



from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxSeqaSeqConfigWithPast
from ...utils import logging


if TYPE_CHECKING:
	from ...feature_extraction_utils import FeatureExtractionMixin
	from ...tokenization_utils_base import PreTrainedTokenizerBase
	from ...utils import TensorType

a      :  List[str]			     =			logging.get_logger(__name__)

a      :  Tuple			     =			{
    'openai/whisper-base': 'https://huggingface.co/openai/whisper-base/resolve/main/config.json',
}

# fmt: off
a      :  List[Any]			     =			[
    1, 2, 7, 8, 9, 10, 14, 25,
    26, 27, 28, 29, 31, 58, 59, 60, 61, 62,
    63, 90, 91, 92, 93, 357, 366, 438, 532, 685,
    705, 796, 930, 1_058, 1_220, 1_267, 1_279, 1_303, 1_343, 1_377,
    1_391, 1_635, 1_782, 1_875, 2_162, 2_361, 2_488, 3_467, 4_008, 4_211,
    4_600, 4_808, 5_299, 5_855, 6_329, 7_203, 9_609, 9_959, 10_563, 10_786,
    11_420, 11_709, 11_907, 13_163, 13_697, 13_700, 14_808, 15_306, 16_410, 16_791,
    17_992, 19_203, 19_510, 20_724, 22_305, 22_935, 27_007, 30_109, 30_420, 33_409,
    34_949, 40_283, 40_493, 40_549, 47_282, 49_146, 50_257, 50_359, 50_360, 50_361
]
a      :  str			     =			[
    1, 2, 7, 8, 9, 10, 14, 25,
    26, 27, 28, 29, 31, 58, 59, 60, 61, 62,
    63, 90, 91, 92, 93, 359, 503, 522, 542, 873,
    893, 902, 918, 922, 931, 1_350, 1_853, 1_982, 2_460, 2_627,
    3_246, 3_253, 3_268, 3_536, 3_846, 3_961, 4_183, 4_667, 6_585, 6_647,
    7_273, 9_061, 9_383, 10_428, 10_929, 11_938, 12_033, 12_331, 12_562, 13_793,
    14_157, 14_635, 15_265, 15_618, 16_553, 16_604, 18_362, 18_956, 20_075, 21_675,
    22_520, 26_130, 26_161, 26_435, 28_279, 29_464, 31_650, 32_302, 32_470, 36_865,
    42_863, 47_425, 49_870, 50_254, 50_258, 50_360, 50_361, 50_362
]







class 				_a				(   _lowerCAmelCase					):
			A      		=	'''whisper'''
			A      		=	['''past_key_values''']
			A      		=	{'''num_attention_heads''': '''encoder_attention_heads''', '''hidden_size''': '''d_model'''}

