




"""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 		_snake_case	(   _snake_case				:   Union[str, Any]							,    _snake_case				:   int				)       ->   Union[str, Any]:






      '''simple docstring'''


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






def 		_snake_case	(   _snake_case				:   Optional[int]				)       ->   int:






      '''simple docstring'''


      _A     =  object_name.split('.'				)
      _A     =  0

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

      with open(os.path.join(_snake_case							,    F'''{module}.py'''				)							,    'r'							,    encoding='utf-8'							,    newline='\n'				) as f:
            _A     =  f.readlines()

      # Now let's find the class / func in the code!
      _A     =  ''
      _A     =  0
      for name in parts[i + 1 :]:
            while (
                line_index < len(_snake_case				) 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(_snake_case				):
            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).
      _A     =  line_index
      while line_index < len(_snake_case				) and _should_continue(lines[line_index]							,    _snake_case				):
            line_index += 1
      # Clean up empty lines at the end (if any).
      while len(lines[line_index - 1]				) <= 1:
            line_index -= 1

      _A     =  lines[start_index:line_index]
      return "".join(_snake_case				)


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 		_snake_case	(   _snake_case				:   Optional[int]				)       ->   Any:






      '''simple docstring'''


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






def 		_snake_case	(   _snake_case				:   Union[str, Any]				)       ->   List[Any]:






      '''simple docstring'''


      _A     =  len(get_indent(_snake_case				)				) > 0
      if has_indent:
            _A     =  F'''class Bla:\n{code}'''
      _A     =  black.Mode(target_versions={black.TargetVersion.PYaa}							,    line_length=1_19							,    preview=_snake_case				)
      _A     =  black.format_str(_snake_case							,    mode=_snake_case				)
      _A  ,       _A     =  style_docstrings_in_code(_snake_case				)
      return result[len('class Bla:\n'				) :] if has_indent else result






def 		_snake_case	(   _snake_case				:   Tuple							,    _snake_case				:   List[Any]=False				)       ->   Tuple:






      '''simple docstring'''


      with open(_snake_case							,    'r'							,    encoding='utf-8'							,    newline='\n'				) as f:
            _A     =  f.readlines()
      _A     =  []
      _A     =  0
      # Not a for loop cause `lines` is going to change (if `overwrite=True`).
      while line_index < len(_snake_case				):
            _A     =  _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.
            _A  ,       _A  ,       _A     =  search.groups()
            _A     =  find_code_in_diffusers(_snake_case				)
            _A     =  get_indent(_snake_case				)

            _A     =  line_index + 1 if indent == theoretical_indent else line_index + 2
            _A     =  theoretical_indent
            _A     =  start_index

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

            _A     =  lines[start_index:line_index]
            _A     =  ''.join(_snake_case				)

            # Remove any nested `Copied from` comments to avoid circular copies
            _A     =  [line for line in theoretical_code.split('\n'				) if _re_copy_warning.search(_snake_case				) is None]
            _A     =  '\n'.join(_snake_case				)

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

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

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






def 		_snake_case	(   _snake_case				:   bool = False				)       ->   Optional[Any]:






      '''simple docstring'''


      _A     =  glob.glob(os.path.join(_snake_case							,    '**/*.py'				)							,    recursive=_snake_case				)
      _A     =  []
      for filename in all_files:
            _A     =  is_copy_consistent(_snake_case							,    _snake_case				)
            diffs += [F'''- {filename}: copy does not match {d[0]} at line {d[1]}''' for d in new_diffs]
      if not overwrite and len(_snake_case				) > 0:
            _A     =  '\n'.join(_snake_case				)
            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"""

from ...configuration_utils import PretrainedConfig
from ...utils import logging


a							      =     logging.get_logger(__name__)

a							      =     {
    '''facebook/s2t-small-librispeech-asr''': (
        '''https://huggingface.co/facebook/s2t-small-librispeech-asr/resolve/main/config.json'''
    ),
    # See all Speech2Text models at https://huggingface.co/models?filter=speech_to_text
}





class 							lowercase_			(	__lowerCAmelCase				):



