"""simple docstring"""






import unittest

from transformers import BigBirdConfig, is_flax_available
from transformers.testing_utils import require_flax, slow

from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask


if is_flax_available():
						import jax

						from transformers.models.big_bird.modeling_flax_big_bird import (
						    FlaxBigBirdForCausalLM,
						    FlaxBigBirdForMaskedLM,
						    FlaxBigBirdForMultipleChoice,
						    FlaxBigBirdForPreTraining,
						    FlaxBigBirdForQuestionAnswering,
						    FlaxBigBirdForSequenceClassification,
						    FlaxBigBirdForTokenClassification,
						    FlaxBigBirdModel,
						)

class lowerCamelCase		(unittest.TestCase      ):






					'''simple docstring'''


					def __init__(						self			:				Union[str, Any]   , _snake_case			:				List[str]   , _snake_case			:				str=2   , _snake_case			:				Any=56   , _snake_case			:				str=True   , _snake_case			:				int=True   , _snake_case			:				int=True   , _snake_case			:				Any=True   , _snake_case			:				Optional[Any]=99   , _snake_case			:				Union[str, Any]=32   , _snake_case			:				Tuple=2   , _snake_case			:				Optional[Any]=2   , _snake_case			:				Union[str, Any]=7   , _snake_case			:				Any="gelu_new"   , _snake_case			:				List[Any]=0.1   , _snake_case			:				int=0.1   , _snake_case			:				Dict=512   , _snake_case			:				Dict=16   , _snake_case			:				Optional[Any]=2   , _snake_case			:				int=0.02   , _snake_case			:				Optional[int]=4   , _snake_case			:				List[Any]="block_sparse"   , _snake_case			:				Optional[int]=True   , _snake_case			:				Any=False   , _snake_case			:				Optional[Any]=2   , _snake_case			:				Any=3   , )							->       Optional[Any]:
									SCREAMING_SNAKE_CASE__		  =				parent
									SCREAMING_SNAKE_CASE__		  =				batch_size
									SCREAMING_SNAKE_CASE__		  =				seq_length
									SCREAMING_SNAKE_CASE__		  =				is_training
									SCREAMING_SNAKE_CASE__		  =				use_attention_mask
									SCREAMING_SNAKE_CASE__		  =				use_token_type_ids
									SCREAMING_SNAKE_CASE__		  =				use_labels
									SCREAMING_SNAKE_CASE__		  =				vocab_size
									SCREAMING_SNAKE_CASE__		  =				hidden_size
									SCREAMING_SNAKE_CASE__		  =				num_hidden_layers
									SCREAMING_SNAKE_CASE__		  =				num_attention_heads
									SCREAMING_SNAKE_CASE__		  =				intermediate_size
									SCREAMING_SNAKE_CASE__		  =				hidden_act
									SCREAMING_SNAKE_CASE__		  =				hidden_dropout_prob
									SCREAMING_SNAKE_CASE__		  =				attention_probs_dropout_prob
									SCREAMING_SNAKE_CASE__		  =				max_position_embeddings
									SCREAMING_SNAKE_CASE__		  =				type_vocab_size
									SCREAMING_SNAKE_CASE__		  =				type_sequence_label_size
									SCREAMING_SNAKE_CASE__		  =				initializer_range
									SCREAMING_SNAKE_CASE__		  =				num_choices

									SCREAMING_SNAKE_CASE__		  =				rescale_embeddings
									SCREAMING_SNAKE_CASE__		  =				attention_type
									SCREAMING_SNAKE_CASE__		  =				use_bias
									SCREAMING_SNAKE_CASE__		  =				block_size
									SCREAMING_SNAKE_CASE__		  =				num_random_blocks



					def 			lowerCAmelCase_					(						self			:				Dict		)							->       Tuple:
									SCREAMING_SNAKE_CASE__		  =				ids_tensor([self.batch_size, self.seq_length]   , self.vocab_size		)

									SCREAMING_SNAKE_CASE__		  =				None
									if self.use_attention_mask:
													SCREAMING_SNAKE_CASE__		  =				random_attention_mask([self.batch_size, self.seq_length]		)