			def __init__(self,   SCREAMING_SNAKE_CASE_=51865,   SCREAMING_SNAKE_CASE_=80,   SCREAMING_SNAKE_CASE_=6,   SCREAMING_SNAKE_CASE_=4,   SCREAMING_SNAKE_CASE_=6,   SCREAMING_SNAKE_CASE_=4,   SCREAMING_SNAKE_CASE_=1536,   SCREAMING_SNAKE_CASE_=1536,   SCREAMING_SNAKE_CASE_=0.0,   SCREAMING_SNAKE_CASE_=0.0,   SCREAMING_SNAKE_CASE_=50257,   SCREAMING_SNAKE_CASE_=True,   SCREAMING_SNAKE_CASE_=True,   SCREAMING_SNAKE_CASE_="gelu",   SCREAMING_SNAKE_CASE_=256,   SCREAMING_SNAKE_CASE_=0.0,   SCREAMING_SNAKE_CASE_=0.0,   SCREAMING_SNAKE_CASE_=0.0,   SCREAMING_SNAKE_CASE_=0.0_2,   SCREAMING_SNAKE_CASE_=False,   SCREAMING_SNAKE_CASE_=1500,   SCREAMING_SNAKE_CASE_=448,   SCREAMING_SNAKE_CASE_=50256,   SCREAMING_SNAKE_CASE_=50256,   SCREAMING_SNAKE_CASE_=50256,   SCREAMING_SNAKE_CASE_=None,   SCREAMING_SNAKE_CASE_=[220, 50256],   SCREAMING_SNAKE_CASE_=False,   SCREAMING_SNAKE_CASE_=256,   SCREAMING_SNAKE_CASE_=False,   SCREAMING_SNAKE_CASE_=0.0_5,   SCREAMING_SNAKE_CASE_=10,   SCREAMING_SNAKE_CASE_=2,   SCREAMING_SNAKE_CASE_=0.0,   SCREAMING_SNAKE_CASE_=10,   SCREAMING_SNAKE_CASE_=0,   SCREAMING_SNAKE_CASE_=7,   **SCREAMING_SNAKE_CASE_,   )       ->   List[Any]:
						UpperCAmelCase_:		Tuple							      =     vocab_size
						UpperCAmelCase_:		str							      =     num_mel_bins
						UpperCAmelCase_:		Dict							      =     d_model
						UpperCAmelCase_:		Optional[Any]							      =     encoder_layers
						UpperCAmelCase_:		str							      =     encoder_attention_heads
						UpperCAmelCase_:		Dict							      =     decoder_layers
						UpperCAmelCase_:		List[Any]							      =     decoder_attention_heads
						UpperCAmelCase_:		List[str]							      =     decoder_ffn_dim
						UpperCAmelCase_:		Union[str, Any]							      =     encoder_ffn_dim
						UpperCAmelCase_:		Any							      =     dropout
						UpperCAmelCase_:		Dict							      =     attention_dropout
						UpperCAmelCase_:		Optional[int]							      =     activation_dropout
						UpperCAmelCase_:		str							      =     activation_function
						UpperCAmelCase_:		Tuple							      =     init_std
						UpperCAmelCase_:		int							      =     encoder_layerdrop
						UpperCAmelCase_:		List[Any]							      =     decoder_layerdrop
						UpperCAmelCase_:		Optional[Any]							      =     use_cache
						UpperCAmelCase_:		List[Any]							      =     encoder_layers
						UpperCAmelCase_:		Any							      =     scale_embedding  # scale factor will be sqrt(d_model) if True
						UpperCAmelCase_:		Tuple							      =     max_source_positions
						UpperCAmelCase_:		Optional[int]							      =     max_target_positions

						# Audio Classification-specific parameters. Feel free to ignore for other classes.
						UpperCAmelCase_:		Dict							      =     classifier_proj_size
						UpperCAmelCase_:		List[Any]							      =     use_weighted_layer_sum

						# fine-tuning config parameters for SpecAugment: https://arxiv.org/abs/1904.08779
						UpperCAmelCase_:		Any							      =     apply_spec_augment
						UpperCAmelCase_:		Optional[Any]							      =     mask_time_prob
						UpperCAmelCase_:		Union[str, Any]							      =     mask_time_length
						UpperCAmelCase_:		Dict							      =     mask_time_min_masks
						UpperCAmelCase_:		str							      =     mask_feature_prob
						UpperCAmelCase_:		str							      =     mask_feature_length
						UpperCAmelCase_:		Optional[Any]							      =     mask_feature_min_masks

						UpperCAmelCase_:		Optional[Any]							      =     median_filter_width

						super().__init__(
						    pad_token_id=A_,   bos_token_id=A_,   eos_token_id=A_,   is_encoder_decoder=A_,   decoder_start_token_id=A_,   suppress_tokens=A_,   begin_suppress_tokens=A_,   **A_,   )







class 				_a				(   _lowerCAmelCase					):

			@property
			def      __snake_case       (self					)       ->   Union[str, Any]:
						UpperCAmelCase_:		Optional[Any]							      =     OrderedDict(
						    [
						        ("""input_features""", {0: """batch""", 1: """feature_size""", 2: """encoder_sequence"""}),
						    ]					)
						if self.use_past:
									UpperCAmelCase_:		str							      =     {0: """batch"""}
						else:
									UpperCAmelCase_:		Optional[int]							      =     {0: """batch""", 1: """decoder_sequence"""}

						if self.use_past:
									self.fill_with_past_key_values_(A_,   direction="""inputs"""					)

						return common_inputs

			def      __snake_case       (self,   SCREAMING_SNAKE_CASE_,   SCREAMING_SNAKE_CASE_ = -1,   SCREAMING_SNAKE_CASE_ = -1,   SCREAMING_SNAKE_CASE_ = False,   SCREAMING_SNAKE_CASE_ = None,   SCREAMING_SNAKE_CASE_ = 22050,   SCREAMING_SNAKE_CASE_ = 5.0,   SCREAMING_SNAKE_CASE_ = 220,   )       ->   Optional[Any]:
						UpperCAmelCase_:		int							      =     OrderedDict()
						UpperCAmelCase_:		Any							      =     OnnxConfig.generate_dummy_inputs(
						    self,   preprocessor=preprocessor.feature_extractor,   batch_size=A_,   framework=A_,   sampling_rate=A_,   time_duration=A_,   frequency=A_,   )
						UpperCAmelCase_:		List[str]							      =     encoder_inputs["""input_features"""].shape[2]
						UpperCAmelCase_:		Optional[Any]							      =     encoder_sequence_length // 2 if self.use_past else seq_length

