [57600/60000] + loss: 2.300076 [ 0/60000] + loss: 2.286131 [ 6400/60000] + loss: 2.270285 [12800/60000] + loss: 2.269111 [19200/60000] + loss: 2.246381 [25600/60000] + loss: 2.232410 [32000/60000] + loss: 2.226862 [38400/60000] + loss: 2.200187 [44800/60000] + loss: 2.191414 [51200/60000] + loss: 2.166425 [57600/60000] Test Error: - Accuracy: 41.6%, Avg loss: 2.155380 + Accuracy: 49.6%, Avg loss: 2.163558 Epoch 2 ------------------------- - loss: 2.165997 [ 0/60000] - loss: 2.152457 [ 6400/60000] - loss: 2.089101 [12800/60000] - loss: 2.111734 [19200/60000] - loss: 2.067156 [25600/60000] - loss: 1.996914 [32000/60000] - loss: 2.044302 [38400/60000] - loss: 1.953458 [44800/60000] - loss: 1.964826 [51200/60000] - loss: 1.911599 [57600/60000] + loss: 2.169617 [ 0/60000] + loss: 2.159865 [ 6400/60000] + loss: 2.108187 [12800/60000] + loss: 2.129137 [19200/60000] + loss: 2.074021 [25600/60000] + loss: 2.023518 [32000/60000] + loss: 2.047665 [38400/60000] + loss: 1.969611 [44800/60000] + loss: 1.970435 [51200/60000] + loss: 1.909339 [57600/60000] Test Error: - Accuracy: 52.9%, Avg loss: 1.885347 + Accuracy: 55.3%, Avg loss: 1.904233 Epoch 3 ------------------------- - loss: 1.917414 [ 0/60000] - loss: 1.880982 [ 6400/60000] - loss: 1.754690 [12800/60000] - loss: 1.811048 [19200/60000] - loss: 1.710644 [25600/60000] - loss: 1.653802 [32000/60000] - loss: 1.698502 [38400/60000] - loss: 1.586629 [44800/60000] - loss: 1.619078 [51200/60000] - loss: 1.530940 [57600/60000] + loss: 1.931548 [ 0/60000] + loss: 1.902627 [ 6400/60000] + loss: 1.787215 [12800/60000] + loss: 1.838000 [19200/60000] + loss: 1.722751 [25600/60000] + loss: 1.671043 [32000/60000] + loss: 1.698132 [38400/60000] + loss: 1.589851 [44800/60000] + loss: 1.611929 [51200/60000] + loss: 1.516776 [57600/60000] Test Error: - Accuracy: 61.0%, Avg loss: 1.523789 + Accuracy: 61.2%, Avg loss: 1.529558 Epoch 4 ------------------------- - loss: 1.587635 [ 0/60000] - loss: 1.547149 [ 6400/60000] - loss: 1.394430 [12800/60000] - loss: 1.478471 [19200/60000] - loss: 1.364701 [25600/60000] - loss: 1.353640 [32000/60000] - loss: 1.377746 [38400/60000] - loss: 1.296400 [44800/60000] - loss: 1.337154 [51200/60000] - loss: 1.241225 [57600/60000] + loss: 1.591249 [ 0/60000] + loss: 1.554227 [ 6400/60000] + loss: 1.404630 [12800/60000] + loss: 1.492260 [19200/60000] + loss: 1.367048 [25600/60000] + loss: 1.355335 [32000/60000] + loss: 1.376330 [38400/60000] + loss: 1.291993 [44800/60000] + loss: 1.328009 [51200/60000] + loss: 1.234482 [57600/60000] Test Error: - Accuracy: 63.8%, Avg loss: 1.256419 + Accuracy: 64.1%, Avg loss: 1.258872 Epoch 5 ------------------------- - loss: 1.330760 [ 0/60000] - loss: 1.307394 [ 6400/60000] - loss: 1.146088 [12800/60000] - loss: 1.255699 [19200/60000] - loss: 1.136910 [25600/60000] - loss: 1.152944 [32000/60000] - loss: 1.175349 [38400/60000] - loss: 1.112468 [44800/60000] - loss: 1.159765 [51200/60000] - loss: 1.070423 [57600/60000] + loss: 1.335057 [ 0/60000] + loss: 1.311481 [ 