






'''simple docstring'''
import argparse
import glob
import importlib.util
import os
import re

import black
from doc_builder.style_doc import style_docstrings_in_code


# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_copies.py
a_											=			'''src/diffusers'''
a_											=			'''.'''


# This is to make sure the diffusers module imported is the one in the repo.
a_											=			importlib.util.spec_from_file_location(
    'diffusers',
    os.path.join(DIFFUSERS_PATH, '__init__.py'),
    submodule_search_locations=[DIFFUSERS_PATH],
)
a_											=			spec.loader.load_module()





def 			_a(	UpperCamelCase__					:    List[Any],						UpperCamelCase__					:    Any				):




      '''simple docstring'''






      return line.startswith(_lowercase				) or len(_lowercase				) <= 1 or re.search(R'''^\s*\)(\s*->.*:|:)\s*$''',						_lowercase				) is not None





def 			_a(	UpperCamelCase__					:    Dict				):




      '''simple docstring'''






      SCREAMING_SNAKE_CASE__  :					Optional[Any]						=object_name.split('''.'''				)
      SCREAMING_SNAKE_CASE__  :					str						=0

      # First let's find the module where our object lives.
      SCREAMING_SNAKE_CASE__  :					List[Any]						=parts[i]
      while i < len(_lowercase				) and not os.path.isfile(os.path.join(_lowercase,						f"{module}.py"				)				):
            i += 1
            if i < len(_lowercase				):
                  SCREAMING_SNAKE_CASE__  :					List[Any]						=os.path.join(_lowercase,						parts[i]				)
      if i >= len(_lowercase				):
            raise ValueError(f"`object_name` should begin with the name of a module of diffusers but got {object_name}."				)

      with open(os.path.join(_lowercase,						f"{module}.py"				),						'''r''',						encoding='''utf-8''',						newline='''\n'''				) as f:
            SCREAMING_SNAKE_CASE__  :					Dict						=f.readlines()

      # Now let's find the class / func in the code!
      SCREAMING_SNAKE_CASE__  :					Any						=""
      SCREAMING_SNAKE_CASE__  :					Tuple						=0
      for name in parts[i + 1 :]:
            while (
                line_index < len(_lowercase				) and re.search(Rf"^{indent}(class|def)\s+{name}(\(|\:)",						lines[line_index]				) is None
            ):
                  line_index += 1
            indent += "    "
            line_index += 1

      if line_index >= len(_lowercase				):
            raise ValueError(f" {object_name} does not match any function or class in {module}."				)

      # We found the beginning of the class / func, now let's find the end (when the indent diminishes).
      SCREAMING_SNAKE_CASE__  :					List[Any]						=line_index
      while line_index < len(_lowercase				) and _should_continue(lines[line_index],						_lowercase				):
            line_index += 1
      # Clean up empty lines at the end (if any).
      while len(lines[line_index - 1]				) <= 1:
            line_index -= 1

      SCREAMING_SNAKE_CASE__  :					str						=lines[start_index:line_index]
      return "".join(_lowercase				)


a_											=			re.compile(R'^(\s*)#\s*Copied from\s+diffusers\.(\S+\.\S+)\s*($|\S.*$)')
a_											=			re.compile(R'^\s*(\S+)->(\S+)(\s+.*|$)')
a_											=			re.compile(R'<FILL\s+[^>]*>')





def 			_a(	UpperCamelCase__					:    Optional[int]				):




      '''simple docstring'''






      SCREAMING_SNAKE_CASE__  :					Optional[int]						=code.split('''\n'''				)
      SCREAMING_SNAKE_CASE__  :					Optional[int]						=0
      while idx < len(_lowercase				) and len(lines[idx]				) == 0:
            idx += 1
      if idx < len(_lowercase				):
            return re.search(R'''^(\s*)\S''',						lines[idx]				).groups()[0]
      return ""





def 			_a(	UpperCamelCase__					:    Optional[Any]				):




      '''simple docstring'''






