





'''simple docstring'''







import argparse
import os
import re


_lowercase       						=			'src/transformers'

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

def    __UpperCamelCase	(	a    : Optional[int]     ) ->Any:
 snake_case				=			_re_indent.search(a     )
 return "" if search is None else search.groups()[0]

def    __UpperCamelCase	(	a    : Union[str, Any]					,   a    : Any=""					,   a    : List[str]=None					,   a    : List[Any]=None     ) ->Tuple:
 snake_case				=			0
 snake_case				=			code.split('''\n'''     )
 if start_prompt is not None:
  while not lines[index].startswith(a     ):
   index += 1
  snake_case				=			['''\n'''.join(lines[:index]     )]
 else:
  snake_case				=			[]

 # We split into blocks until we get to the `end_prompt` (or the end of the block).
 snake_case				=			[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:
     snake_case				=			[lines[index + 1]]
     index += 1
    else:
     snake_case				=			[]
   else:
    blocks.append('''\n'''.join(a     )     )
    snake_case				=			[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    __UpperCamelCase	(	a    : Dict     ) ->Dict:

 def _inner(a    : List[Any]     ):
  return key(a     ).lower().replace('''_'''					,   ''''''     )

 return _inner

def    __UpperCamelCase	(	a    : Dict					,   a    : List[str]=None     ) ->Optional[int]:

 # If no key is provided, we use a noop.
 def noop(a    : Any     ):
  return x

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

 snake_case				=			ignore_underscore(a     )
 return sorted(a					,   key=a     ) + sorted(a					,   key=a     ) + sorted(a					,   key=a     )

def    __UpperCamelCase	(	a    : int     ) ->List[str]:

 # This inner function sort imports between [ ].
 def _replace(a    : List[Any]     ):
  snake_case				=			match.groups()[0]
  if "," not in imports:
   return f"""[{imports}]"""
  snake_case				=			[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:
   snake_case				=			keys[:-1]
  return "[" + ", ".join([f"""\"{k}\"""" for k in sort_objects(a     )]     ) + "]"

 snake_case				=			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.
  snake_case				=			2 if lines[1].strip() == '''[''' else 1
  snake_case				=			[(i, _re_strip_line.search(a     ).groups()[0]) for i, line in enumerate(lines[idx:-idx]     )]
  snake_case				=			sort_objects(a					,   key=lambda a     : x[1]     )
  snake_case				=			[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:
   snake_case				=			_re_bracket_content.sub(_replace					,   lines[1]     )
  else:
   snake_case				=			[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:
    snake_case				=			keys[:-1]
   snake_case				=			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
  snake_case				=			_re_bracket_content.sub(_replace					,   a     )
  return import_statement

def    __UpperCamelCase	(	a    : str					,   a    : int=True     ) ->Dict:
 with open(a					,   encoding='''utf-8'''     ) as f:
  snake_case				=			f.read()

 if "_import_structure" not in code:
  return

 # Blocks of indent level 0
 snake_case				=			split_code_in_indented_blocks(
     a					,   start_prompt='''_import_structure = {'''					,   end_prompt='''if TYPE_CHECKING:'''     )

 # We ignore block 0 (everything untils 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.
  snake_case				=			main_blocks[block_idx]
  snake_case				=			block.split('''\n'''     )

  # Get to the start of the imports.
  snake_case				=			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]:
    snake_case				=			len(a     )
   else:
    line_idx += 1
  if line_idx >= len(a     ):
   continue

  # Ignore beginning and last line: they don't contain anything.
  snake_case				=			'''\n'''.join(block_lines[line_idx:-1]     )
  snake_case				=			get_indent(block_lines[1]     )
  # Slit the internal block into blocks of indent level 1.
  snake_case				=			split_code_in_indented_blocks(a					,   indent_level=a     )
  # We have two categories of import key: list or _import_structure[key].append/extend
  snake_case				=			_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.
  snake_case				=			[(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.
  snake_case				=			[(i, key) for i, key in enumerate(a     ) if key is not None]
  snake_case				=			[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.
  snake_case				=			0
  snake_case				=			[]
  for i in range(len(a     )     ):
   if keys[i] is None:
    reorderded_blocks.append(internal_blocks[i]     )
   else:
    snake_case				=			sort_objects_in_import(internal_blocks[sorted_indices[count]]     )
    reorderded_blocks.append(a     )
    count += 1