6400/60000] + loss: 1.146769 [12800/60000] + loss: 1.267080 [19200/60000] + loss: 1.139563 [25600/60000] + loss: 1.155214 [32000/60000] + loss: 1.180817 [38400/60000] + loss: 1.110676 [44800/60000] + loss: 1.153375 [51200/60000] + loss: 1.072037 [57600/60000] Test Error: - Accuracy: 65.2%, Avg loss: 1.087738 + Accuracy: 65.1%, Avg loss: 1.092873 - TensorDict training done! time: 8.5392 s + TensorDict training done! time: 8.7976 s Epoch 1 ------------------------- - loss: 2.301747 [ 0/60000] - loss: 2.295032 [ 6400/60000] - loss: 2.279933 [12800/60000] - loss: 2.278636 [19200/60000] - loss: 2.268745 [25600/60000] - loss: 2.236384 [32000/60000] - loss: 2.248804 [38400/60000] - loss: 2.216845 [44800/60000] - loss: 2.219797 [51200/60000] - loss: 2.192523 [57600/60000] + loss: 2.296688 [ 0/60000] + loss: 2.288965 [ 6400/60000] + loss: 2.276427 [12800/60000] + loss: 2.270163 [19200/60000] + loss: 2.243812 [25600/60000] + loss: 2.231423 [32000/60000] + loss: 2.236040 [38400/60000] + loss: 2.204681 [44800/60000] + loss: 2.199894 [51200/60000] + loss: 2.183506 [57600/60000] Test Error: - Accuracy: 46.4%, Avg loss: 2.188948 + Accuracy: 54.0%, Avg loss: 2.171313 Epoch 2 ------------------------- - loss: 2.192766 [ 0/60000] - loss: 2.184700 [ 6400/60000] - loss: 2.142058 [12800/60000] - loss: 2.161197 [19200/60000] - loss: 2.117076 [25600/60000] - loss: 2.063707 [32000/60000] - loss: 2.095457 [38400/60000] - loss: 2.023851 [44800/60000] - loss: 2.038857 [51200/60000] - loss: 1.978099 [57600/60000] + loss: 2.178011 [ 0/60000] + loss: 2.167310 [ 6400/60000] + loss: 2.121355 [12800/60000] + loss: 2.132777 [19200/60000] + loss: 2.077321 [25600/60000] + loss: 2.037216 [32000/60000] + loss: 2.065279 [38400/60000] + loss: 1.991604 [44800/60000] + loss: 1.993688 [51200/60000] + loss: 1.945264 [57600/60000] Test Error: - Accuracy: 52.3%, Avg loss: 1.970957 + Accuracy: 58.0%, Avg loss: 1.931493 Epoch 3 ------------------------- - loss: 1.990906 [ 0/60000] - loss: 1.967228 [ 6400/60000] - loss: 1.868619 [12800/60000] - loss: 1.912106 [19200/60000] - loss: 1.808444 [25600/60000] - loss: 1.746715 [32000/60000] - loss: 1.782484 [38400/60000] - loss: 1.673189 [44800/60000] - loss: 1.709751 [51200/60000] - loss: 1.609759 [57600/60000] + loss: 1.958883 [ 0/60000] + loss: 1.928166 [ 6400/60000] + loss: 1.826211 [12800/60000] + loss: 1.859600 [19200/60000] + loss: 1.752121 [25600/60000] + loss: 1.713980 [32000/60000] + loss: 1.735593 [38400/60000] + loss: 1.639609 [44800/60000] + loss: 1.658125 [51200/60000] + loss: 1.568059 [57600/60000] Test Error: - Accuracy: 60.1%, Avg loss: 1.616188 + Accuracy: 59.8%, Avg loss: 1.578069 Epoch 4 ------------------------- - loss: 1.667624 [ 0/60000] - loss: 1.636496 [ 6400/60000] - loss: 1.492325 [12800/60000] - loss: 1.563238 [19200/60000] - loss: 1.448025 [25600/60000] - loss: 1.421502 [32000/60000] - loss: 1.442929 [38400/60000] - loss: 1.355865 [44800/60000] - loss: 1.400344 [51200/60000] - loss: 1.292719 [57600/60000] + loss: 1.641037 [ 