									SCREAMING_SNAKE_CASE__		  =				None
									if self.use_token_type_ids:
													SCREAMING_SNAKE_CASE__		  =				ids_tensor([self.batch_size, self.seq_length]   , self.type_vocab_size		)

									SCREAMING_SNAKE_CASE__		  =				BigBirdConfig(
									    vocab_size=self.vocab_size   , hidden_size=self.hidden_size   , num_hidden_layers=self.num_hidden_layers   , num_attention_heads=self.num_attention_heads   , intermediate_size=self.intermediate_size   , hidden_act=self.hidden_act   , hidden_dropout_prob=self.hidden_dropout_prob   , attention_probs_dropout_prob=self.attention_probs_dropout_prob   , max_position_embeddings=self.max_position_embeddings   , type_vocab_size=self.type_vocab_size   , is_decoder=_snake_case   , initializer_range=self.initializer_range   , attention_type=self.attention_type   , block_size=self.block_size   , num_random_blocks=self.num_random_blocks   , use_bias=self.use_bias   , rescale_embeddings=self.rescale_embeddings   , )

									return config, input_ids, token_type_ids, attention_mask



					def 			lowerCAmelCase_					(						self			:				Tuple		)							->       List[Any]:
									SCREAMING_SNAKE_CASE__		  =				self.prepare_config_and_inputs()
									SCREAMING_SNAKE_CASE__  ,       SCREAMING_SNAKE_CASE__  ,       SCREAMING_SNAKE_CASE__  ,       SCREAMING_SNAKE_CASE__		  =				config_and_inputs
									SCREAMING_SNAKE_CASE__		  =				{
									    "input_ids": input_ids,
									    "token_type_ids": token_type_ids,
									    "attention_mask": attention_mask,
									}
									return config, inputs_dict



@require_flax
class lowerCamelCase		(_SCREAMING_SNAKE_CASE    ,    unittest.TestCase      ):






					'''simple docstring'''


					a   	=		(
					    (
					        FlaxBigBirdForCausalLM,
					        FlaxBigBirdModel,
					        FlaxBigBirdForPreTraining,
					        FlaxBigBirdForMaskedLM,
					        FlaxBigBirdForMultipleChoice,
					        FlaxBigBirdForQuestionAnswering,
					        FlaxBigBirdForSequenceClassification,
					        FlaxBigBirdForTokenClassification,
					    )
					    if is_flax_available()
					    else ()
					)

					a   	=		False
					a   	=		False



					def 			lowerCAmelCase_					(						self			:				List[Any]		)							->       Any:
									SCREAMING_SNAKE_CASE__		  =				FlaxBigBirdModelTester(self		)



					@slow
					# copied from `test_modeling_flax_common` because it takes much longer than other models
					def 			lowerCAmelCase_					(						self			:				Tuple		)							->       Union[str, Any]:
									super().test_from_pretrained_save_pretrained()



					@slow
					# copied from `test_modeling_flax_common` because it takes much longer than other models
					def 			lowerCAmelCase_					(						self			:				Tuple		)							->       Union[str, Any]:
									super().test_from_pretrained_with_no_automatic_init()



					@slow
					# copied from `test_modeling_flax_common` because it takes much longer than other models
					def 			lowerCAmelCase_					(						self			:				Dict		)							->       List[Any]:
									super().test_no_automatic_init()



					@slow
					# copied from `test_modeling_flax_common` because it takes much longer than other models
					def 			lowerCAmelCase_					(						self			:				Optional[Any]		)							->       List[str]:
									super().test_hidden_states_output()



					@slow
					def 			lowerCAmelCase_					(						self			:				List[str]		)							->       Any:
									for model_class_name in self.all_model_classes:
													SCREAMING_SNAKE_CASE__		  =				model_class_name.from_pretrained("google/bigbird-roberta-base"		)
													self.assertIsNotNone(_snake_case		)



					def 			lowerCAmelCase_					(						self			:				int		)							->       Any:
									if self.test_attn_probs:
													super().test_attention_outputs()



