
'''simple docstring'''






import collections
import importlib.util
import os
import re
from pathlib import Path


UpperCAmelCase_							: List[str] =							"""src/transformers"""


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







def 		A_							(						_lowerCAmelCase :     Union[str, Any]				):



      """simple docstring"""




      if _re_test_backend.search(_lowerCAmelCase				) is None:
            return None
      _lowerCamelCase					: Union[str, Any]		    = [b[0] for b in _re_backend.findall(_lowerCAmelCase				)]
      backends.sort()
      return "_and_".join(_lowerCAmelCase				)







def 		A_							(						_lowerCAmelCase :     List[Any]				):



      """simple docstring"""




      with open(_lowerCAmelCase					,						"r"					,						encoding="utf-8"					,						newline="\n"				) as f:
            _lowerCamelCase					: Tuple		    = f.readlines()

      _lowerCamelCase					: List[str]		    = 0
      while line_index < len(_lowerCAmelCase				) and not lines[line_index].startswith("_import_structure = {"				):
            line_index += 1

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

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

      _lowerCamelCase					: Tuple		    = {"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.
            _lowerCamelCase					: int		    = 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:
                  _lowerCamelCase					: str		    = 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

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

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

    # At this stage we are in the TYPE_CHECKING part, first grab the objects without a specific backend
      _lowerCamelCase					: str		    = []
      while (
          line_index < len(_lowerCAmelCase				)
          and find_backend(lines[line_index]				) is None
          and not lines[line_index].startswith("else"				)
      ):
            _lowerCamelCase					: int		    = lines[line_index]
            _lowerCamelCase					: Any		    = _re_import.search(_lowerCAmelCase				)
            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

      _lowerCamelCase					: Optional[Any]		    = {"none": objects}
      # Let's continue with backend-specific objects
      while line_index < len(_lowerCAmelCase				):
            # If the line is an if is_backend_available, we grab all objects associated.
            _lowerCamelCase					: List[Any]		    = 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:
                  _lowerCamelCase					: int		    = 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

                  _lowerCamelCase					: Optional[Any]		    = []
                  # Until we unindent, add backend objects to the list
                  while len(lines[line_index]				) <= 1 or lines[line_index].startswith(" " * 8				):
                        _lowerCamelCase					: List[Any]		    = lines[line_index]
                        _lowerCamelCase					: Tuple		    = _re_import.search(_lowerCAmelCase				)
                        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					: Dict		    = objects
            else:
                  line_index += 1

      return import_dict_objects, type_hint_objects







def 		A_							(						_lowerCAmelCase :     Any					,						_lowerCAmelCase :     Dict				):



      """simple docstring"""




      def find_duplicates(_lowerCAmelCase :     Tuple				):
            return [k for k, v in collections.Counter(_lowerCAmelCase				).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!"]

      _lowerCamelCase					: str		    = []
      for key in import_dict_objects.keys():
            _lowerCamelCase					: List[str]		    = find_duplicates(import_dict_objects[key]				)
            if duplicate_imports:
                  errors.append(F'Duplicate _import_structure definitions for: {duplicate_imports}'				)
            _lowerCamelCase					: List[Any]		    = 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]				)				):
                  _lowerCamelCase					: Optional[int]		    = "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 		A_							(						):



      """simple docstring"""




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







def 		A_							(						):



      """simple docstring"""




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


UpperCAmelCase_							: Dict =							[
    """convert_pytorch_checkpoint_to_tf2""",
    """modeling_flax_pytorch_utils""",
]







def 		A_							(						):



      """simple docstring"""




      _lowerCamelCase					: int		    = importlib.util.spec_from_file_location(
          "transformers"					,						os.path.join(_lowerCAmelCase					,						"__init__.py"				)					,						submodule_search_locations=[PATH_TO_TRANSFORMERS]					,						)
      _lowerCamelCase					: Optional[int]		    = spec.loader.load_module()

      _lowerCamelCase					: Dict		    = [
          module
          for module in get_transformers_submodules()
          if module not in IGNORE_SUBMODULES and module not in transformers._import_structure.keys()
      ]
      if len(_lowerCAmelCase				) > 0:
            _lowerCamelCase					: Optional[int]		    = "\n".join(F'- {module}' for module in module_not_registered				)
            raise ValueError(
                "The following submodules are not properly registered 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()



'''simple docstring'''
import unittest

import numpy as np

from transformers import DistilBertConfig, 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.numpy as jnp

					from transformers.models.distilbert.modeling_flax_distilbert import (
					    FlaxDistilBertForMaskedLM,
					    FlaxDistilBertForMultipleChoice,
					    FlaxDistilBertForQuestionAnswering,
					    FlaxDistilBertForSequenceClassification,
					    FlaxDistilBertForTokenClassification,
					    FlaxDistilBertModel,
					)




class        _UpperCamelCase	(    unittest.TestCase):