0/60000] + loss: 1.601733 [ 6400/60000] + loss: 1.462240 [12800/60000] + loss: 1.520895 [19200/60000] + loss: 1.408690 [25600/60000] + loss: 1.401289 [32000/60000] + loss: 1.408055 [38400/60000] + loss: 1.339955 [44800/60000] + loss: 1.367329 [51200/60000] + loss: 1.270362 [57600/60000] Test Error: - Accuracy: 62.6%, Avg loss: 1.317928 + Accuracy: 62.0%, Avg loss: 1.300243 Epoch 5 ------------------------- - loss: 1.387819 [ 0/60000] - loss: 1.372476 [ 6400/60000] - loss: 1.209445 [12800/60000] - loss: 1.308686 [19200/60000] - loss: 1.190643 [25600/60000] - loss: 1.199597 [32000/60000] - loss: 1.219788 [38400/60000] - loss: 1.151322 [44800/60000] - loss: 1.197672 [51200/60000] - loss: 1.104183 [57600/60000] + loss: 1.380182 [ 0/60000] + loss: 1.355997 [ 6400/60000] + loss: 1.197436 [12800/60000] + loss: 1.285367 [19200/60000] + loss: 1.172652 [25600/60000] + loss: 1.192038 [32000/60000] + loss: 1.199795 [38400/60000] + loss: 1.150505 [44800/60000] + loss: 1.181850 [51200/60000] + loss: 1.097848 [57600/60000] Test Error: - Accuracy: 64.4%, Avg loss: 1.128394 + Accuracy: 64.0%, Avg loss: 1.124975 - Training done! time: 34.7385 s + Training done! time: 34.0093 s @@ -580,7 +580,7 @@ adjust how we unpack the data to the more explicit key-based retrieval offered b .. rst-class:: sphx-glr-timing - **Total running time of the script:** (0 minutes 55.706 seconds) + **Total running time of the script:** (0 minutes 54.911 seconds) .. _sphx_glr_download_tutorials_data_fashion.py: diff --git a/main/_sources/tutorials/export.rst.txt b/main/_sources/tutorials/export.rst.txt index ffea72977..f0100e9e2 100644 --- a/main/_sources/tutorials/export.rst.txt +++ b/main/_sources/tutorials/export.rst.txt @@ -141,7 +141,7 @@ Let us run this model and see what the output looks like: .. code-block:: none - (tensor([[0.0000, 1.2591, 2.3107, 0.0000]], grad_fn=), tensor([[ 0.4546, -0.8538, 0.0919, 1.0503]], grad_fn=), tensor([[ 0.4546, -0.8538]], grad_fn=), tensor([[1.0587, 1.7738]], grad_fn=), tensor([[ 0.4546, -0.8538]], grad_fn=)) + (tensor([[0.3425, 0.0000, 0.0000, 0.9478]], grad_fn=), tensor([[-0.4300, 0.9601, -0.2439, 0.1372]], grad_fn=), tensor([[-0.4300, 0.9601]], grad_fn=), tensor([[0.8538, 1.0884]], grad_fn=), tensor([[-0.4300, 0.9601]], grad_fn=)) @@ -266,8 +266,8 @@ This module can be run exactly like our original module (with a lower overhead): .. code-block:: none - Time for TDModule: 591.04 micro-seconds - Time for exported module: 343.80 micro-seconds + Time for TDModule: 573.40 micro-seconds + Time for exported module: 362.40 micro-seconds @@ -297,7 +297,7 @@ and the FX graph: relu: "f32[1, 4]" = torch.ops.aten.relu.default(linear); linear = None linear_1: "f32[1, 4]" = torch.ops.aten.linear.default(relu, p_l__args___0_module_2_module_weight, p_l__args___0_module_2_module_bias); p_l__args___0_module_2_module_weight = p_l__args___0_module_2_module_bias = None - # File: /pytorch/tensordict/tensordict/nn/distributions/continuous.py:129 in forward, code: loc, scale = tensor.chunk(2, -1) + # File: /pytorch/tensordict/tensordict/nn/distributions/continuous.py:130 in forward, code: loc, scale = tensor.chunk(2, -1) chunk = torch.ops.aten.chunk.default(linear_1, 2, -1) getitem: "f32[1, 2]" = chunk[0] getitem_1: "f32[1, 2]" = chunk[1]; chunk = None @@ -307,7 +307,7 @@ and the FX graph: softplus: "f32[1, 2]" = torch.ops.aten.softplus.default(add); add = None add_1: "f32[1, 2]" = torch.ops.aten.add.Tensor(softplus, 0.01); softplus = None - # File: /pytorch/tensordict/tensordict/nn/distributions/continuous.py:130 in forward, code: scale = self.scale_mapping(scale).clamp_min(self.scale_lb) + # File: /pytorch/tensordict/tensordict/nn/distributions/continuous.py:131 in forward, code: scale = self.scale_mapping(scale).clamp_min(self.scale_lb) clamp_min: "f32[1, 2]" = torch.ops.aten.clamp_min.default(add_1, 0.0001); add_1 = None # File: /pytorch/tensordict/env/lib/python3.10/site-packages/torch/distributions/utils.py:55 in broadcast_all, code: return torch.broadcast_tensors(*values) @@ -323,7 +323,7 @@ and the FX graph: relu: "f32[1, 4]" = torch.ops.aten.relu.default(linear); linear = None linear_1: "f32[1, 4]" = torch.ops.aten.linear.default(relu, p_l__args___0_module_2_module_weight, p_l__args___0_module_2_module_bias); p_l__args___0_module_2_module_weight = p_l__args___0_module_2_module_bias = None - # File: /pytorch/tensordict/tensordict/nn/distributions/continuous.py:129 in forward, code: loc, scale = tensor.chunk(2, -1) + # File: /pytorch/tensordict/tensordict/nn/distributions/continuous.py:130 in forward, code: loc, scale = tensor.chunk(2, -1) chunk = torch.ops.aten.chunk.default(linear_1, 2, -1) getitem: "f32[1, 2]" = chunk[0] getitem_1: "f32[1, 2]" = chunk[1]; chunk = None @@ -333,7 +333,7 @@ and the FX graph: softplus: "f32[1, 2]" = torch.ops.aten.softplus.default(add); add = None add_1: "f32[1, 2]" = torch.ops.aten.add.Tensor(softplus, 0.01); softplus = None - # File: /pytorch/tensordict/tensordict/nn/distributions/continuous.py:130 in forward, code: scale = self.scale_mapping(scale).clamp_min(self.scale_lb) + # File: /pytorch/tensordict/tensordict/nn/distributions/continuous.py:131 in forward, code: scale = self.scale_mapping(scale).clamp_min(self.scale_lb) clamp_min: "f32[1, 2]" = torch.ops.aten.clamp_min.default(add_1, 0.0001); add_1 = None # File: /pytorch/tensordict/env/lib/python3.10/site-packages/torch/distributions/utils.py:55 in broadcast_all, code: return torch.broadcast_tensors(*values) @@ -450,7 +450,7 @@ distribution: .. code-block:: none - tensor([[ 0.4546, -0.8538]], grad_fn=) + tensor([[-0.4300, 0.9601]], grad_fn=) @@ -657,7 +657,7 @@ Next steps and further reading .. rst-class:: sphx-glr-timing - **Total running time of the script:** (0 minutes 1.864 seconds) + **Total running time of the script:** (0 minutes 1.824 seconds) .. _sphx_glr_download_tutorials_export.py: diff --git a/main/_sources/tutorials/sg_execution_times.rst.txt b/main/_sources/tutorials/sg_execution_times.rst.txt index f3bdbc3b0..aaae9f584 