					@slow
					# copied from `test_modeling_flax_common` because it takes much longer than other models
					def 			lowerCAmelCase_					(						self			:				Optional[int]		)							->       Union[str, Any]:
									SCREAMING_SNAKE_CASE__  ,       SCREAMING_SNAKE_CASE__		  =				self.model_tester.prepare_config_and_inputs_for_common()

									for model_class in self.all_model_classes:
													with self.subTest(model_class.__name__		):
																	SCREAMING_SNAKE_CASE__		  =				self._prepare_for_class(_snake_case   , _snake_case		)
																	SCREAMING_SNAKE_CASE__		  =				model_class(_snake_case		)

																	@jax.jit
																	def model_jitted(_snake_case			:				List[Any]   , _snake_case			:				Optional[int]=None   , **_snake_case			:				Tuple		):
																					return model(input_ids=_snake_case   , attention_mask=_snake_case   , **_snake_case		)

																	with self.subTest("JIT Enabled"		):
																					SCREAMING_SNAKE_CASE__		  =				model_jitted(**_snake_case		).to_tuple()

																	with self.subTest("JIT Disabled"		):
																					with jax.disable_jit():
																									SCREAMING_SNAKE_CASE__		  =				model_jitted(**_snake_case		).to_tuple()

																	self.assertEqual(len(_snake_case		)   , len(_snake_case		)		)
																	for jitted_output, output in zip(_snake_case   , _snake_case		):
																					self.assertEqual(jitted_output.shape   , output.shape		)



					def 			lowerCAmelCase_					(						self			:				Union[str, Any]   , _snake_case			:				Optional[Any]   , _snake_case			:				Dict   , _snake_case			:				Optional[Any]   , _snake_case			:				Union[str, Any]=1e-5   , _snake_case			:				Optional[Any]="outputs"   , _snake_case			:				List[Any]=None		)							->       Optional[int]:
									# `bigbird_block_sparse_attention` in `FlaxBigBird` returns `attention_probs = None`, while in PyTorch version,
									# an effort was done to return `attention_probs` (yet to be verified).
									if name.startswith("outputs.attentions"		):
													return
									else:
													super().check_pt_flax_outputs(_snake_case   , _snake_case   , _snake_case   , _snake_case   , _snake_case   , _snake_case		)





"""simple docstring"""






import collections
import os
import re
from pathlib import Path


_A   					=    'src/transformers'


# Matches is_xxx_available()
_A   					=    re.compile(R'is\_([a-z_]*)_available()')
# Catches a one-line _import_struct = {xxx}
_A   					=    re.compile(R'^_import_structure\s+=\s+\{([^\}]+)\}')
# Catches a line with a key-values pattern: "bla": ["foo", "bar"]
_A   					=    re.compile(R'\s+"\S*":\s+\[([^\]]*)\]')
# Catches a line if not is_foo_available
_A   					=    re.compile(R'^\s*if\s+not\s+is\_[a-z_]*\_available\(\)')
# Catches a line _import_struct["bla"].append("foo")
_A   					=    re.compile(R'^\s*_import_structure\["\S*"\]\.append\("(\S*)"\)')
# Catches a line _import_struct["bla"].extend(["foo", "bar"]) or _import_struct["bla"] = ["foo", "bar"]
_A   					=    re.compile(R'^\s*_import_structure\[\S*\](?:\.extend\(|\s*=\s+)\[([^\]]*)\]')
# Catches a line with an object between quotes and a comma:     "MyModel",
_A   					=    re.compile(R'^\s+"([^"]+)",')
# Catches a line with objects between brackets only:    ["foo", "bar"],
_A   					=    re.compile(R'^\s+\[([^\]]+)\]')
# Catches a line with from foo import bar, bla, boo
_A   					=    re.compile(R'\s+from\s+\S*\s+import\s+([^\(\s].*)\n')
# Catches a line with try:
_A   					=    re.compile(R'^\s*try:')
# Catches a line with else:
_A   					=    re.compile(R'^\s*else:')




def 						SCREAMING_SNAKE_CASE					(  __UpperCAmelCase       )							->   List[str]:
				if _re_test_backend.search(__UpperCAmelCase       ) is None:
								return None
				SCREAMING_SNAKE_CASE__		  =				[b[0] for b in _re_backend.findall(__UpperCAmelCase       )]
				backends.sort()
				return "_and_".join(__UpperCAmelCase       )




def 						SCREAMING_SNAKE_CASE					(  __UpperCAmelCase       )							->   Optional[Any]:
				with open(__UpperCAmelCase  ,					"r"  ,					encoding="utf-8"  ,					newline="\n"       ) as f:
								SCREAMING_SNAKE_CASE__		  =				f.readlines()

