import argparse
import os
import re


UpperCamelCase__    							= 'src/diffusers'

# Pattern that looks at the indentation in a line.
UpperCamelCase__    							= re.compile(R'^(\s*)\S')
# Pattern that matches `"key":" and puts `key` in group 0.
UpperCamelCase__    							= re.compile(R'^\s*"([^"]+)":')
# Pattern that matches `_import_structure["key"]` and puts `key` in group 0.
UpperCamelCase__    							= re.compile(R'^\s*_import_structure\["([^"]+)"\]')
# Pattern that matches `"key",` and puts `key` in group 0.
UpperCamelCase__    							= re.compile(R'^\s*"([^"]+)",\s*$')
# Pattern that matches any `[stuff]` and puts `stuff` in group 0.
UpperCamelCase__    							= re.compile(R'\[([^\]]+)\]')




def        lowerCAmelCase_			(					__A							)					->    str:







      '''simple docstring'''


      UpperCAmelCase__								=  _re_indent.search(__A							)
      return "" if search is None else search.groups()[0]




def        lowerCAmelCase_			(					__A,  __A="",  __A=None,  __A=None							)					->    str:







      '''simple docstring'''


      UpperCAmelCase__								=  0
      UpperCAmelCase__								=  code.split("\n"							)
      if start_prompt is not None:
            while not lines[index].startswith(__A							):
                  index += 1
            UpperCAmelCase__								=  ["\n".join(lines[:index]							)]
      else:
            UpperCAmelCase__								=  []

      # We split into blocks until we get to the `end_prompt` (or the end of the block).
      UpperCAmelCase__								=  [lines[index]]
      index += 1
      while index < len(__A							) and (end_prompt is None or not lines[index].startswith(__A							)):
            if len(lines[index]							) > 0 and get_indent(lines[index]							) == indent_level:
                  if len(__A							) > 0 and get_indent(current_block[-1]							).startswith(indent_level + " "							):
                        current_block.append(lines[index]							)
                        blocks.append("\n".join(__A							)							)
                        if index < len(__A							) - 1:
                              UpperCAmelCase__								=  [lines[index + 1]]
                              index += 1
                        else:
                              UpperCAmelCase__								=  []
                  else:
                        blocks.append("\n".join(__A							)							)
                        UpperCAmelCase__								=  [lines[index]]
            else:
                  current_block.append(lines[index]							)
            index += 1

      # Adds current block if it's nonempty.
      if len(__A							) > 0:
            blocks.append("\n".join(__A							)							)

      # Add final block after end_prompt if provided.
      if end_prompt is not None and index < len(__A							):
            blocks.append("\n".join(lines[index:]							)							)

      return blocks




def        lowerCAmelCase_			(					__A							)					->    Tuple:







      '''simple docstring'''


      def _inner(__A							):
            return key(__A							).lower().replace("_",  ""							)

      return _inner




def        lowerCAmelCase_			(					__A,  __A=None							)					->    List[str]:







      '''simple docstring'''


      def noop(__A							):
            return x

      if key is None:
            UpperCAmelCase__								=  noop
      # Constants are all uppercase, they go first.
      UpperCAmelCase__								=  [obj for obj in objects if key(__A							).isupper()]
      # Classes are not all uppercase but start with a capital, they go second.
      UpperCAmelCase__								=  [obj for obj in objects if key(__A							)[0].isupper() and not key(__A							).isupper()]
      # Functions begin with a lowercase, they go last.
      UpperCAmelCase__								=  [obj for obj in objects if not key(__A							)[0].isupper()]

      UpperCAmelCase__								=  ignore_underscore(__A							)
      return sorted(__A,  key=__A							) + sorted(__A,  key=__A							) + sorted(__A,  key=__A							)




def        lowerCAmelCase_			(					__A							)					->    Optional[Any]:







      '''simple docstring'''


      def _replace(__A							):
            UpperCAmelCase__								=  match.groups()[0]
            if "," not in imports:
                  return f"""[{imports}]"""
            UpperCAmelCase__								=  [part.strip().replace("\"",  ""							) for part in imports.split(","							)]
            # We will have a final empty element if the line finished with a comma.
            if len(keys[-1]							) == 0:
                  UpperCAmelCase__								=  keys[:-1]
            return "[" + ", ".join([f"""\"{k}\"""" for k in sort_objects(__A							)]							) + "]"

      UpperCAmelCase__								=  import_statement.split("\n"							)
      if len(__A							) > 3:
            # Here we have to sort internal imports that are on several lines (one per name):
            # key: [
            #     "object1",
            #     "object2",
            #     ...
            # ]

            # We may have to ignore one or two lines on each side.
            UpperCAmelCase__								=  2 if lines[1].strip() == "[" else 1
            UpperCAmelCase__								=  [(i, _re_strip_line.search(__A							).groups()[0]) for i, line in enumerate(lines[idx:-idx]							)]
            UpperCAmelCase__								=  sort_objects(__A,  key=lambda __A							: x[1]							)
            UpperCAmelCase__								=  [lines[x[0] + idx] for x in sorted_indices]
            return "\n".join(lines[:idx] + sorted_lines + lines[-idx:]							)
      elif len(__A							) == 3:
            # Here we have to sort internal imports that are on one separate line:
            # key: [
            #     "object1", "object2", ...
            # ]
            if _re_bracket_content.search(lines[1]							) is not None:
                  UpperCAmelCase__								=  _re_bracket_content.sub(_replace,  lines[1]							)
            else:
                  UpperCAmelCase__								=  [part.strip().replace("\"",  ""							) for part in lines[1].split(","							)]
                  # We will have a final empty element if the line finished with a comma.
                  if len(keys[-1]							) == 0:
                        UpperCAmelCase__								=  keys[:-1]
                  UpperCAmelCase__								=  get_indent(lines[1]							) + ", ".join([f"""\"{k}\"""" for k in sort_objects(__A							)]							)
            return "\n".join(__A							)
      else:
            # Finally we have to deal with imports fitting on one line
            UpperCAmelCase__								=  _re_bracket_content.sub(_replace,  __A							)
            return import_statement




def        lowerCAmelCase_			(					__A,  __A=True							)					->    Any:







      '''simple docstring'''


      with open(__A,  "r"							) as f:
            UpperCAmelCase__								=  f.read()

      if "_import_structure" not in code:
            return

      # Blocks of indent level 0
      UpperCAmelCase__								=  split_code_in_indented_blocks(
          __A,  start_prompt="_import_structure = {",  end_prompt="if TYPE_CHECKING:"							)

      # We ignore block 0 (everything until start_prompt) and the last block (everything after end_prompt).
      for block_idx in range(1,  len(__A							) - 1							):
            # Check if the block contains some `_import_structure`s thingy to sort.
            UpperCAmelCase__								=  main_blocks[block_idx]
            UpperCAmelCase__								=  block.split("\n"							)

            # Get to the start of the imports.
            UpperCAmelCase__								=  0
            while line_idx < len(__A							) and "_import_structure" not in block_lines[line_idx]:
                  # Skip dummy import blocks
                  if "import dummy" in block_lines[line_idx]:
                        UpperCAmelCase__								=  len(__A							)
                  else:
                        line_idx += 1
            if line_idx >= len(__A							):
                  continue