      SCREAMING_SNAKE_CASE__  :					List[Any]						=len(get_indent(_lowercase				)				) > 0
      if has_indent:
            SCREAMING_SNAKE_CASE__  :					Optional[int]						=f"class Bla:\n{code}"
      SCREAMING_SNAKE_CASE__  :					List[Any]						=black.Mode(target_versions={black.TargetVersion.PYaa},						line_length=1_1_9,						preview=_lowercase				)
      SCREAMING_SNAKE_CASE__  :					int						=black.format_str(_lowercase,						mode=_lowercase				)
      SCREAMING_SNAKE_CASE__  :					Tuple						=style_docstrings_in_code(_lowercase				)
      return result[len('''class Bla:\n'''				) :] if has_indent else result





def 			_a(	UpperCamelCase__					:    Optional[Any],						UpperCamelCase__					:    List[Any]=False				):




      '''simple docstring'''






      with open(_lowercase,						'''r''',						encoding='''utf-8''',						newline='''\n'''				) as f:
            SCREAMING_SNAKE_CASE__  :					int						=f.readlines()
      SCREAMING_SNAKE_CASE__  :					Optional[int]						=[]
      SCREAMING_SNAKE_CASE__  :					Optional[int]						=0
      # Not a for loop cause `lines` is going to change (if `overwrite=True`).
      while line_index < len(_lowercase				):
            SCREAMING_SNAKE_CASE__  :					Union[str, Any]						=_re_copy_warning.search(lines[line_index]				)
            if search is None:
                  line_index += 1
                  continue

            # There is some copied code here, let's retrieve the original.
            SCREAMING_SNAKE_CASE__  :					Dict						=search.groups()
            SCREAMING_SNAKE_CASE__  :					Optional[int]						=find_code_in_diffusers(_lowercase				)
            SCREAMING_SNAKE_CASE__  :					List[str]						=get_indent(_lowercase				)

            SCREAMING_SNAKE_CASE__  :					Any						=line_index + 1 if indent == theoretical_indent else line_index + 2
            SCREAMING_SNAKE_CASE__  :					Union[str, Any]						=theoretical_indent
            SCREAMING_SNAKE_CASE__  :					Optional[Any]						=start_index

            # Loop to check the observed code, stop when indentation diminishes or if we see a End copy comment.
            SCREAMING_SNAKE_CASE__  :					List[Any]						=True
            while line_index < len(_lowercase				) and should_continue:
                  line_index += 1
                  if line_index >= len(_lowercase				):
                        break
                  SCREAMING_SNAKE_CASE__  :					Optional[int]						=lines[line_index]
                  SCREAMING_SNAKE_CASE__  :					Tuple						=_should_continue(_lowercase,						_lowercase				) and re.search(f"^{indent}# End copy",						_lowercase				) is None
            # Clean up empty lines at the end (if any).
            while len(lines[line_index - 1]				) <= 1:
                  line_index -= 1

            SCREAMING_SNAKE_CASE__  :					Optional[int]						=lines[start_index:line_index]
            SCREAMING_SNAKE_CASE__  :					Tuple						="".join(_lowercase				)

            # Remove any nested `Copied from` comments to avoid circular copies
            SCREAMING_SNAKE_CASE__  :					Union[str, Any]						=[line for line in theoretical_code.split('''\n'''				) if _re_copy_warning.search(_lowercase				) is None]
            SCREAMING_SNAKE_CASE__  :					List[Any]						="\n".join(_lowercase				)