				SCREAMING_SNAKE_CASE__		  =				0
				while line_index < len(__UpperCAmelCase       ) and not lines[line_index].startswith("_import_structure = {"       ):
								line_index += 1

				# If this is a traditional init, just return.
				if line_index >= len(__UpperCAmelCase       ):
								return None

				# First grab the objects without a specific backend in _import_structure
				SCREAMING_SNAKE_CASE__		  =				[]
				while not lines[line_index].startswith("if TYPE_CHECKING"       ) and find_backend(lines[line_index]       ) is None:
								SCREAMING_SNAKE_CASE__		  =				lines[line_index]
								# If we have everything on a single line, let's deal with it.
								if _re_one_line_import_struct.search(__UpperCAmelCase       ):
												SCREAMING_SNAKE_CASE__		  =				_re_one_line_import_struct.search(__UpperCAmelCase       ).groups()[0]
												SCREAMING_SNAKE_CASE__		  =				re.findall(R"\[([^\]]+)\]"  ,					__UpperCAmelCase       )
												for imp in imports:
																objects.extend([obj[1:-1] for obj in imp.split(", "       )]       )
												line_index += 1
												continue
								SCREAMING_SNAKE_CASE__		  =				_re_import_struct_key_value.search(__UpperCAmelCase       )
								if single_line_import_search is not None:
												SCREAMING_SNAKE_CASE__		  =				[obj[1:-1] for obj in single_line_import_search.groups()[0].split(", "       ) if len(__UpperCAmelCase       ) > 0]
												objects.extend(__UpperCAmelCase       )
								elif line.startswith(" " * 8 + "\""       ):
												objects.append(line[9:-3]       )
								line_index += 1

				SCREAMING_SNAKE_CASE__		  =				{"none": objects}
				# Let's continue with backend-specific objects in _import_structure
				while not lines[line_index].startswith("if TYPE_CHECKING"       ):
								# If the line is an if not is_backend_available, we grab all objects associated.
								SCREAMING_SNAKE_CASE__		  =				find_backend(lines[line_index]       )
								# Check if the backend declaration is inside a try block:
								if _re_try.search(lines[line_index - 1]       ) is None:
												SCREAMING_SNAKE_CASE__		  =				None

								if backend is not None:
												line_index += 1

												# Scroll until we hit the else block of try-except-else
												while _re_else.search(lines[line_index]       ) is None:
																line_index += 1

												line_index += 1

												SCREAMING_SNAKE_CASE__		  =				[]
												# Until we unindent, add backend objects to the list
												while len(lines[line_index]       ) <= 1 or lines[line_index].startswith(" " * 4       ):
																SCREAMING_SNAKE_CASE__		  =				lines[line_index]
																if _re_import_struct_add_one.search(__UpperCAmelCase       ) is not None:
																				objects.append(_re_import_struct_add_one.search(__UpperCAmelCase       ).groups()[0]       )
																elif _re_import_struct_add_many.search(__UpperCAmelCase       ) is not None:
																				SCREAMING_SNAKE_CASE__		  =				_re_import_struct_add_many.search(__UpperCAmelCase       ).groups()[0].split(", "       )
																				SCREAMING_SNAKE_CASE__		  =				[obj[1:-1] for obj in imports if len(__UpperCAmelCase       ) > 0]
																				objects.extend(__UpperCAmelCase       )
																elif _re_between_brackets.search(__UpperCAmelCase       ) is not None:
																				SCREAMING_SNAKE_CASE__		  =				_re_between_brackets.search(__UpperCAmelCase       ).groups()[0].split(", "       )
																				SCREAMING_SNAKE_CASE__		  =				[obj[1:-1] for obj in imports if len(__UpperCAmelCase       ) > 0]
																				objects.extend(__UpperCAmelCase       )
																elif _re_quote_object.search(__UpperCAmelCase       ) is not None:
																				objects.append(_re_quote_object.search(__UpperCAmelCase       ).groups()[0]       )
																elif line.startswith(" " * 8 + "\""       ):
																				objects.append(line[9:-3]       )
																elif line.startswith(" " * 12 + "\""       ):
																				objects.append(line[13:-3]       )
																line_index += 1