            # Ignore beginning and last line: they don't contain anything.
            UpperCAmelCase__								=  "\n".join(block_lines[line_idx:-1]							)
            UpperCAmelCase__								=  get_indent(block_lines[1]							)
            # Slit the internal block into blocks of indent level 1.
            UpperCAmelCase__								=  split_code_in_indented_blocks(__A,  indent_level=__A							)
            # We have two categories of import key: list or _import_structure[key].append/extend
            UpperCAmelCase__								=  _re_direct_key if "_import_structure" in block_lines[0] else _re_indirect_key
            # Grab the keys, but there is a trap: some lines are empty or just comments.
            UpperCAmelCase__								=  [(pattern.search(__A							).groups()[0] if pattern.search(__A							) is not None else None) for b in internal_blocks]
            # We only sort the lines with a key.
            UpperCAmelCase__								=  [(i, key) for i, key in enumerate(__A							) if key is not None]
            UpperCAmelCase__								=  [x[0] for x in sorted(__A,  key=lambda __A							: x[1]							)]

            # We reorder the blocks by leaving empty lines/comments as they were and reorder the rest.
            UpperCAmelCase__								=  0
            UpperCAmelCase__								=  []
            for i in range(len(__A							)							):
                  if keys[i] is None:
                        reordered_blocks.append(internal_blocks[i]							)
                  else:
                        UpperCAmelCase__								=  sort_objects_in_import(internal_blocks[sorted_indices[count]]							)
                        reordered_blocks.append(__A							)
                        count += 1

        # And we put our main block back together with its first and last line.
            UpperCAmelCase__								=  "\n".join(block_lines[:line_idx] + reordered_blocks + [block_lines[-1]]							)

      if code != "\n".join(__A							):
            if check_only:
                  return True
            else:
                  print(f"""Overwriting {file}."""							)
                  with open(__A,  "w"							) as f:
                        f.write("\n".join(__A							)							)




def        lowerCAmelCase_			(					__A=True							)					->    List[str]:







      '''simple docstring'''


      UpperCAmelCase__								=  []
      for root, _, files in os.walk(__A							):
            if "__init__.py" in files:
                  UpperCAmelCase__								=  sort_imports(os.path.join(__A,  "__init__.py"							),  check_only=__A							)
                  if result:
                        UpperCAmelCase__								=  [os.path.join(__A,  "__init__.py"							)]
      if len(__A							) > 0:
            raise ValueError(f"""Would overwrite {len(__A							)} files, run `make style`."""							)


if __name__ == "__main__":
      UpperCamelCase__    							= argparse.ArgumentParser()
      parser.add_argument('--check_only', action='store_true', help='Whether to only check or fix style.')
      UpperCamelCase__    							= parser.parse_args()

      sort_imports_in_all_inits(check_only=args.check_only)




from __future__ import annotations

import unittest

from transformers import DistilBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow

from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask
from ...test_pipeline_mixin import PipelineTesterMixin


if is_tf_available():
      import tensorflow as tf

      from transformers.models.distilbert.modeling_tf_distilbert import (
          TF_DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
          TFDistilBertForMaskedLM,
          TFDistilBertForMultipleChoice,
          TFDistilBertForQuestionAnswering,
          TFDistilBertForSequenceClassification,
          TFDistilBertForTokenClassification,
          TFDistilBertModel,
      )





class 					A							:


   def __init__(self					:						Tuple	,  __UpperCAmelCase					:						str	,  )						->    Dict:
         """simple docstring"""



         UpperCAmelCase__								=  parent
         UpperCAmelCase__								=  1_3
         UpperCAmelCase__								=  7
         UpperCAmelCase__								=  True
         UpperCAmelCase__								=  True
         UpperCAmelCase__								=  False
         UpperCAmelCase__								=  True
         UpperCAmelCase__								=  9_9
         UpperCAmelCase__								=  3_2
         UpperCAmelCase__								=  2
         UpperCAmelCase__								=  4
         UpperCAmelCase__								=  3_7
         UpperCAmelCase__								=  "gelu"
         UpperCAmelCase__								=  0.1
         UpperCAmelCase__								=  0.1
         UpperCAmelCase__								=  5_1_2
         UpperCAmelCase__								=  1_6
         UpperCAmelCase__								=  2
         UpperCAmelCase__								=  0.02
         UpperCAmelCase__								=  3
         UpperCAmelCase__								=  4
         UpperCAmelCase__								=  None


   def       lowercase_				(self					:						int		)						->    Union[str, Any]:
         """simple docstring"""