						UpperCAmelCase_:		str							      =     super().generate_dummy_inputs(
						    preprocessor.tokenizer,   A_,   A_,   A_,   A_					)

						UpperCAmelCase_:		str							      =     encoder_inputs.pop("""input_features"""					)
						UpperCAmelCase_:		Optional[int]							      =     decoder_inputs.pop("""decoder_input_ids"""					)

						if "past_key_values" in decoder_inputs:
									UpperCAmelCase_:		Optional[Any]							      =     decoder_inputs.pop("""past_key_values"""					)

						return dummy_inputs

			@property
			def      __snake_case       (self					)       ->   str:
						return 1E-3










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


SCREAMING_SNAKE_CASE__					:     List[Any]       =     'src/transformers'


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




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




def    a__    (		snake_case__					:							Optional[int]     ):
  with open(snake_case__						,   """r"""						,   encoding="""utf-8"""						,   newline="""\n"""     ) as f:
    _UpperCAmelCase		:							Optional[Any]							=     f.readlines()

  _UpperCAmelCase		:							int							=     0
  while line_index < len(snake_case__     ) and not lines[line_index].startswith("""_import_structure = {"""     ):
    line_index += 1

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

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

  _UpperCAmelCase		:							str							=     {"""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.
    _UpperCAmelCase		:							Tuple							=     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:
      _UpperCAmelCase		:							List[Any]							=     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

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

      _UpperCAmelCase		:							str							=     objects
    else:
      line_index += 1

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

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

      _UpperCAmelCase		:							Dict							=     []
      # Until we unindent, add backend objects to the list
      while len(lines[line_index]     ) <= 1 or lines[line_index].startswith(""" """ * 8     ):
        _UpperCAmelCase		:							Union[str, Any]							=     lines[line_index]
        _UpperCAmelCase		:							Any							=     _re_import.search(snake_case__     )
        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

      _UpperCAmelCase		:							str							=     objects
    else:
      line_index += 1

  return import_dict_objects, type_hint_objects




def    a__    (		snake_case__					:							Any						,   snake_case__					:							Optional[int]     ):

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

  _UpperCAmelCase		:							int							=     []
  for key in import_dict_objects.keys():
    _UpperCAmelCase		:							Any							=     find_duplicates(import_dict_objects[key]     )
    if duplicate_imports:
      errors.append(f'''Duplicate _import_structure definitions for: {duplicate_imports}'''     )
    _UpperCAmelCase		:							Optional[int]							=     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]     )     ):
      _UpperCAmelCase		:							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__    (		):
  _UpperCAmelCase		:							Any							=     []
  for root, _, files in os.walk(snake_case__     ):
    if "__init__.py" in files:
      _UpperCAmelCase		:							Optional[Any]							=     os.path.join(snake_case__						,   """__init__.py"""     )
      _UpperCAmelCase		:							List[str]							=     parse_init(snake_case__     )
      if objects is not None:
        _UpperCAmelCase		:							int							=     analyze_results(*snake_case__     )
        if len(snake_case__     ) > 0:
          _UpperCAmelCase		:							Union[str, Any]							=     f'''Problem in {fname}, both halves do not define the same objects.\n{errors[0]}'''
          failures.append("""\n""".join(snake_case__     )     )
  if len(snake_case__     ) > 0:
    raise ValueError("""\n\n""".join(snake_case__     )     )




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


SCREAMING_SNAKE_CASE__					:     List[Any]       =     [
    'convert_pytorch_checkpoint_to_tf2',
    'modeling_flax_pytorch_utils',
]




def    a__    (		):
  # This is to make sure the transformers module imported is the one in the repo.
  _UpperCAmelCase		:							int							=     importlib.util.spec_from_file_location(
      """transformers"""						,   os.path.join(snake_case__						,   """__init__.py"""     )						,   submodule_search_locations=[PATH_TO_TRANSFORMERS]						,   )
  _UpperCAmelCase		:							Optional[int]							=     spec.loader.load_module()

  _UpperCAmelCase		:							int							=     [
      module
      for module in get_transformers_submodules()
      if module not in IGNORE_SUBMODULES and module not in transformers._import_structure.keys()
  ]
  if len(snake_case__     ) > 0:
    _UpperCAmelCase		:							Dict							=     """\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()





