Normalize all std imports to use import std / xxx

This also removes a few unnecessary imports of the complex and math modules (which are automatically exported by arraymancer). The test touches a lot funtions but the changes are minimal and simple (basically changing things like `import unittest, os` into `import std / [unittest, os]` and so on).

benchmarks/euler_nativearray.nim

@@ -1,4 +1,4 @@
-import math, times, strformat
+import std / [math, times, strformat]
 
 const
   dz = 0.1

benchmarks/euler_tensor.nim

@@ -1,4 +1,4 @@
-import math, times, strformat
+import std / [times, strformat]
 import ../src/arraymancer
 
 proc getTime(): float =

benchmarks/euler_tensor_optim.nim

@@ -1,4 +1,4 @@
-import math, times, strformat
+import std / [times, strformat]
 import ../src/arraymancer
 
 proc getTime(): float =

benchmarks/ex02_mnist.nim

@@ -1,4 +1,5 @@
-import ../src/arraymancer, random
+import ../src/arraymancer
+import std / random
 
 # Make the results reproducible by initializing a random seed
 randomize(42)

benchmarks/implementation/iteration.nim

@@ -1,6 +1,6 @@
 import ../../src/arraymancer
 import ../../src/tensor/backend/[openmp, memory_optimization_hints]
-import times
+import std / times
 
 const
   dz = 0.01

benchmarks/implementation/logsumexp.nim

@@ -1,4 +1,6 @@
-import times, ../../src/arraymancer, math, sequtils
+import std / times
+import ../../src/arraymancer
+import std / sequtils
 
 # Reference python
 # import numpy as np

benchmarks/implementation/proc_method_closure_bench.nim

@@ -1,4 +1,4 @@
-import times
+import std / times
 
 type FooBase = ref object {.inheritable.}
   dummy: int

benchmarks/implementation/stable_sigmoid_bench.nim

@@ -1,4 +1,5 @@
-import times, ../../src/arraymancer, math
+import std / times
+import ../../src/arraymancer
 
 # The goal is to test the speed of various sigmoid implementation
 # Some are numericall stable for positive, negative or both value

benchmarks/implementation/triot.nim

@@ -19,7 +19,7 @@
 
 
 import ../../src/tensor/backend/metadataArray
-import macros
+import std / macros
 
 proc shape_to_strides*(shape: MetadataArray): MetadataArray {.noSideEffect.} =
   var accum = 1
@@ -210,7 +210,7 @@ proc warmup() =
 ################################################################################################
 #### Bench
 
-import times
+import std / times
 
 
 let a = [2, 3, 4].toMetadataArray

benchmarks/integer_matmul.nim

@@ -1,4 +1,4 @@
-import os, strutils, random
+import std / [os, strutils, random]
 import ../src/arraymancer
 
 {.passC: "-march=native" .}

benchmarks/kostya_matmul.nim

@@ -1,6 +1,6 @@
 # From: https://github.com/kostya/benchmarks
 
-import os, strutils
+import std / [os, strutils]
 import ../src/arraymancer
 
 proc matgen(n: int): auto =

benchmarks/kostya_matmul_higher_order_template.nim

@@ -1,6 +1,6 @@
 # From: https://github.com/kostya/benchmarks
 
-import os, strutils, sequtils
+import std / [os, strutils, sequtils]
 import ../src/arraymancer
 
 proc matgen(n: int): auto =

benchmarks/kostya_matmul_list_comprehension.nim

@@ -1,6 +1,6 @@
 # From: https://github.com/kostya/benchmarks
 
-import os, strutils, sugar
+import std / [os, strutils, sugar]
 import ../src/arraymancer
 
 proc matgen(n: int): auto =

benchmarks/kostya_matmul_mitems.nim

@@ -1,6 +1,6 @@
 # From: https://github.com/kostya/benchmarks
 
-import os, strutils
+import std / [os, strutils]
 import ../src/arraymancer
 
 proc divmod[T: SomeInteger](n: T, b: T): (T, T) =

benchmarks/randomized_svd.nim

@@ -1,5 +1,5 @@
 import ../src/arraymancer
-import times, strformat
+import std / [times, strformat]
 
 # Compile with -d:release -d:danger (optionally -d:openmp)
 

docs/docs.nim

@@ -1,14 +1,14 @@
-import macros, strformat, strutils, sequtils, sets, tables, algorithm
+import std / [macros, strformat, strutils, sequtils, sets, tables, algorithm]
 
-from os import parentDir, getCurrentCompilerExe, DirSep, extractFilename, `/`, setCurrentDir
+from std / os import parentDir, getCurrentCompilerExe, DirSep, extractFilename, `/`, setCurrentDir
 
 # NOTE:
 # for some time on devel 1.3.x `paramCount` and `paramStr` had to be imported
 # os, because they were removed for nimscript. This was reverted in:
 # https://github.com/nim-lang/Nim/pull/14658
 # For `nimdoc` we still have to import those from `os`!
 when defined(nimdoc):
-  from os import getCurrentDir, paramCount, paramStr
+  from std / os import getCurrentDir, paramCount, paramStr
 
 #[
 This file is a slightly modified version of the same file of `nimterop`:

examples/ex04_fizzbuzz_interview_cheatsheet.nim

@@ -8,7 +8,8 @@
 #              if it's divisible by 5 print "buzz", and if it's divisible by 15 print "fizzbuzz".
 