         UpperCAmelCase__								=  ids_tensor([self.batch_size, self.seq_length]	,  self.vocab_size		)

         UpperCAmelCase__								=  None
         if self.use_input_mask:
               UpperCAmelCase__								=  random_attention_mask([self.batch_size, self.seq_length]		)

         UpperCAmelCase__								=  None
         UpperCAmelCase__								=  None
         UpperCAmelCase__								=  None
         if self.use_labels:
               UpperCAmelCase__								=  ids_tensor([self.batch_size]	,  self.type_sequence_label_size		)
               UpperCAmelCase__								=  ids_tensor([self.batch_size, self.seq_length]	,  self.num_labels		)
               UpperCAmelCase__								=  ids_tensor([self.batch_size]	,  self.num_choices		)

         UpperCAmelCase__								=  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	,  )

         return config, input_ids, input_mask, sequence_labels, token_labels, choice_labels


   def       lowercase_				(self					:						int	,  __UpperCAmelCase					:						int	,  __UpperCAmelCase					:						Tuple	,  __UpperCAmelCase					:						Optional[Any]	,  __UpperCAmelCase					:						Union[str, Any]	,  __UpperCAmelCase					:						Tuple	,  __UpperCAmelCase					:						Tuple		)						->    Tuple:
         """simple docstring"""



         UpperCAmelCase__								=  TFDistilBertModel(config=__UpperCAmelCase		)
         UpperCAmelCase__								=  {"input_ids": input_ids, "attention_mask": input_mask}

         UpperCAmelCase__								=  model(__UpperCAmelCase		)

         UpperCAmelCase__								=  [input_ids, input_mask]

         UpperCAmelCase__								=  model(__UpperCAmelCase		)

         self.parent.assertEqual(result.last_hidden_state.shape	,  (self.batch_size, self.seq_length, self.hidden_size)		)


   def       lowercase_				(self					:						str	,  __UpperCAmelCase					:						int	,  __UpperCAmelCase					:						Optional[Any]	,  __UpperCAmelCase					:						Union[str, Any]	,  __UpperCAmelCase					:						List[Any]	,  __UpperCAmelCase					:						Any	,  __UpperCAmelCase					:						Dict		)						->    List[Any]:
         """simple docstring"""



         UpperCAmelCase__								=  TFDistilBertForMaskedLM(config=__UpperCAmelCase		)
         UpperCAmelCase__								=  {"input_ids": input_ids, "attention_mask": input_mask}
         UpperCAmelCase__								=  model(__UpperCAmelCase		)
         self.parent.assertEqual(result.logits.shape	,  (self.batch_size, self.seq_length, self.vocab_size)		)


   def       lowercase_				(self					:						int	,  __UpperCAmelCase					:						Dict	,  __UpperCAmelCase					:						Optional[Any]	,  __UpperCAmelCase					:						str	,  __UpperCAmelCase					:						Optional[Any]	,  __UpperCAmelCase					:						List[Any]	,  __UpperCAmelCase					:						List[str]		)						->    List[Any]:
         """simple docstring"""



         UpperCAmelCase__								=  TFDistilBertForQuestionAnswering(config=__UpperCAmelCase		)
         UpperCAmelCase__								=  {
             "input_ids": input_ids,
             "attention_mask": input_mask,
         }
         UpperCAmelCase__								=  model(__UpperCAmelCase		)
         self.parent.assertEqual(result.start_logits.shape	,  (self.batch_size, self.seq_length)		)
         self.parent.assertEqual(result.end_logits.shape	,  (self.batch_size, self.seq_length)		)


   def       lowercase_				(self					:						Optional[int]	,  __UpperCAmelCase					:						str	,  __UpperCAmelCase					:						Optional[Any]	,  __UpperCAmelCase					:						List[str]	,  __UpperCAmelCase					:						Dict	,  __UpperCAmelCase					:						Optional[int]	,  __UpperCAmelCase					:						List[str]		)						->    str:
         """simple docstring"""