            # Before comparing, use the `replace_pattern` on the original code.
            if len(_lowercase				) > 0:
                  SCREAMING_SNAKE_CASE__  :					Optional[int]						=replace_pattern.replace('''with''',						''''''				).split(''','''				)
                  SCREAMING_SNAKE_CASE__  :					Optional[int]						=[_re_replace_pattern.search(_lowercase				) for p in patterns]
                  for pattern in patterns:
                        if pattern is None:
                              continue
                        SCREAMING_SNAKE_CASE__  :					List[str]						=pattern.groups()
                        SCREAMING_SNAKE_CASE__  :					Optional[int]						=re.sub(_lowercase,						_lowercase,						_lowercase				)
                        if option.strip() == "all-casing":
                              SCREAMING_SNAKE_CASE__  :					int						=re.sub(obja.lower(),						obja.lower(),						_lowercase				)
                              SCREAMING_SNAKE_CASE__  :					int						=re.sub(obja.upper(),						obja.upper(),						_lowercase				)

            # Blackify after replacement. To be able to do that, we need the header (class or function definition)
            # from the previous line
                  SCREAMING_SNAKE_CASE__  :					List[str]						=blackify(lines[start_index - 1] + theoretical_code				)
                  SCREAMING_SNAKE_CASE__  :					str						=theoretical_code[len(lines[start_index - 1]				) :]

            # Test for a diff and act accordingly.
            if observed_code != theoretical_code:
                  diffs.append([object_name, start_index]				)
                  if overwrite:
                        SCREAMING_SNAKE_CASE__  :					List[Any]						=lines[:start_index] + [theoretical_code] + lines[line_index:]
                        SCREAMING_SNAKE_CASE__  :					Tuple						=start_index + 1

      if overwrite and len(_lowercase				) > 0:
            # Warn the user a file has been modified.
            print(f"Detected changes, rewriting {filename}."				)
            with open(_lowercase,						'''w''',						encoding='''utf-8''',						newline='''\n'''				) as f:
                  f.writelines(_lowercase				)
      return diffs





def 			_a(	UpperCamelCase__					:    bool = False				):




      '''simple docstring'''






      SCREAMING_SNAKE_CASE__  :					Optional[int]						=glob.glob(os.path.join(_lowercase,						'''**/*.py'''				),						recursive=_lowercase				)
      SCREAMING_SNAKE_CASE__  :					Any						=[]
      for filename in all_files:
            SCREAMING_SNAKE_CASE__  :					List[Any]						=is_copy_consistent(_lowercase,						_lowercase				)
            diffs += [f"- {filename}: copy does not match {d[0]} at line {d[1]}" for d in new_diffs]
      if not overwrite and len(_lowercase				) > 0:
            SCREAMING_SNAKE_CASE__  :					List[str]						="\n".join(_lowercase				)
            raise Exception(
                '''Found the following copy inconsistencies:\n'''
                + diff
                + '''\nRun `make fix-copies` or `python utils/check_copies.py --fix_and_overwrite` to fix them.'''				)


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

  check_copies(args.fix_and_overwrite)






"""simple docstring"""




import unittest

import numpy as np

from transformers import RoFormerConfig, 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.roformer.modeling_flax_roformer import (
		    FlaxRoFormerForMaskedLM,
		    FlaxRoFormerForMultipleChoice,
		    FlaxRoFormerForQuestionAnswering,
		    FlaxRoFormerForSequenceClassification,
		    FlaxRoFormerForTokenClassification,
		    FlaxRoFormerModel,
		)


class 			__UpperCamelCase							(		unittest.TestCase		):