 # Let's start with standard imports
-import ../src/arraymancer, math, strformat
+import ../src/arraymancer
+import std / strformat
 
 # We want to input a number and output the correct "fizzbuzz" representation
 # ideally the input is a represented by a vector of real values between 0 and 1

examples/ex07_save_load_model.nim

@@ -1,4 +1,5 @@
-import ../src/arraymancer, strformat, os
+import ../src/arraymancer
+import std / [strformat, os]
 
 #[
 A fully-connected ReLU network with one hidden layer, trained to predict y from x

src/arraymancer/autograd/autograd_common.nim

@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import typetraits, macros
+import std / [typetraits, macros]
 
 # ############################################################
 #

src/arraymancer/datasets/imdb.nim

@@ -13,8 +13,8 @@
 # limitations under the License.
 
 
-import  httpclient, strformat, os, strutils,
-        ./util, ../tensor,
+import std / [httpclient, strformat, os, strutils]
+import ./util, ../tensor,
         untar
 
 const

src/arraymancer/datasets/mnist.nim

@@ -52,8 +52,8 @@
 # The labels values are 0 to 9.
 
 
-import  streams, os, httpClient, strformat, sugar, sequtils,
-        ../tensor, ../io/io_stream_readers, ./util,
+import std / [streams, os, httpClient, strformat, sugar, sequtils]
+import ../tensor, ../io/io_stream_readers, ./util,
         zip/gzipfiles
 
 type Mnist = tuple[

src/arraymancer/datasets/util.nim

@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import os
+import std / os
 
 proc get_cache_home(): string =
     result = getEnv("XDG_CACHE_HOME", getHomeDir() / ".cache")

src/arraymancer/io/io_csv.nim

@@ -13,8 +13,8 @@
 # limitations under the License.
 
 
-import  os, parsecsv, streams, strutils, sequtils, algorithm,
-        ../tensor
+import  std / [os, parsecsv, streams, strutils, sequtils, algorithm]
+import ../tensor
 from memfiles as mf import nil
 
 proc countLinesAndCols(file: string, sep: char, quote: char,

src/arraymancer/laser/openmp.nim

@@ -396,7 +396,7 @@ template omp_taskloop*(
   for `index`{.inject.} in `||`(0, length-1, omp_annotation):
     block: body
 
-import macros
+import std / macros
 macro omp_flush*(variables: varargs[untyped]): untyped =
   var listvars = "("
   for i, variable in variables:

src/arraymancer/laser/tensor/datatypes.nim

@@ -11,7 +11,7 @@ import
 
 when NimVersion < "1.1.0":
   # For distinctBase
-  import sugar
+  import std / sugar
 
 when not defined(nimHasCursor):
   {.pragma: cursor.}

src/arraymancer/laser/tensor/initialization.nim

@@ -3,19 +3,19 @@
 # Distributed under the Apache v2 License (license terms are at http://www.apache.org/licenses/LICENSE-2.0).
 # This file may not be copied, modified, or distributed except according to those terms.
 
-import std/complex
+import std / complex
 
 import
   ../openmp,
   ../compiler_optim_hints,
   ../strided_iteration/foreach,
   ../dynamic_stack_arrays,
   ../private/nested_containers,
-  ./datatypes,
-  # Standard library
-  typetraits, sequtils,
-  # Third-party
-  nimblas
+  ./datatypes
+# Standard library
+import std / [typetraits, sequtils]
+# Third-party
+import nimblas
 
 when (NimMajor, NimMinor) < (1, 4):
   import ../../std_version_types
@@ -289,7 +289,7 @@ func item*[T_IN, T_OUT](t: Tensor[T_IN], _: typedesc[T_OUT]): T_OUT =
       # When the input and the output types are Complex, we need to find
       # the "base" type of the output type (e.g. float32 or float64),
       # and then convert the real and imaginary parts of the input value
-      # into the output base type before creating the output complex type 
+      # into the output base type before creating the output complex type
       type TT = typeof(
         block:
           var tmp: T_OUT

src/arraymancer/linear_algebra/algebra.nim

@@ -2,9 +2,8 @@
 # Distributed under the Apache v2 License (license terms are at http://www.apache.org/licenses/LICENSE-2.0).
 # This file may not be copied, modified, or distributed except according to those terms.
 