												SCREAMING_SNAKE_CASE__		  =				objects
								else:
												line_index += 1

    # At this stage we are in the TYPE_CHECKING part, first grab the objects without a specific backend
				SCREAMING_SNAKE_CASE__		  =				[]
				while (
				    line_index < len(__UpperCAmelCase       )
				    and find_backend(lines[line_index]       ) is None
				    and not lines[line_index].startswith("else"       )
				):
								SCREAMING_SNAKE_CASE__		  =				lines[line_index]
								SCREAMING_SNAKE_CASE__		  =				_re_import.search(__UpperCAmelCase       )
								if single_line_import_search is not None:
												objects.extend(single_line_import_search.groups()[0].split(", "       )       )
								elif line.startswith(" " * 8       ):
												objects.append(line[8:-2]       )
								line_index += 1

				SCREAMING_SNAKE_CASE__		  =				{"none": objects}
				# Let's continue with backend-specific objects
				while line_index < len(__UpperCAmelCase       ):
								# If the line is an if is_backend_available, we grab all objects associated.
								SCREAMING_SNAKE_CASE__		  =				find_backend(lines[line_index]       )
								# Check if the backend declaration is inside a try block:
								if _re_try.search(lines[line_index - 1]       ) is None:
												SCREAMING_SNAKE_CASE__		  =				None

								if backend is not None:
												line_index += 1

												# Scroll until we hit the else block of try-except-else
												while _re_else.search(lines[line_index]       ) is None:
																line_index += 1

												line_index += 1

												SCREAMING_SNAKE_CASE__		  =				[]
												# Until we unindent, add backend objects to the list
												while len(lines[line_index]       ) <= 1 or lines[line_index].startswith(" " * 8       ):
																SCREAMING_SNAKE_CASE__		  =				lines[line_index]
																SCREAMING_SNAKE_CASE__		  =				_re_import.search(__UpperCAmelCase       )
																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

												SCREAMING_SNAKE_CASE__		  =				objects
								else:
												line_index += 1

				return import_dict_objects, type_hint_objects




def 						SCREAMING_SNAKE_CASE					(  __UpperCAmelCase  ,					__UpperCAmelCase       )							->   Any:

				def find_duplicates(__UpperCAmelCase       ):
								return [k for k, v in collections.Counter(__UpperCAmelCase       ).items() if v > 1]

				if list(import_dict_objects.keys()       ) != list(type_hint_objects.keys()       ):
								return ["Both sides of the init do not have the same backends!"]

				SCREAMING_SNAKE_CASE__		  =				[]
				for key in import_dict_objects.keys():
								SCREAMING_SNAKE_CASE__		  =				find_duplicates(import_dict_objects[key]       )
								if duplicate_imports:
												errors.append(F"""Duplicate _import_structure definitions for: {duplicate_imports}"""       )
								SCREAMING_SNAKE_CASE__		  =				find_duplicates(type_hint_objects[key]       )
								if duplicate_type_hints:
												errors.append(F"""Duplicate TYPE_CHECKING objects for: {duplicate_type_hints}"""       )

								if sorted(set(import_dict_objects[key]       )       ) != sorted(set(type_hint_objects[key]       )       ):
												SCREAMING_SNAKE_CASE__		  =				"base imports" if key == "none" else F"""{key} backend"""
												errors.append(F"""Differences for {name}:"""       )
												for a in type_hint_objects[key]:
																if a not in import_dict_objects[key]:
																				errors.append(F"""  {a} in TYPE_HINT but not in _import_structure."""       )
												for a in import_dict_objects[key]:
																if a not in type_hint_objects[key]:
																				errors.append(F"""  {a} in _import_structure but not in TYPE_HINT."""       )
				return errors