				'''simple docstring'''


				def __init__(     self							,      a_							,      a_=1_3							,      a_=7							,      a_=True							,      a_=True							,      a_=True							,      a_=True							,      a_=9_9							,      a_=3_2							,      a_=5							,      a_=4							,      a_=3_7							,      a_="gelu"							,      a_=0.1							,      a_=0.1							,      a_=5_1_2							,      a_=1_6							,      a_=2							,      a_=0.02							,      a_=4							,      )    ->  Tuple:
					lowercase						:		Optional[Any]   					=		parent
					lowercase						:		int   					=		batch_size
					lowercase						:		int   					=		seq_length
					lowercase						:		List[str]   					=		is_training
					lowercase						:		str   					=		use_attention_mask
					lowercase						:		List[str]   					=		use_token_type_ids
					lowercase						:		Optional[Any]   					=		use_labels
					lowercase						:		Dict   					=		vocab_size
					lowercase						:		Union[str, Any]   					=		hidden_size
					lowercase						:		int   					=		num_hidden_layers
					lowercase						:		Optional[Any]   					=		num_attention_heads
					lowercase						:		Optional[Any]   					=		intermediate_size
					lowercase						:		int   					=		hidden_act
					lowercase						:		Dict   					=		hidden_dropout_prob
					lowercase						:		Optional[Any]   					=		attention_probs_dropout_prob
					lowercase						:		Dict   					=		max_position_embeddings
					lowercase						:		Tuple   					=		type_vocab_size
					lowercase						:		int   					=		type_sequence_label_size
					lowercase						:		Optional[Any]   					=		initializer_range
					lowercase						:		Union[str, Any]   					=		num_choices

				def 	a__		(     self							)    ->  Optional[int]:
					lowercase						:		List[Any]   					=		ids_tensor([self.batch_size, self.seq_length]							,      self.vocab_size							)

					lowercase						:		Any   					=		None
					if self.use_attention_mask:
						lowercase						:		str   					=		random_attention_mask([self.batch_size, self.seq_length]							)

					lowercase						:		Optional[Any]   					=		DistilBertConfig(
					    vocab_size=self.vocab_size							,      dim=self.hidden_size							,      n_layers=self.num_hidden_layers							,      n_heads=self.num_attention_heads							,      hidden_dim=self.intermediate_size							,      hidden_act=self.hidden_act							,      dropout=self.hidden_dropout_prob							,      attention_dropout=self.attention_probs_dropout_prob							,      max_position_embeddings=self.max_position_embeddings							,      initializer_range=self.initializer_range							,      tie_weights_=a_							,      )

					return config, input_ids, attention_mask


				def 	a__		(     self							)    ->  List[str]:
					lowercase						:		Dict   					=		self.prepare_config_and_inputs()
					lowercase					,		lowercase					,		lowercase						:		Dict   					=		config_and_inputs
					lowercase						:		Any   					=		{"input_ids": input_ids, "attention_mask": attention_mask}
					return config, inputs_dict




@require_flax
class        _UpperCamelCase	(    SCREAMING_SNAKE_CASE						,			unittest.TestCase):


				'''simple docstring'''


				_snake_case						       =				(
				    (
				        FlaxDistilBertModel,
				        FlaxDistilBertForMaskedLM,
				        FlaxDistilBertForMultipleChoice,
				        FlaxDistilBertForQuestionAnswering,
				        FlaxDistilBertForSequenceClassification,
				        FlaxDistilBertForTokenClassification,
				        FlaxDistilBertForQuestionAnswering,
				    )
				    if is_flax_available()
				    else ()
				)

				def 	a__		(     self							)    ->  Dict:
					lowercase						:		Optional[int]   					=		FlaxDistilBertModelTester(self							)


				@slow
				def 	a__		(     self							)    ->  Union[str, Any]:
					for model_class_name in self.all_model_classes:
						lowercase						:		int   					=		model_class_name.from_pretrained("distilbert-base-uncased"							)
						lowercase						:		Tuple   					=		model(np.ones((1, 1)							)							)
						self.assertIsNotNone(a_							)




@require_flax
class        _UpperCamelCase	(    unittest.TestCase):


				'''simple docstring'''


				@slow
				def 	a__		(     self							)    ->  Union[str, Any]:
					lowercase						:		str   					=		FlaxDistilBertModel.from_pretrained("distilbert-base-uncased"							)
					lowercase						:		int   					=		np.array([[0, 3_4_5, 2_3_2, 3_2_8, 7_4_0, 1_4_0, 1_6_9_5, 6_9, 6_0_7_8, 1_5_8_8, 2]]							)
					lowercase						:		int   					=		np.array([[0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]							)
					lowercase						:		List[str]   					=		model(a_							,      attention_mask=a_							)[0]
					lowercase						:		int   					=		(1, 1_1, 7_6_8)
					self.assertEqual(output.shape							,      a_							)
					lowercase						:		List[str]   					=		np.array([[[-0.16_39, 0.32_99, 0.16_48], [-0.17_46, 0.32_89, 0.17_10], [-0.18_84, 0.33_57, 0.18_10]]]							)

					self.assertTrue(jnp.allclose(output[:, 1:4, 1:4]							,      a_							,      atol=1e-4							)							)