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

 if code != "\n".join(a     ):
  if check_only:
   return True
  else:
   print(f"""Overwriting {file}."""     )
   with open(a					,   '''w'''					,   encoding='''utf-8'''     ) as f:
    f.write('''\n'''.join(a     )     )

def    __UpperCamelCase	(	a    : Union[str, Any]=True     ) ->int:
 snake_case				=			[]
 for root, _, files in os.walk(a     ):
  if "__init__.py" in files:
   snake_case				=			sort_imports(os.path.join(a					,   '''__init__.py'''     )					,   check_only=a     )
   if result:
    snake_case				=			[os.path.join(a					,   '''__init__.py'''     )]
 if len(a     ) > 0:
  raise ValueError(f"""Would overwrite {len(a     )} files, run `make style`."""     )


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

   sort_imports_in_all_inits(check_only=args.check_only)








'''simple docstring'''







from __future__ import annotations

import inspect
import unittest

from transformers import ViTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available

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


if is_tf_available():
   import tensorflow as tf

   from transformers import TFViTForImageClassification, TFViTModel


if is_vision_available():
   from PIL import Image

   from transformers import ViTImageProcessor
class 			_lowercase						:







     def __init__( self    ,   A__    ,   A__=13    ,   A__=30    ,   A__=2    ,   A__=3    ,   A__=True    ,   A__=True    ,   A__=32    ,   A__=2    ,   A__=4    ,   A__=37    ,   A__="gelu"    ,   A__=0.1    ,   A__=0.1    ,   A__=10    ,   A__=0.0_2    ,   A__=3    ,   A__=None    ,   ) ->	List[Any]:
      snake_case				=			parent
      snake_case				=			batch_size
      snake_case				=			image_size
      snake_case				=			patch_size
      snake_case				=			num_channels
      snake_case				=			is_training
      snake_case				=			use_labels
      snake_case				=			hidden_size
      snake_case				=			num_hidden_layers
      snake_case				=			num_attention_heads
      snake_case				=			intermediate_size
      snake_case				=			hidden_act
      snake_case				=			hidden_dropout_prob
      snake_case				=			attention_probs_dropout_prob
      snake_case				=			type_sequence_label_size
      snake_case				=			initializer_range
      snake_case				=			scope

      # in ViT, the seq length equals the number of patches + 1 (we add 1 for the [CLS] token)
      snake_case				=			(image_size // patch_size) ** 2
      snake_case				=			num_patches + 1







     def     UpperCamelCase			( self    ) ->	int:
      snake_case				=			floats_tensor([self.batch_size, self.num_channels, self.image_size, self.image_size]    )

      snake_case				=			None
      if self.use_labels:
       snake_case				=			ids_tensor([self.batch_size]    ,   self.type_sequence_label_size    )

      snake_case				=			self.get_config()

      return config, pixel_values, labels







     def     UpperCamelCase			( self    ) ->	int:
      return ViTConfig(
          image_size=self.image_size    ,   patch_size=self.patch_size    ,   num_channels=self.num_channels    ,   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    ,   is_decoder=A__    ,   initializer_range=self.initializer_range    ,   )







     def     UpperCamelCase			( self    ,   A__    ,   A__    ,   A__    ) ->	Union[str, Any]:
      snake_case				=			TFViTModel(config=A__    )
      snake_case				=			model(A__    ,   training=A__    )
      self.parent.assertEqual(result.last_hidden_state.shape    ,   (self.batch_size, self.seq_length, self.hidden_size)    )

      # Test with an image with different size than the one specified in config.
      snake_case				=			self.image_size // 2
      snake_case				=			pixel_values[:, :, :image_size, :image_size]
      snake_case				=			model(A__    ,   interpolate_pos_encoding=A__    ,   training=A__    )
      snake_case				=			(image_size // self.patch_size) ** 2 + 1
      self.parent.assertEqual(result.last_hidden_state.shape    ,   (self.batch_size, seq_length, self.hidden_size)    )







     def     UpperCamelCase			( self    ,   A__    ,   A__    ,   A__    ) ->	Optional[int]:
      snake_case				=			self.type_sequence_label_size
      snake_case				=			TFViTForImageClassification(A__    )
      snake_case				=			model(A__    ,   labels=A__    ,   training=A__    )
      self.parent.assertEqual(result.logits.shape    ,   (self.batch_size, self.type_sequence_label_size)    )

      # Test with an image with different size than the one specified in config.
      snake_case				=			self.image_size // 2
      snake_case				=			pixel_values[:, :, :image_size, :image_size]
      snake_case				=			model(A__    ,   interpolate_pos_encoding=A__    ,   training=A__    )
      self.parent.assertEqual(result.logits.shape    ,   (self.batch_size, self.type_sequence_label_size)    )