 '''simple docstring'''
 UpperCAmelCase       :	str     =      '''speech_to_text'''
 UpperCAmelCase       :	List[Any]     =      ['''past_key_values''']
 UpperCAmelCase       :	Tuple     =      {'''num_attention_heads''': '''encoder_attention_heads''', '''hidden_size''': '''d_model'''}

 def __init__(					self			:			int       ,				_UpperCAmelCase			:			Union[str, Any]=10_000       ,				_UpperCAmelCase			:			Tuple=12       ,				_UpperCAmelCase			:			int=2_048       ,				_UpperCAmelCase			:			Optional[Any]=4       ,				_UpperCAmelCase			:			List[str]=6       ,				_UpperCAmelCase			:			Tuple=2_048       ,				_UpperCAmelCase			:			str=4       ,				_UpperCAmelCase			:			int=0.0       ,				_UpperCAmelCase			:			Dict=0.0       ,				_UpperCAmelCase			:			Optional[int]=True       ,				_UpperCAmelCase			:			Optional[Any]=True       ,				_UpperCAmelCase			:			Union[str, Any]="relu"       ,				_UpperCAmelCase			:			List[Any]=256       ,				_UpperCAmelCase			:			Optional[int]=0.1       ,				_UpperCAmelCase			:			Any=0.0       ,				_UpperCAmelCase			:			Dict=0.0       ,				_UpperCAmelCase			:			str=0.02       ,				_UpperCAmelCase			:			Any=2       ,				_UpperCAmelCase			:			Dict=True       ,				_UpperCAmelCase			:			List[str]=1       ,				_UpperCAmelCase			:			Tuple=0       ,				_UpperCAmelCase			:			Tuple=2       ,				_UpperCAmelCase			:			List[str]=6_000       ,				_UpperCAmelCase			:			Optional[Any]=1_024       ,				_UpperCAmelCase			:			Optional[Any]=2       ,				_UpperCAmelCase			:			Any=(5, 5)       ,				_UpperCAmelCase			:			int=1_024       ,				_UpperCAmelCase			:			str=80       ,				_UpperCAmelCase			:			Any=1       ,				**_UpperCAmelCase			:			Tuple       ,				):
       _A     =  vocab_size
       _A     =  d_model
       _A     =  encoder_ffn_dim
       _A     =  encoder_layers
       _A     =  encoder_attention_heads
       _A     =  decoder_ffn_dim
       _A     =  decoder_layers
       _A     =  decoder_attention_heads
       _A     =  dropout
       _A     =  attention_dropout
       _A     =  activation_dropout
       _A     =  activation_function
       _A     =  init_std
       _A     =  encoder_layerdrop
       _A     =  decoder_layerdrop
       _A     =  use_cache
       _A     =  encoder_layers
       _A     =  scale_embedding  # scale factor will be sqrt(d_model) if True
       _A     =  max_source_positions
       _A     =  max_target_positions
       _A     =  num_conv_layers
       _A     =  list(_UpperCAmelCase						)
       _A     =  conv_channels
       _A     =  input_feat_per_channel
       _A     =  input_channels

       if len(self.conv_kernel_sizes						) != self.num_conv_layers:
             raise ValueError(
                 'Configuration for convolutional module is incorrect. '
                 'It is required that `len(config.conv_kernel_sizes)` == `config.num_conv_layers` '
                 F'''but is `len(config.conv_kernel_sizes) = {len(self.conv_kernel_sizes						)}`, '''
                 F'''`config.num_conv_layers = {self.num_conv_layers}`.'''						)

       super().__init__(
           pad_token_id=_UpperCAmelCase       ,				bos_token_id=_UpperCAmelCase       ,				eos_token_id=_UpperCAmelCase       ,				is_encoder_decoder=_UpperCAmelCase       ,				decoder_start_token_id=_UpperCAmelCase       ,				**_UpperCAmelCase       ,				)

