





# 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 lowerCAmelCase__(__snake_case=None							)				->      List[str]:







	'''simple docstring'''







	if subparsers is not None:
		lowerCamelCase__								=		subparsers.add_parser('''test'''							)
	else:
		lowerCamelCase__								=		argparse.ArgumentParser('''Accelerate test command'''							)

	parser.add_argument(
	    '''--config_file'''       ,default=__snake_case       ,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=__snake_case							)
	return parser





def lowerCAmelCase__(__snake_case							)				->      Dict:







	'''simple docstring'''







	lowerCamelCase__								=		os.path.sep.join(__file__.split(os.path.sep							)[:-2] + ['''test_utils''', '''scripts''', '''test_script.py''']							)

	if args.config_file is None:
		lowerCamelCase__								=		script_name
	else:
		lowerCamelCase__								=		F'--config_file={args.config_file} {script_name}'

	lowerCamelCase__								=		['''accelerate-launch'''] + test_args.split()
	lowerCamelCase__								=		execute_subprocess_async(__snake_case       ,env=os.environ.copy()							)
	if result.returncode == 0:
		print('''Test is a success! You are ready for your distributed training!'''							)





def lowerCAmelCase__()				->      Optional[int]:







	'''simple docstring'''







	lowerCamelCase__								=		test_command_parser()
	lowerCamelCase__								=		parser.parse_args()
	test_command(__snake_case							)


if __name__ == "__main__":
			main()










from typing import List, Optional, Union

from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType






class 					__A    (    lowerCAmelCase ):

			'''simple docstring'''







			lowerCAmelCase_							     =						["""image_processor""", """tokenizer"""]
			lowerCAmelCase_							     =						"""BlipImageProcessor"""
			lowerCAmelCase_							     =						("""BertTokenizer""", """BertTokenizerFast""")





			def __init__(    self       ,  __lowerCAmelCase       ,  __lowerCAmelCase							):



				'''simple docstring'''







				lowerCamelCase__								=		False
				super().__init__(__lowerCAmelCase       ,  __lowerCAmelCase							)
				lowerCamelCase__								=		self.image_processor





			def __call__(    self       ,  __lowerCAmelCase = None       ,  __lowerCAmelCase = None       ,  __lowerCAmelCase = True       ,  __lowerCAmelCase = False       ,  __lowerCAmelCase = None       ,  __lowerCAmelCase = None       ,  __lowerCAmelCase = 0       ,  __lowerCAmelCase = None       ,  __lowerCAmelCase = None       ,  __lowerCAmelCase = False       ,  __lowerCAmelCase = False       ,  __lowerCAmelCase = False       ,  __lowerCAmelCase = False       ,  __lowerCAmelCase = False       ,  __lowerCAmelCase = True       ,  __lowerCAmelCase = None       ,  **__lowerCAmelCase       ,  ):



				'''simple docstring'''







				if images is None and text is None:
					raise ValueError('''You have to specify either images or text.'''							)

				# Get only text
				if images is None:
					lowerCamelCase__								=		self.tokenizer
					lowerCamelCase__								=		self.tokenizer(
					    text=__lowerCAmelCase       ,  add_special_tokens=__lowerCAmelCase       ,  padding=__lowerCAmelCase       ,  truncation=__lowerCAmelCase       ,  max_length=__lowerCAmelCase       ,  stride=__lowerCAmelCase       ,  pad_to_multiple_of=__lowerCAmelCase       ,  return_attention_mask=__lowerCAmelCase       ,  return_overflowing_tokens=__lowerCAmelCase       ,  return_special_tokens_mask=__lowerCAmelCase       ,  return_offsets_mapping=__lowerCAmelCase       ,  return_token_type_ids=__lowerCAmelCase       ,  return_length=__lowerCAmelCase       ,  verbose=__lowerCAmelCase       ,  return_tensors=__lowerCAmelCase       ,  **__lowerCAmelCase       ,  )
					return text_encoding

				# add pixel_values
				lowerCamelCase__								=		self.image_processor(__lowerCAmelCase       ,  return_tensors=__lowerCAmelCase							)

				if text is not None:
					lowerCamelCase__								=		self.tokenizer(
					    text=__lowerCAmelCase       ,  add_special_tokens=__lowerCAmelCase       ,  padding=__lowerCAmelCase       ,  truncation=__lowerCAmelCase       ,  max_length=__lowerCAmelCase       ,  stride=__lowerCAmelCase       ,  pad_to_multiple_of=__lowerCAmelCase       ,  return_attention_mask=__lowerCAmelCase       ,  return_overflowing_tokens=__lowerCAmelCase       ,  return_special_tokens_mask=__lowerCAmelCase       ,  return_offsets_mapping=__lowerCAmelCase       ,  return_token_type_ids=__lowerCAmelCase       ,  return_length=__lowerCAmelCase       ,  verbose=__lowerCAmelCase       ,  return_tensors=__lowerCAmelCase       ,  **__lowerCAmelCase       ,  )
				else:
					lowerCamelCase__								=		None

				if text_encoding is not None:
					encoding_image_processor.update(__lowerCAmelCase							)

				return encoding_image_processor





			def 		__lowerCamelCase				(    self       ,  *__lowerCAmelCase       ,  **__lowerCAmelCase							):



				'''simple docstring'''







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





			def 		__lowerCamelCase				(    self       ,  *__lowerCAmelCase       ,  **__lowerCAmelCase							):



				'''simple docstring'''







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





			@property
			def 		__lowerCamelCase				(    self							):



				'''simple docstring'''







				lowerCamelCase__								=		self.tokenizer.model_input_names
				lowerCamelCase__								=		self.image_processor.model_input_names
				return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names							)							)