-import std/complex
-import
-  ../tensor
+import std / complex
+import ../tensor
 
 proc pinv*[T: SomeFloat](A: Tensor[T], rcond = 1e-15): Tensor[T] =
   ## Compute the (Moore-Penrose) pseudo-inverse of a matrix.

src/arraymancer/linear_algebra/helpers/overload.nim

@@ -1,4 +1,4 @@
-import macros
+import std / macros
 
 # Alias / overload generator
 # --------------------------------------------------------------------------------------

src/arraymancer/linear_algebra/special_matrices.nim

@@ -4,7 +4,7 @@
 
 import ../tensor
 import ./helpers/triangular
-import std/[sequtils, bitops]
+import std / [sequtils, bitops]
 
 proc hilbert*(n: int, T: typedesc[SomeFloat]): Tensor[T] =
   ## Generates an Hilbert matrix of shape [N, N]

src/arraymancer/ml/clustering/dbscan.nim

@@ -1,5 +1,4 @@
-import deques
-import sequtils
+import std / [deques, sequtils]
 
 import ../../spatial/[distances, neighbors],
        ../../tensor

src/arraymancer/nn_primitives/nnp_activation.nim

@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import math
+import std / math
 import  ../tensor,
         ./private/p_activation
 

src/arraymancer/nn_primitives/private/p_activation.nim

@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import math
+import std / math
 
 proc sigmoid*[T: SomeFloat](x: T): T {.inline, noSideEffect.} =
   1 / (1 + exp(-x))

src/arraymancer/private/ast_utils.nim

@@ -14,7 +14,7 @@
 
 # Tools to manipulate Nim Abstract Syntax Tree
 
-import macros
+import std / macros
 
 proc hasType*(x: NimNode, t: static[string]): bool {. compileTime .} =
   ## Compile-time type checking

src/arraymancer/private/deprecate.nim

@@ -12,7 +12,8 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import macros, ./ast_utils
+import std / macros
+import ./ast_utils
 
 # Handle deprecation and replacement
 # --------------------------------------------------------------------------------------

src/arraymancer/private/functional.nim

@@ -13,7 +13,7 @@
 # limitations under the License.
 
 # Functional programming and iterator tooling
-import sequtils
+import std / sequtils
 
 when not defined(nimHasEffectsOf):
   {.pragma: effectsOf.}

src/arraymancer/spatial/distances.nim

@@ -1,5 +1,4 @@
-import math
-import sets
+import std / [math, sets]
 
 import ../tensor
 

src/arraymancer/spatial/kdtree.nim

@@ -1,4 +1,4 @@
-import math, typetraits
+import std / [math, typetraits]
 
 import ../tensor
 import ./distances

src/arraymancer/stats/distributions.nim

@@ -13,7 +13,7 @@
 # limitations under the License.
 
 import ../tensor
-import math
+import std / math
 
 proc gauss*[T](x, mean, sigma: T, norm = false): float =
   ## Returns a value of the gaussian distribution described by `mean`, `sigma`

src/arraymancer/tensor/aggregate.nim

@@ -23,7 +23,7 @@ import  ./data_structure,
         ./accessors_macros_syntax,
         ./algorithms,
         ./private/p_empty_tensors
-import std/[math, macros]
+import std / [math, macros]
 import complex except Complex64, Complex32
 
 # ### Standard aggregate functions
@@ -459,7 +459,7 @@ proc unwrap_period*[T: SomeNumber](t: Tensor[T], discont: T = -1, axis = -1, per
       temp[_] = tAxis +. pAxis
 
 when (NimMajor, NimMinor, NimPatch) > (1, 6, 0):
-  import std/atomics
+  import std / atomics
 proc nonzero*[T](arg: Tensor[T]): Tensor[int] =
   ## Returns the indices, which are non zero as a `Tensor[int]`.
   ##

src/arraymancer/tensor/complex.nim

@@ -2,7 +2,7 @@
 # Distributed under the Apache v2 License (license terms are at http://www.apache.org/licenses/LICENSE-2.0).
 # This file may not be copied, modified, or distributed except according to those terms.
 
-import std/complex
+import std / complex
 import
   ./data_structure,
   ./accessors,

src/arraymancer/tensor/einsum.nim

@@ -1,4 +1,4 @@
-import macros, sequtils, sets, algorithm
+import std / [macros, sequtils, sets, algorithm]
 import ../private/ast_utils
 import ./shapeshifting
   # Note: importing shapeshifting_cuda will trigger a Nim inference bug

src/arraymancer/tensor/exporting.nim

@@ -14,7 +14,7 @@
 
 import ./data_structure
 import ./accessors
-import std/sequtils
+import std / sequtils
 
 proc toRawSeq*[T](t:Tensor[T]): seq[T] {.noSideEffect, deprecated: "This proc cannot be reimplemented in a backward compatible way.".} =
   ## Convert a tensor to the raw sequence of data.