         UpperCAmelCase__								=  self.num_labels
         UpperCAmelCase__								=  TFDistilBertForSequenceClassification(__UpperCAmelCase		)
         UpperCAmelCase__								=  {"input_ids": input_ids, "attention_mask": input_mask}
         UpperCAmelCase__								=  model(__UpperCAmelCase		)
         self.parent.assertEqual(result.logits.shape	,  (self.batch_size, self.num_labels)		)


   def       lowercase_				(self					:						Optional[int]	,  __UpperCAmelCase					:						List[Any]	,  __UpperCAmelCase					:						Optional[Any]	,  __UpperCAmelCase					:						Dict	,  __UpperCAmelCase					:						List[Any]	,  __UpperCAmelCase					:						str	,  __UpperCAmelCase					:						Any		)						->    int:
         """simple docstring"""



         UpperCAmelCase__								=  self.num_choices
         UpperCAmelCase__								=  TFDistilBertForMultipleChoice(__UpperCAmelCase		)
         UpperCAmelCase__								=  tf.tile(tf.expand_dims(__UpperCAmelCase	,  1		)	,  (1, self.num_choices, 1)		)
         UpperCAmelCase__								=  tf.tile(tf.expand_dims(__UpperCAmelCase	,  1		)	,  (1, self.num_choices, 1)		)
         UpperCAmelCase__								=  {
             "input_ids": multiple_choice_inputs_ids,
             "attention_mask": multiple_choice_input_mask,
         }
         UpperCAmelCase__								=  model(__UpperCAmelCase		)
         self.parent.assertEqual(result.logits.shape	,  (self.batch_size, self.num_choices)		)


   def       lowercase_				(self					:						Dict	,  __UpperCAmelCase					:						Tuple	,  __UpperCAmelCase					:						Optional[int]	,  __UpperCAmelCase					:						Tuple	,  __UpperCAmelCase					:						List[str]	,  __UpperCAmelCase					:						Any	,  __UpperCAmelCase					:						Optional[int]		)						->    List[Any]:
         """simple docstring"""



         UpperCAmelCase__								=  self.num_labels
         UpperCAmelCase__								=  TFDistilBertForTokenClassification(__UpperCAmelCase		)
         UpperCAmelCase__								=  {"input_ids": input_ids, "attention_mask": input_mask}
         UpperCAmelCase__								=  model(__UpperCAmelCase		)
         self.parent.assertEqual(result.logits.shape	,  (self.batch_size, self.seq_length, self.num_labels)		)





   def       lowercase_				(self					:						Any		)						->    Dict:
         """simple docstring"""



         UpperCAmelCase__								=  self.prepare_config_and_inputs()
         ((UpperCAmelCase__)		,				(UpperCAmelCase__)		,				(UpperCAmelCase__)		,				(UpperCAmelCase__)		,				(UpperCAmelCase__)		,				(UpperCAmelCase__))								=  config_and_inputs
         UpperCAmelCase__								=  {"input_ids": input_ids, "attention_mask": input_mask}
         return config, inputs_dict





@require_tf
class 					A							(    UpperCAmelCase_		,    UpperCAmelCase_		,    unittest.TestCase					):
   __UpperCAmelCase			:			Union[str, Any]              =      (
       (
           TFDistilBertModel,
           TFDistilBertForMaskedLM,
           TFDistilBertForQuestionAnswering,
           TFDistilBertForSequenceClassification,
           TFDistilBertForTokenClassification,
           TFDistilBertForMultipleChoice,
       )
       if is_tf_available()
       else None
   )
   __UpperCAmelCase			:			Optional[int]              =      (
       {
           'feature-extraction': TFDistilBertModel,
           'fill-mask': TFDistilBertForMaskedLM,
           'question-answering': TFDistilBertForQuestionAnswering,
           'text-classification': TFDistilBertForSequenceClassification,
           'token-classification': TFDistilBertForTokenClassification,
           'zero-shot': TFDistilBertForSequenceClassification,
       }
       if is_tf_available()
       else {}
   )
   __UpperCAmelCase			:			Tuple              =      False
   __UpperCAmelCase			:			str              =      False


   def       lowercase_				(self					:						Union[str, Any]		)						->    str:
         """simple docstring"""



