Some warning removals (#635)

* Remove "A custom '=destroy' hook which takes a 'var T' parameter is deprecated" warning from tensor\datatypes.nim

Note that there is still another similar warning left in:

\laser\primitives\matrix_multiplication\gemm_tiling.nim(321, 3)

* Fix typo in comment

* Fix several `imported and not used [UnusedImport]` warnings

In particular:
- Warning: imported and not used: 'datatypes'
- Warning: imported and not used: 'complex'
Warning: imported and not used: 'math'

* Remove a ` conversion from string to itself` hint

Removed from `examples\ex06_shakespeare_generator.nim`.

* Remove `Deprecated since 1.5; TaintedString is deprecated` warning

* Do not crash when no argument is passed to ex06_shakespeare_generator

* Disable the remaining `'=destroy' hook which takes a 'var T' parameter is deprecated` warning

We cannot really fix that warning because it is due to the fact that (as for 2.0.2) nim creates a var destructor when `new X, T` is called. Since we cannot fix it we simply disable it.

* 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).

* Remove `imported and not used: 'sequninit' [UnusedImport]` warning

This warning only happens with devel. The fix is to make sequninit.nim "used" when newSeqUninit is not needed.

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/ex06_shakespeare_generator.nim

@@ -19,8 +19,8 @@
 # TODO: save/reload trained weights
 
 import
-  os, random, times, strformat, algorithm, sequtils, tables,
-  ../src/arraymancer
+  std / [os, random, times, strformat, algorithm, sequtils, tables]
+import ../src/arraymancer
 
 # ################################################################
 #
@@ -56,7 +56,7 @@ const
 #
 # ################################################################
 
-proc strToTensor(str: string|TaintedString): Tensor[PrintableIdx] =
+proc strToTensor(str: string): Tensor[PrintableIdx] =
   result = newTensor[PrintableIdx](str.len)
 
   # For each x in result, map the corresponding char index
@@ -262,7 +262,15 @@ proc gen_text[T](
 
 proc main() =
   # Parse the input file
-  let filePath = paramStr(1).string
+  if paramCount() < 1:
+    echo "Please provide an input file path as an argument"
+    return
+
+  let filePath = paramStr(1)
+  if not filePath.fileExists:
+    echo "Could not find input file"
+    return
+
   let txt_raw = readFile(filePath)
 
   echo "Checking the first hundred characters of your file"

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.nim

@@ -41,6 +41,6 @@ export  tensor,
         std_version_types
 
 when not defined(no_lapack):
-  # The ml module also does not export everything is LAPACK is not available
+  # The ml module also does not export everything if LAPACK is not available
   import ./arraymancer/linear_algebra
   export linear_algebra

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/primitives/matrix_multiplication/gemm.nim

@@ -9,9 +9,6 @@ import
   ./gemm_tiling, ./gemm_utils, ./gemm_packing,
   ./gemm_ukernel_dispatch
 
-from ../../tensor/datatypes import KnownSupportsCopyMem
-
-
 when defined(i386) or defined(amd64):
   import ../../cpuinfo_x86
 

src/arraymancer/laser/primitives/matrix_multiplication/gemm_tiling.nim

@@ -318,7 +318,14 @@ proc newTiles*(
   #   - kc * nr in L1 cache µkernel
   #   - mc * kc in L2 cache Ã
   #   - kc * nc in L3 cache ~B (no L3 in Xeon Phi ¯\_(ツ)_/¯)
+
+  # The following line implictly creates a destructor which, as of nim 2.0.2,
+  # creates a "non var `=destroy`" which generates a warning
+  # We temporary disable that warning because there is nothing we can do about it
+  {.push warning[Deprecated]:off.}
   new result, deallocTiles[T]
+  {.pop.}
+
   const
     nr = ukernel.nr
     mr = ukernel.mr

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.}
@@ -77,13 +77,24 @@ when not defined(gcDestructors):
       storage.memalloc.deallocShared()
       storage.memalloc = nil
 else:
-  proc `=destroy`[T](storage: var CpuStorageObj[T]) =
-    when T is KnownSupportsCopyMem:
-      if storage.isMemOwner and not storage.memalloc.isNil:
-        storage.memalloc.deallocShared()
-        storage.memalloc = nil
-    else:
-      `=destroy`(storage.raw_buffer)
+  when (NimMajor, NimMinor, NimPatch) >= (2, 0, 0):
+    proc `=destroy`[T](storage: CpuStorageObj[T]) =
+      when T is KnownSupportsCopyMem:
+        if storage.isMemOwner and not storage.memalloc.isNil:
+          storage.memalloc.deallocShared()
+      else:
+        # The following cast removes the following warning:
+        # =destroy(storage.raw_buffer) can raise an unlisted exception: Exception
+        {.cast(raises: []).}:
+          `=destroy`(storage.raw_buffer)
+  else:
+    proc `=destroy`[T](storage: var CpuStorageObj[T]) =
+      when T is KnownSupportsCopyMem:
+        if storage.isMemOwner and not storage.memalloc.isNil:
+          storage.memalloc.deallocShared()
+          storage.memalloc = nil
+      else:
+        `=destroy`(storage.raw_buffer)
 
   proc `=copy`[T](a: var CpuStorageObj[T]; b: CpuStorageObj[T]) {.error.}
   proc `=sink`[T](a: var CpuStorageObj[T]; b: CpuStorageObj[T]) {.error.}

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