def 						SCREAMING_SNAKE_CASE					(  )							->   List[Any]:
				SCREAMING_SNAKE_CASE__		  =				[]
				for root, _, files in os.walk(__UpperCAmelCase       ):
								if "__init__.py" in files:
												SCREAMING_SNAKE_CASE__		  =				os.path.join(__UpperCAmelCase  ,					"__init__.py"       )
												SCREAMING_SNAKE_CASE__		  =				parse_init(__UpperCAmelCase       )
												if objects is not None:
																SCREAMING_SNAKE_CASE__		  =				analyze_results(*__UpperCAmelCase       )
																if len(__UpperCAmelCase       ) > 0:
																				SCREAMING_SNAKE_CASE__		  =				F"""Problem in {fname}, both halves do not define the same objects.\n{errors[0]}"""
																				failures.append("\n".join(__UpperCAmelCase       )       )
				if len(__UpperCAmelCase       ) > 0:
								raise ValueError("\n\n".join(__UpperCAmelCase       )       )




def 						SCREAMING_SNAKE_CASE					(  )							->   Optional[Any]:
				SCREAMING_SNAKE_CASE__		  =				[]
				for path, directories, files in os.walk(__UpperCAmelCase       ):
								for folder in directories:
												# Ignore private modules
												if folder.startswith("_"       ):
																directories.remove(__UpperCAmelCase       )
																continue
												# Ignore leftovers from branches (empty folders apart from pycache)
												if len(list((Path(__UpperCAmelCase       ) / folder).glob("*.py"       )       )       ) == 0:
																continue
												SCREAMING_SNAKE_CASE__		  =				str((Path(__UpperCAmelCase       ) / folder).relative_to(__UpperCAmelCase       )       )
												SCREAMING_SNAKE_CASE__		  =				short_path.replace(os.path.sep  ,					"."       )
												submodules.append(__UpperCAmelCase       )
								for fname in files:
												if fname == "__init__.py":
																continue
												SCREAMING_SNAKE_CASE__		  =				str((Path(__UpperCAmelCase       ) / fname).relative_to(__UpperCAmelCase       )       )
												SCREAMING_SNAKE_CASE__		  =				short_path.replace(".py"  ,					""       ).replace(os.path.sep  ,					"."       )
												if len(submodule.split("."       )       ) == 1:
																submodules.append(__UpperCAmelCase       )
				return submodules


_A   					=    [
    'convert_pytorch_checkpoint_to_tf2',
    'modeling_flax_pytorch_utils',
    'models.esm.openfold_utils',
]




def 						SCREAMING_SNAKE_CASE					(  )							->   Union[str, Any]:
				# This is to make sure the transformers module imported is the one in the repo.
				from transformers.utils import direct_transformers_import

				SCREAMING_SNAKE_CASE__		  =				direct_transformers_import(__UpperCAmelCase       )

				SCREAMING_SNAKE_CASE__		  =				set(transformers._import_structure.keys()       )
				# This contains all the base keys of the _import_structure object defined in the init, but if the user is missing
				# some optional dependencies, they may not have all of them. Thus we read the init to read all additions and
				# (potentiall re-) add them.
				with open(os.path.join(__UpperCAmelCase  ,					"__init__.py"       )  ,					"r"       ) as f:
								SCREAMING_SNAKE_CASE__		  =				f.read()
				import_structure_keys.update(set(re.findall(R"import_structure\[\"([^\"]*)\"\]"  ,					__UpperCAmelCase       )       )       )

				SCREAMING_SNAKE_CASE__		  =				[
				    module
				    for module in get_transformers_submodules()
				    if module not in IGNORE_SUBMODULES and module not in import_structure_keys
				]

				if len(__UpperCAmelCase       ) > 0:
								SCREAMING_SNAKE_CASE__		  =				"\n".join(F"""- {module}""" for module in module_not_registered       )
								raise ValueError(
								    "The following submodules are not properly registed in the main init of Transformers:\n"
								    F"""{list_of_modules}\n"""
								    "Make sure they appear somewhere in the keys of `_import_structure` with an empty list as value."       )


if __name__ == "__main__":
						check_all_inits()
						check_submodules()