         UpperCAmelCase__								=  TFDistilBertModelTester(self		)
         UpperCAmelCase__								=  ConfigTester(self	,  config_class=__UpperCAmelCase	,  dim=3_7		)


   def       lowercase_				(self					:						Any		)						->    int:
         """simple docstring"""



         self.config_tester.run_common_tests()


   def       lowercase_				(self					:						int		)						->    int:
         """simple docstring"""



         UpperCAmelCase__								=  self.model_tester.prepare_config_and_inputs()
         self.model_tester.create_and_check_distilbert_model(*__UpperCAmelCase		)


   def       lowercase_				(self					:						Optional[int]		)						->    int:
         """simple docstring"""



         UpperCAmelCase__								=  self.model_tester.prepare_config_and_inputs()
         self.model_tester.create_and_check_distilbert_for_masked_lm(*__UpperCAmelCase		)


   def       lowercase_				(self					:						Any		)						->    Optional[int]:
         """simple docstring"""



         UpperCAmelCase__								=  self.model_tester.prepare_config_and_inputs()
         self.model_tester.create_and_check_distilbert_for_question_answering(*__UpperCAmelCase		)


   def       lowercase_				(self					:						List[str]		)						->    str:
         """simple docstring"""



         UpperCAmelCase__								=  self.model_tester.prepare_config_and_inputs()
         self.model_tester.create_and_check_distilbert_for_sequence_classification(*__UpperCAmelCase		)


   def       lowercase_				(self					:						Dict		)						->    List[str]:
         """simple docstring"""



         UpperCAmelCase__								=  self.model_tester.prepare_config_and_inputs()
         self.model_tester.create_and_check_distilbert_for_multiple_choice(*__UpperCAmelCase		)


   def       lowercase_				(self					:						str		)						->    List[Any]:
         """simple docstring"""



         UpperCAmelCase__								=  self.model_tester.prepare_config_and_inputs()
         self.model_tester.create_and_check_distilbert_for_token_classification(*__UpperCAmelCase		)





   @slow
   def       lowercase_				(self					:						Optional[int]		)						->    Optional[int]:
         """simple docstring"""



         for model_name in list(TF_DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST[:1]		):
               UpperCAmelCase__								=  TFDistilBertModel.from_pretrained(__UpperCAmelCase		)
               self.assertIsNotNone(__UpperCAmelCase		)





@require_tf
class 					A							(    unittest.TestCase					):


   @slow
   def       lowercase_				(self					:						List[Any]		)						->    Dict:
         """simple docstring"""



         UpperCAmelCase__								=  TFDistilBertModel.from_pretrained("distilbert-base-uncased"		)
         UpperCAmelCase__								=  tf.constant([[0, 1, 2, 3, 4, 5]]		)
         UpperCAmelCase__								=  model(__UpperCAmelCase		)[0]

         UpperCAmelCase__								=  [1, 6, 7_6_8]
         self.assertEqual(output.shape	,  __UpperCAmelCase		)

         UpperCAmelCase__								=  tf.constant(
             [
                 [
                     [0.19261885, -0.13732955, 0.4119799],
                     [0.22150156, -0.07422661, 0.39037204],
                     [0.22756018, -0.0896414, 0.3701467],
                 ]
             ]		)
         tf.debugging.assert_near(output[:, :3, :3]	,  __UpperCAmelCase	,  atol=1E-4		)



