import warnings

from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding






class 		a__						(					A__					):
					A	       =							['image_processor', 'tokenizer']
					A	       =							'ChineseCLIPImageProcessor'
					A	       =							('BertTokenizer', 'BertTokenizerFast')

					def __init__(    self      :       Any,_A      :       str=None,_A      :       Union[str, Any]=None,**_A      :       Union[str, Any]    ):







							"""simple docstring"""






							SCREAMING_SNAKE_CASE_  :		Tuple				      =    None
							if "feature_extractor" in kwargs:
									warnings.warn(
									    "The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`"
									    " instead.",_A,)
									SCREAMING_SNAKE_CASE_  :		List[str]				      =    kwargs.pop("feature_extractor"    )

							SCREAMING_SNAKE_CASE_  :		Dict				      =    image_processor if image_processor is not None else feature_extractor
							if image_processor is None:
									raise ValueError("You need to specify an `image_processor`."    )
							if tokenizer is None:
									raise ValueError("You need to specify a `tokenizer`."    )

							super().__init__(_A,_A    )
							SCREAMING_SNAKE_CASE_  :		List[Any]				      =    self.image_processor

					def __call__(    self      :       Dict,_A      :       Optional[Any]=None,_A      :       str=None,_A      :       List[Any]=None,**_A      :       str    ):







							"""simple docstring"""






							if text is None and images is None:
									raise ValueError("You have to specify either text or images. Both cannot be none."    )

							if text is not None:
									SCREAMING_SNAKE_CASE_  :		List[str]				      =    self.tokenizer(_A,return_tensors=_A,**_A    )

							if images is not None:
									SCREAMING_SNAKE_CASE_  :		Optional[int]				      =    self.image_processor(_A,return_tensors=_A,**_A    )

							if text is not None and images is not None:
									SCREAMING_SNAKE_CASE_  :		int				      =    image_features.pixel_values
									return encoding
							elif text is not None:
									return encoding
							else:
									return BatchEncoding(data=dict(**_A    ),tensor_type=_A    )

					def 				__UpperCamelCase   (    self      :       Union[str, Any],*_A      :       str,**_A      :       List[Any]    ):







							"""simple docstring"""






							return self.tokenizer.batch_decode(*_A,**_A    )

					def 				__UpperCamelCase   (    self      :       str,*_A      :       str,**_A      :       int    ):







							"""simple docstring"""






							return self.tokenizer.decode(*_A,**_A    )

					@property
					def 				__UpperCamelCase   (    self      :       List[Any]    ):







							"""simple docstring"""






							SCREAMING_SNAKE_CASE_  :		Optional[int]				      =    self.tokenizer.model_input_names
							SCREAMING_SNAKE_CASE_  :		str				      =    self.image_processor.model_input_names
							return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names    )    )






					@property
					def 				__UpperCamelCase   (    self      :       str    ):







							"""simple docstring"""






							warnings.warn(
							    "`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead.",_A,)
							return self.image_processor_class

# 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       _snake_case	(   ):
		"""simple docstring"""







		SCREAMING_SNAKE_CASE_  :		int				      =    ArgumentParser("Accelerate CLI tool"   , usage="accelerate <command> [<args>]"   , allow_abbrev=lowerCAmelCase	)
		SCREAMING_SNAKE_CASE_  :		Optional[int]				      =    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
		SCREAMING_SNAKE_CASE_  :		Dict				      =    parser.parse_args()

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

		# Run
		args.func(lowerCAmelCase	)


if __name__ == "__main__":
		main()
