from typing import Dict, List, Optional, Union

import numpy as np

from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import convert_to_rgb, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
    OPENAI_CLIP_MEAN,
    OPENAI_CLIP_STD,
    ChannelDimension,
    ImageInput,
    PILImageResampling,
    make_list_of_images,
    to_numpy_array,
    valid_images,
)
from ...utils import TensorType, is_vision_available, logging


if is_vision_available():
       import PIL


__lowerCAmelCase					: Union[str, Any]        =logging.get_logger(__name__)





class 				_A		( lowerCAmelCase			):
      snake_case__    :     Optional[Any]													=			['pixel_values']

      def __init__(		self	, __lowerCAmelCase = True	, __lowerCAmelCase = None	, __lowerCAmelCase = PILImageResampling.BICUBIC	, __lowerCAmelCase = True	, __lowerCAmelCase = 1 / 255	, __lowerCAmelCase = True	, __lowerCAmelCase = None	, __lowerCAmelCase = None	, __lowerCAmelCase = True	, **__lowerCAmelCase	, ):







            """simple docstring"""



            super().__init__(**__lowerCAmelCase		)
            lowercase														=			size if size is not None else {"""height""": 384, """width""": 384}
            lowercase														=			get_size_dict(__lowerCAmelCase	, default_to_square=__lowerCAmelCase		)

            lowercase														=			do_resize
            lowercase														=			size
            lowercase														=			resample
            lowercase														=			do_rescale
            lowercase														=			rescale_factor
            lowercase														=			do_normalize
            lowercase														=			image_mean if image_mean is not None else OPENAI_CLIP_MEAN
            lowercase														=			image_std if image_std is not None else OPENAI_CLIP_STD
            lowercase														=			do_convert_rgb

      def        A__ (		self	, __lowerCAmelCase	, __lowerCAmelCase	, __lowerCAmelCase = PILImageResampling.BICUBIC	, __lowerCAmelCase = None	, **__lowerCAmelCase	, ):







            """simple docstring"""



            lowercase														=			get_size_dict(__lowerCAmelCase	, default_to_square=__lowerCAmelCase		)
            if "height" not in size or "width" not in size:
                  raise ValueError(f'The `size` dictionary must contain the keys `height` and `width`. Got {size.keys()}'		)
            lowercase														=			(size["""height"""], size["""width"""])
            return resize(__lowerCAmelCase	, size=__lowerCAmelCase	, resample=__lowerCAmelCase	, data_format=__lowerCAmelCase	, **__lowerCAmelCase		)

      def        A__ (		self	, __lowerCAmelCase	, __lowerCAmelCase	, __lowerCAmelCase = None	, **__lowerCAmelCase	, ):







            """simple docstring"""



            return rescale(__lowerCAmelCase	, scale=__lowerCAmelCase	, data_format=__lowerCAmelCase	, **__lowerCAmelCase		)

      def        A__ (		self	, __lowerCAmelCase	, __lowerCAmelCase	, __lowerCAmelCase	, __lowerCAmelCase = None	, **__lowerCAmelCase	, ):







            """simple docstring"""



            return normalize(__lowerCAmelCase	, mean=__lowerCAmelCase	, std=__lowerCAmelCase	, data_format=__lowerCAmelCase	, **__lowerCAmelCase		)







      def        A__ (		self	, __lowerCAmelCase	, __lowerCAmelCase = None	, __lowerCAmelCase = None	, __lowerCAmelCase = None	, __lowerCAmelCase = None	, __lowerCAmelCase = None	, __lowerCAmelCase = None	, __lowerCAmelCase = None	, __lowerCAmelCase = None	, __lowerCAmelCase = None	, __lowerCAmelCase = None	, __lowerCAmelCase = ChannelDimension.FIRST	, **__lowerCAmelCase	, ):







            """simple docstring"""



            lowercase														=			do_resize if do_resize is not None else self.do_resize
            lowercase														=			resample if resample is not None else self.resample
            lowercase														=			do_rescale if do_rescale is not None else self.do_rescale
            lowercase														=			rescale_factor if rescale_factor is not None else self.rescale_factor
            lowercase														=			do_normalize if do_normalize is not None else self.do_normalize
            lowercase														=			image_mean if image_mean is not None else self.image_mean
            lowercase														=			image_std if image_std is not None else self.image_std
            lowercase														=			do_convert_rgb if do_convert_rgb is not None else self.do_convert_rgb

            lowercase														=			size if size is not None else self.size
            lowercase														=			get_size_dict(__lowerCAmelCase	, default_to_square=__lowerCAmelCase		)

            lowercase														=			make_list_of_images(__lowerCAmelCase		)

            if not valid_images(__lowerCAmelCase		):
                  raise ValueError(
                      """Invalid image type. Must be of type PIL.Image.Image, numpy.ndarray, """
                      """torch.Tensor, tf.Tensor or jax.ndarray."""		)

            if do_resize and size is None or resample is None:
                  raise ValueError("""Size and resample must be specified if do_resize is True."""		)

            if do_rescale and rescale_factor is None:
                  raise ValueError("""Rescale factor must be specified if do_rescale is True."""		)

            if do_normalize and (image_mean is None or image_std is None):
                  raise ValueError("""Image mean and std must be specified if do_normalize is True."""		)

            # PIL RGBA images are converted to RGB
            if do_convert_rgb:
                  lowercase														=			[convert_to_rgb(__lowerCAmelCase		) for image in images]

            # All transformations expect numpy arrays.
            lowercase														=			[to_numpy_array(__lowerCAmelCase		) for image in images]

            if do_resize:
                  lowercase														=			[self.resize(image=__lowerCAmelCase	, size=__lowerCAmelCase	, resample=__lowerCAmelCase		) for image in images]

            if do_rescale:
                  lowercase														=			[self.rescale(image=__lowerCAmelCase	, scale=__lowerCAmelCase		) for image in images]

            if do_normalize:
                  lowercase														=			[self.normalize(image=__lowerCAmelCase	, mean=__lowerCAmelCase	, std=__lowerCAmelCase		) for image in images]

            lowercase														=			[to_channel_dimension_format(__lowerCAmelCase	, __lowerCAmelCase		) for image in images]

            lowercase														=			BatchFeature(data={"""pixel_values""": images}	, tensor_type=__lowerCAmelCase		)

            return encoded_outputs




"""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.

from argparse import ArgumentParser

from accelerate.commands.config import get_config_parser
from accelerate.commands.env import env_command_parser
from accelerate.commands.launch import launch_command_parser
from accelerate.commands.test import test_command_parser
from accelerate.commands.tpu import tpu_command_parser


def     UpperCAmelCase__ (       )				->					Tuple:
      '''simple docstring'''


      lowercase														=			ArgumentParser("""Accelerate CLI tool"""      ,	usage="""accelerate <command> [<args>]"""      ,	allow_abbrev=lowerCAmelCase__	)
      lowercase														=			parser.add_subparsers(help="""accelerate command helpers"""	)

      # Register commands
      get_config_parser(subparsers=lowerCAmelCase__	)
      env_command_parser(subparsers=lowerCAmelCase__	)
      launch_command_parser(subparsers=lowerCAmelCase__	)
      tpu_command_parser(subparsers=lowerCAmelCase__	)
      test_command_parser(subparsers=lowerCAmelCase__	)

      # Let's go
      lowercase														=			parser.parse_args()

      if not hasattr(lowerCAmelCase__      ,	"""func"""	):
            parser.print_help()
            exit(1	)

      # Run
      args.func(lowerCAmelCase__	)


if __name__ == "__main__":
       main()