							def __init__(  self ,   lowerCAmelCase__ ,   lowerCAmelCase__=13 ,   lowerCAmelCase__=7 ,   lowerCAmelCase__=True ,   lowerCAmelCase__=True ,   lowerCAmelCase__=True ,   lowerCAmelCase__=True ,   lowerCAmelCase__=99 ,   lowerCAmelCase__=32 ,   lowerCAmelCase__=5 ,   lowerCAmelCase__=4 ,   lowerCAmelCase__=37 ,   lowerCAmelCase__="gelu" ,   lowerCAmelCase__=0.1 ,   lowerCAmelCase__=0.1 ,   lowerCAmelCase__=512 ,   lowerCAmelCase__=16 ,   lowerCAmelCase__=2 ,   lowerCAmelCase__=0.02 ,   lowerCAmelCase__=4 ,   )      ->					List[str]:
								a :						Any      =							parent
								a :						str      =							batch_size
								a :						str      =							seq_length
								a :						List[str]      =							is_training
								a :						Optional[int]      =							use_attention_mask
								a :						Optional[int]      =							use_token_type_ids
								a :						Union[str, Any]      =							use_labels
								a :						Optional[int]      =							vocab_size
								a :						Optional[Any]      =							hidden_size
								a :						List[Any]      =							num_hidden_layers
								a :						Optional[int]      =							num_attention_heads
								a :						Optional[int]      =							intermediate_size
								a :						Tuple      =							hidden_act
								a :						List[str]      =							hidden_dropout_prob
								a :						Optional[Any]      =							attention_probs_dropout_prob
								a :						List[Any]      =							max_position_embeddings
								a :						Optional[int]      =							type_vocab_size
								a :						Dict      =							type_sequence_label_size
								a :						int      =							initializer_range
								a :						Tuple      =							num_choices






							def        __a  (  self )      ->					List[Any]:
								a :						Dict      =							ids_tensor([self.batch_size, self.seq_length] ,   self.vocab_size )

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

								a :						List[str]      =							None
								if self.use_token_type_ids:
									a :						Dict      =							ids_tensor([self.batch_size, self.seq_length] ,   self.type_vocab_size )

								a :						Tuple      =							RoFormerConfig(
								    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=lowerCAmelCase__ ,   initializer_range=self.initializer_range ,   )

								return config, input_ids, token_type_ids, attention_mask






							def        __a  (  self )      ->					List[str]:
								a :						Dict      =							self.prepare_config_and_inputs()
								a,			a,			a,			a :						int      =							config_and_inputs
								a :						Dict      =							{"input_ids": input_ids, "token_type_ids": token_type_ids, "attention_mask": attention_mask}
								return config, inputs_dict


@require_flax
class 			__UpperCamelCase							(		a__						,			unittest.TestCase		):
							lowerCamelCase  :   Union[str, Any]    =True

							lowerCamelCase  :   Union[str, Any]    =(
							    (
							        FlaxRoFormerModel,
							        FlaxRoFormerForMaskedLM,
							        FlaxRoFormerForSequenceClassification,
							        FlaxRoFormerForTokenClassification,
							        FlaxRoFormerForMultipleChoice,
							        FlaxRoFormerForQuestionAnswering,
							    )
							    if is_flax_available()
							    else ()
							)






							def        __a  (  self )      ->					List[Any]:
								a :						Dict      =							FlaxRoFormerModelTester(self )






							@slow
							def        __a  (  self )      ->					List[str]:
								for model_class_name in self.all_model_classes:
									a :						Any      =							model_class_name.from_pretrained("junnyu/roformer_chinese_small" ,   from_pt=lowerCAmelCase__ )
									a :						Optional[int]      =							model(np.ones((1, 1) ) )
									self.assertIsNotNone(lowerCAmelCase__ )


@require_flax
class 			__UpperCamelCase							(		unittest.TestCase		):






							@slow
							def        __a  (  self )      ->					List[str]:
								a :						str      =							FlaxRoFormerForMaskedLM.from_pretrained("junnyu/roformer_chinese_base" )
								a :						List[Any]      =							jnp.array([[0, 1, 2, 3, 4, 5]] )
								a :						Any      =							model(lowerCAmelCase__ )[0]

								a :						int      =							5_0000

								a :						Any      =							(1, 6, vocab_size)
								self.assertEqual(output.shape ,   lowerCAmelCase__ )

								a :						List[Any]      =							jnp.array(
								    [[[-0.1_205, -1.0_265, 0.2_922], [-1.5_134, 0.1_974, 0.1_519], [-5.0_135, -3.9_003, -0.8_404]]] )

								self.assertTrue(jnp.allclose(output[:, :3, :3] ,   lowerCAmelCase__ ,   atol=1E-4 ) )