      # test greyscale images
      snake_case				=			1
      snake_case				=			TFViTForImageClassification(A__    )
      snake_case				=			floats_tensor([self.batch_size, 1, self.image_size, self.image_size]    )
      snake_case				=			model(A__    )
      self.parent.assertEqual(result.logits.shape    ,   (self.batch_size, self.type_sequence_label_size)    )







     def     UpperCamelCase			( self    ) ->	Union[str, Any]:
      snake_case				=			self.prepare_config_and_inputs()
      snake_case				,		snake_case				,		snake_case				=			config_and_inputs
      snake_case				=			{'''pixel_values''': pixel_values}
      return config, inputs_dict




@require_tf
class 			_lowercase						(       __a				,		__a				,		unittest.TestCase					):
     _UpperCAmelCase										=					(TFViTModel, TFViTForImageClassification) if is_tf_available() else ()
     _UpperCAmelCase										=					(
         {'''feature-extraction''': TFViTModel, '''image-classification''': TFViTForImageClassification}
         if is_tf_available()
         else {}
     )

     _UpperCAmelCase										=					False
     _UpperCAmelCase										=					False
     _UpperCAmelCase										=					False







     def     UpperCamelCase			( self    ) ->	List[Any]:
      snake_case				=			TFViTModelTester(self    )
      snake_case				=			ConfigTester(self    ,   config_class=A__    ,   has_text_modality=A__    ,   hidden_size=37    )







     def     UpperCamelCase			( self    ) ->	int:
      self.config_tester.run_common_tests()







     @unittest.skip(reason='''ViT does not use inputs_embeds'''    )
     def     UpperCamelCase			( self    ) ->	int:
      pass







     @unittest.skip(reason='''ViT does not use inputs_embeds'''    )
     def     UpperCamelCase			( self    ) ->	str:
      pass







     def     UpperCamelCase			( self    ) ->	Union[str, Any]:
      snake_case				,		snake_case				=			self.model_tester.prepare_config_and_inputs_for_common()

      for model_class in self.all_model_classes:
       snake_case				=			model_class(A__    )
       self.assertIsInstance(model.get_input_embeddings()    ,   (tf.keras.layers.Layer)    )
       snake_case				=			model.get_output_embeddings()
       self.assertTrue(x is None or isinstance(A__    ,   tf.keras.layers.Layer    )    )







     def     UpperCamelCase			( self    ) ->	List[Any]:
      snake_case				,		snake_case				=			self.model_tester.prepare_config_and_inputs_for_common()

      for model_class in self.all_model_classes:
       snake_case				=			model_class(A__    )
       snake_case				=			inspect.signature(model.call    )
       # signature.parameters is an OrderedDict => so arg_names order is deterministic
       snake_case				=			[*signature.parameters.keys()]

       snake_case				=			['''pixel_values''']
       self.assertListEqual(arg_names[:1]    ,   A__    )







     def     UpperCamelCase			( self    ) ->	Union[str, Any]:
      snake_case				=			self.model_tester.prepare_config_and_inputs()
      self.model_tester.create_and_check_model(*A__    )







     def     UpperCamelCase			( self    ) ->	Optional[Any]:
      snake_case				=			self.model_tester.prepare_config_and_inputs()
      self.model_tester.create_and_check_for_image_classification(*A__    )







     @slow
     def     UpperCamelCase			( self    ) ->	Any:
      snake_case				=			TFViTModel.from_pretrained('''google/vit-base-patch16-224'''    )
      self.assertIsNotNone(A__    )




def    __UpperCamelCase	(	) ->Any:
 snake_case				=			Image.open('''./tests/fixtures/tests_samples/COCO/000000039769.png'''     )
 return image






@require_tf
@require_vision
class 			_lowercase						(       unittest.TestCase					):







     @cached_property
     def     UpperCamelCase			( self    ) ->	Optional[int]:
      return ViTImageProcessor.from_pretrained('''google/vit-base-patch16-224'''    ) if is_vision_available() else None







     @slow
     def     UpperCamelCase			( self    ) ->	Dict:
      snake_case				=			TFViTForImageClassification.from_pretrained('''google/vit-base-patch16-224'''    )

      snake_case				=			self.default_image_processor
      snake_case				=			prepare_img()
      snake_case				=			image_processor(images=A__    ,   return_tensors='''tf'''    )

      # forward pass
      snake_case				=			model(**A__    )

      # verify the logits
      snake_case				=			tf.TensorShape((1, 10_00)    )
      self.assertEqual(outputs.logits.shape    ,   A__    )

      snake_case				=			tf.constant([-0.2_7_4_4, 0.8_2_1_5, -0.0_8_3_6]    )

      tf.debugging.assert_near(outputs.logits[0, :3]    ,   A__    ,   atol=1e-4    )

