


'''simple docstring'''






# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import argparse
import os

from accelerate.test_utils import execute_subprocess_async







def     UpperCamelCase_      (   A__ :       str=None ):
  '''simple docstring'''





  if subparsers is not None:
    lowerCAmelCase_      :				Tuple      =       subparsers.add_parser("""test""" )
  else:
    lowerCAmelCase_      :				List[str]      =       argparse.ArgumentParser("""Accelerate test command""" )

  parser.add_argument(
      """--config_file"""							,   default=A__							,   help=(
          """The path to use to store the config file. Will default to a file named default_config.yaml in the cache """
          """location, which is the content of the environment `HF_HOME` suffixed with 'accelerate', or if you don't have """
          """such an environment variable, your cache directory ('~/.cache' or the content of `XDG_CACHE_HOME`) suffixed """
          """with 'huggingface'."""
      )							,   )

  if subparsers is not None:
    parser.set_defaults(func=A__ )
  return parser







def     UpperCamelCase_      (   A__ :       Any ):
  '''simple docstring'''





  lowerCAmelCase_      :				List[Any]      =       os.path.sep.join(__file__.split(os.path.sep )[:-2] + ["""test_utils""", """scripts""", """test_script.py"""] )

  if args.config_file is None:
    lowerCAmelCase_      :				int      =       script_name
  else:
    lowerCAmelCase_      :				Union[str, Any]      =       f'--config_file={args.config_file} {script_name}'

  lowerCAmelCase_      :				Optional[int]      =       ["""accelerate-launch"""] + test_args.split()
  lowerCAmelCase_      :				List[str]      =       execute_subprocess_async(A__							,   env=os.environ.copy() )
  if result.returncode == 0:
    print("""Test is a success! You are ready for your distributed training!""" )







def     UpperCamelCase_      (   ):
  '''simple docstring'''





  lowerCAmelCase_      :				Tuple      =       test_command_parser()
  lowerCAmelCase_      :				str      =       parser.parse_args()
  test_command(A__ )


if __name__ == "__main__":
  main()







'''simple docstring'''






from pathlib import Path

import cva
import numpy as np
from matplotlib import pyplot as plt







def     UpperCamelCase_      (   A__ :       np.ndarray							,   A__ :       np.ndarray							,   A__ :       np.ndarray							,   A__ :       int							,   A__ :       int ):
  '''simple docstring'''





  lowerCAmelCase_      :				List[Any]      =       cva.getAffineTransform(A__							,   A__ )
  return cva.warpAffine(A__							,   A__							,   (rows, cols) )


if __name__ == "__main__":
  # read original image
  __A :  Dict    							=				cva.imread(
      str(Path(__file__).resolve().parent.parent / "image_data" / "lena.jpg")
  )
  # turn image in gray scale value
  __A :  List[Any]    							=				cva.cvtColor(image, cva.COLOR_BGR2GRAY)
  # get image shape
  __A							,			__A :  Dict    							=				gray_img.shape

  # set different points to rotate image
  __A :  List[str]    							=				np.array([[50, 50], [200, 50], [50, 200]], np.floataa)
  __A :  Tuple    							=				np.array([[10, 100], [200, 50], [100, 250]], np.floataa)
  __A :  List[Any]    							=				np.array([[50, 50], [150, 50], [120, 200]], np.floataa)
  __A :  Optional[Any]    							=				np.array([[10, 100], [80, 50], [180, 250]], np.floataa)

  # add all rotated images in a list
  __A :  Optional[Any]    							=				[
      gray_img,
      get_rotation(gray_img, ptsa, ptsa, img_rows, img_cols),
      get_rotation(gray_img, ptsa, ptsa, img_rows, img_cols),
      get_rotation(gray_img, ptsa, ptsa, img_rows, img_cols),
  ]

  # plot different image rotations
  __A :  Dict    							=				plt.figure(1)
  __A :  Optional[Any]    							=				["Original", "Rotation 1", "Rotation 2", "Rotation 3"]
  for i, image in enumerate(images):
    plt.subplot(2, 2, i + 1), plt.imshow(image, "gray")
    plt.title(titles[i])
    plt.axis("off")
    plt.subplots_adjust(left=0.0, bottom=0.0_5, right=1.0, top=0.9_5)
  plt.show()