100644 --- a/main/_sources/tutorials/sg_execution_times.rst.txt +++ b/main/_sources/tutorials/sg_execution_times.rst.txt @@ -6,7 +6,7 @@ Computation times ================= -**02:31.166** total execution time for 11 files **from tutorials**: +**02:29.990** total execution time for 11 files **from tutorials**: .. container:: @@ -33,25 +33,25 @@ Computation times - Time - Mem (MB) * - :ref:`sphx_glr_tutorials_tensorclass_fashion.py` (``tensorclass_fashion.py``) - - 01:00.839 + - 01:00.862 - 0.0 * - :ref:`sphx_glr_tutorials_data_fashion.py` (``data_fashion.py``) - - 00:55.706 + - 00:54.911 - 0.0 * - :ref:`sphx_glr_tutorials_tensordict_module.py` (``tensordict_module.py``) - - 00:20.006 + - 00:19.686 - 0.0 * - :ref:`sphx_glr_tutorials_streamed_tensordict.py` (``streamed_tensordict.py``) - - 00:11.020 + - 00:11.022 - 0.0 * - :ref:`sphx_glr_tutorials_export.py` (``export.py``) - - 00:01.864 + - 00:01.824 - 0.0 * - :ref:`sphx_glr_tutorials_tensorclass_imagenet.py` (``tensorclass_imagenet.py``) - - 00:01.699 + - 00:01.657 - 0.0 * - :ref:`sphx_glr_tutorials_tensordict_keys.py` (``tensordict_keys.py``) - - 00:00.010 + - 00:00.009 - 0.0 * - :ref:`sphx_glr_tutorials_tensordict_shapes.py` (``tensordict_shapes.py``) - 00:00.008 @@ -60,7 +60,7 @@ Computation times - 00:00.005 - 0.0 * - :ref:`sphx_glr_tutorials_tensordict_memory.py` (``tensordict_memory.py``) - - 00:00.005 + - 00:00.004 - 0.0 * - :ref:`sphx_glr_tutorials_tensordict_preallocation.py` (``tensordict_preallocation.py``) - 00:00.003 diff --git a/main/_sources/tutorials/streamed_tensordict.rst.txt b/main/_sources/tutorials/streamed_tensordict.rst.txt index 8d33459c1..0de78db9a 100644 --- a/main/_sources/tutorials/streamed_tensordict.rst.txt +++ b/main/_sources/tutorials/streamed_tensordict.rst.txt @@ -444,7 +444,7 @@ Thanks for following along with this tutorial! We hope you've found it helpful a .. rst-class:: sphx-glr-timing - **Total running time of the script:** (0 minutes 11.020 seconds) + **Total running time of the script:** (0 minutes 11.022 seconds) .. _sphx_glr_download_tutorials_streamed_tensordict.py: diff --git a/main/_sources/tutorials/tensorclass_fashion.rst.txt b/main/_sources/tutorials/tensorclass_fashion.rst.txt index 381f84186..0d0c99e6d 100644 --- a/main/_sources/tutorials/tensorclass_fashion.rst.txt +++ b/main/_sources/tutorials/tensorclass_fashion.rst.txt @@ -94,10 +94,10 @@ the image (e.g. "Bag", "Sneaker" etc.). .. code-block:: none - 0%| | 0.00/26.4M [00:00NonTensorStack
property data
-

Returns a tensordict containing the .data attributes of the leaf tensors.

+

Attempts to return the unique value in the stack.

+

Raises a ValueError if there is more than one unique value.

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Computation times

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02:31.166 total execution time for 11 files from all galleries:

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02:29.990 total execution time for 11 files from all galleries: