




import argparse
import os
import re


# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_dummies.py
UpperCamelCase__  =		"""src/transformers"""

# Matches is_xxx_available()
UpperCamelCase__  =		re.compile(r'is\_([a-z_]*)_available()')
# Matches from xxx import bla
UpperCamelCase__  =		re.compile(r'\s+from\s+\S*\s+import\s+([^\(\s].*)\n')
UpperCamelCase__  =		re.compile(r'^\s+if\s+not\s+\(?is\_[a-z_]*\_available\(\)')


UpperCamelCase__  =		"""
{0} = None
"""

UpperCamelCase__  =		"""
class {0}(metaclass=DummyObject):
    _backends = {1}

    def __init__(self, *args, **kwargs):
        requires_backends(self, {1})
"""


UpperCamelCase__  =		"""
def {0}(*args, **kwargs):
    requires_backends({0}, {1})
"""






def       snake_case      (							A    )							->							Tuple:




	'''simple docstring'''


	if _re_test_backend.search(A    ) is None:
		return None
	lowerCamelCase_							:	List[str]							     =							[b[0] for b in _re_backend.findall(A    )]
	backends.sort()
	return "_and_".join(A    )






def       snake_case      (							)							->							Optional[int]:




	'''simple docstring'''


	with open(os.path.join(A		,     '__init__.py'    )		,     'r'		,     encoding='utf-8'		,     newline='\n'    ) as f:
		lowerCamelCase_							:	Tuple							     =							f.readlines()

	# Get to the point we do the actual imports for type checking
	lowerCamelCase_							:	List[str]							     =							0
	while not lines[line_index].startswith('if TYPE_CHECKING'    ):
		line_index += 1

	lowerCamelCase_							:	Union[str, Any]							     =							{}
	# Go through the end of the file
	while line_index < len(A    ):
		# If the line is an if is_backend_available, we grab all objects associated.
		lowerCamelCase_							:	List[str]							     =							find_backend(lines[line_index]    )
		if backend is not None:
			while not lines[line_index].startswith('    else:'    ):
				line_index += 1
			line_index += 1

			lowerCamelCase_							:	Optional[int]							     =							[]
			# Until we unindent, add backend objects to the list
			while len(lines[line_index]    ) <= 1 or lines[line_index].startswith(' ' * 8    ):
				lowerCamelCase_							:	Optional[int]							     =							lines[line_index]
				lowerCamelCase_							:	Optional[Any]							     =							_re_single_line_import.search(A    )
				if single_line_import_search is not None:
					objects.extend(single_line_import_search.groups()[0].split(', '    )    )
				elif line.startswith(' ' * 12    ):
					objects.append(line[12:-2]    )
				line_index += 1

			lowerCamelCase_							:	Optional[int]							     =							objects
		else:
			line_index += 1

	return backend_specific_objects






def       snake_case      (							A		,     A    )							->							Optional[int]:




	'''simple docstring'''


	if name.isupper():
		return DUMMY_CONSTANT.format(A    )
	elif name.islower():
		return DUMMY_FUNCTION.format(A		,     A    )
	else:
		return DUMMY_CLASS.format(A		,     A    )






def       snake_case      (							A=None    )							->							Union[str, Any]:




	'''simple docstring'''


	if backend_specific_objects is None:
		lowerCamelCase_							:	str							     =							read_init()
	# For special correspondence backend to module name as used in the function requires_modulename
	lowerCamelCase_							:	Union[str, Any]							     =							{}

	for backend, objects in backend_specific_objects.items():
		lowerCamelCase_							:	Any							     =							'''[''' + ''', '''.join(f"\"{b}\"" for b in backend.split('_and_'    )    ) + ''']'''
		lowerCamelCase_							:	Any							     =							'''# This file is autogenerated by the command `make fix-copies`, do not edit.\n'''
		dummy_file += "from ..utils import DummyObject, requires_backends\n\n"
		dummy_file += "\n".join([create_dummy_object(A		,     A    ) for o in objects]    )
		lowerCamelCase_							:	Optional[Any]							     =							dummy_file

	return dummy_files






def       snake_case      (							A=False    )							->							Union[str, Any]:




	'''simple docstring'''


	lowerCamelCase_							:	int							     =							create_dummy_files()
	# For special correspondence backend to shortcut as used in utils/dummy_xxx_objects.py
	lowerCamelCase_							:	Dict							     =							{'''torch''': '''pt'''}

	# Locate actual dummy modules and read their content.
	lowerCamelCase_							:	Optional[Any]							     =							os.path.join(A		,     'utils'    )
	lowerCamelCase_							:	str							     =							{
	    backend: os.path.join(A		,     f"dummy_{short_names.get(A		,     A    )}_objects.py"    )
	    for backend in dummy_files.keys()
	}

	lowerCamelCase_							:	Dict							     =							{}
	for backend, file_path in dummy_file_paths.items():
		if os.path.isfile(A    ):
			with open(A		,     'r'		,     encoding='utf-8'		,     newline='\n'    ) as f:
				lowerCamelCase_							:	List[Any]							     =							f.read()
		else:
			lowerCamelCase_							:	Dict							     =							''''''

	for backend in dummy_files.keys():
		if dummy_files[backend] != actual_dummies[backend]:
			if overwrite:
				print(
				    f"Updating transformers.utils.dummy_{short_names.get(A		,     A    )}_objects.py as the main "
				    '__init__ has new objects.'    )
				with open(dummy_file_paths[backend]		,     'w'		,     encoding='utf-8'		,     newline='\n'    ) as f:
					f.write(dummy_files[backend]    )
			else:
				raise ValueError(
				    'The main __init__ has objects that are not present in '
				    f"transformers.utils.dummy_{short_names.get(A		,     A    )}_objects.py. Run `make fix-copies` "
				    'to fix this.'    )


if __name__ == "__main__":
							UpperCamelCase__  =		argparse.ArgumentParser()
							parser.add_argument('--fix_and_overwrite', action='store_true', help='Whether to fix inconsistencies.')
							UpperCamelCase__  =		parser.parse_args()

							check_dummies(args.fix_and_overwrite)






from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


if TYPE_CHECKING:
							from ... import FeatureExtractionMixin, PreTrainedTokenizerBase, TensorType


UpperCamelCase__  =		logging.get_logger(__name__)

UpperCamelCase__  =		{
    'microsoft/deberta-base': 'https://huggingface.co/microsoft/deberta-base/resolve/main/config.json',
    'microsoft/deberta-large': 'https://huggingface.co/microsoft/deberta-large/resolve/main/config.json',
    'microsoft/deberta-xlarge': 'https://huggingface.co/microsoft/deberta-xlarge/resolve/main/config.json',
    'microsoft/deberta-base-mnli': 'https://huggingface.co/microsoft/deberta-base-mnli/resolve/main/config.json',
    'microsoft/deberta-large-mnli': 'https://huggingface.co/microsoft/deberta-large-mnli/resolve/main/config.json',
    'microsoft/deberta-xlarge-mnli': 'https://huggingface.co/microsoft/deberta-xlarge-mnli/resolve/main/config.json',
}


class        __SCREAMING_SNAKE_CASE							(	lowerCamelCase						):
					_lowerCamelCase							=				"""deberta"""

					def __init__(       self				, __lowercase=50_265				, __lowercase=768				, __lowercase=12				, __lowercase=12				, __lowercase=3_072				, __lowercase="gelu"				, __lowercase=0.1				, __lowercase=0.1				, __lowercase=512				, __lowercase=0				, __lowercase=0.02				, __lowercase=1E-7				, __lowercase=False				, __lowercase=-1				, __lowercase=0				, __lowercase=True				, __lowercase=None				, __lowercase=0				, __lowercase="gelu"				, **__lowercase				, ):







						'''simple docstring'''




						super().__init__(**__lowercase      )

						lowerCamelCase_							:	Dict							     =							hidden_size
						lowerCamelCase_							:	Tuple							     =							num_hidden_layers
						lowerCamelCase_							:	Dict							     =							num_attention_heads
						lowerCamelCase_							:	Tuple							     =							intermediate_size
						lowerCamelCase_							:	Tuple							     =							hidden_act
						lowerCamelCase_							:	List[Any]							     =							hidden_dropout_prob
						lowerCamelCase_							:	Dict							     =							attention_probs_dropout_prob
						lowerCamelCase_							:	List[Any]							     =							max_position_embeddings
						lowerCamelCase_							:	List[Any]							     =							type_vocab_size
						lowerCamelCase_							:	Union[str, Any]							     =							initializer_range
						lowerCamelCase_							:	int							     =							relative_attention
						lowerCamelCase_							:	Tuple							     =							max_relative_positions
						lowerCamelCase_							:	Optional[Any]							     =							pad_token_id
						lowerCamelCase_							:	int							     =							position_biased_input

						# Backwards compatibility
						if type(__lowercase      ) == str:
							lowerCamelCase_							:	Tuple							     =							[x.strip() for x in pos_att_type.lower().split('|'      )]

						lowerCamelCase_							:	Any							     =							pos_att_type
						lowerCamelCase_							:	Any							     =							vocab_size
						lowerCamelCase_							:	List[str]							     =							layer_norm_eps

						lowerCamelCase_							:	str							     =							kwargs.get('pooler_hidden_size'				, __lowercase      )
						lowerCamelCase_							:	List[Any]							     =							pooler_dropout
						lowerCamelCase_							:	str							     =							pooler_hidden_act


class        __SCREAMING_SNAKE_CASE							(	lowerCamelCase						):

					@property
					def 			lowercase_							(       self      ):







						'''simple docstring'''




						if self.task == "multiple-choice":
							lowerCamelCase_							:	Tuple							     =							{0: 'batch', 1: 'choice', 2: 'sequence'}
						else:
							lowerCamelCase_							:	List[str]							     =							{0: 'batch', 1: 'sequence'}
						if self._config.type_vocab_size > 0:
							return OrderedDict(
							    [('input_ids', dynamic_axis), ('attention_mask', dynamic_axis), ('token_type_ids', dynamic_axis)]      )
						else:
							return OrderedDict([('input_ids', dynamic_axis), ('attention_mask', dynamic_axis)]      )

					@property
					def 			lowercase_							(       self      ):







						'''simple docstring'''




						return 12





					def 			lowercase_							(       self				, __lowercase				, __lowercase = -1				, __lowercase = -1				, __lowercase = -1				, __lowercase = False				, __lowercase = None				, __lowercase = 3				, __lowercase = 40				, __lowercase = 40				, __lowercase = None				, ):







						'''simple docstring'''




						lowerCamelCase_							:	Optional[Any]							     =							super().generate_dummy_inputs(preprocessor=__lowercase				, framework=__lowercase      )
						if self._config.type_vocab_size == 0 and "token_type_ids" in dummy_inputs:
							del dummy_inputs["token_type_ids"]
						return dummy_inputs
