

'''simple docstring'''



import argparse
import os
import re


# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_dummies.py
SCREAMING_SNAKE_CASE_    =   "src/transformers"

# Matches is_xxx_available()
SCREAMING_SNAKE_CASE_    =   re.compile(R"is\_([a-z_]*)_available()")
# Matches from xxx import bla
SCREAMING_SNAKE_CASE_    =   re.compile(R"\s+from\s+\S*\s+import\s+([^\(\s].*)\n")
SCREAMING_SNAKE_CASE_    =   re.compile(R"^\s+if\s+not\s+\(?is\_[a-z_]*\_available\(\)")


SCREAMING_SNAKE_CASE_    =   "\n{0} = None\n"

SCREAMING_SNAKE_CASE_    =   "\nclass {0}(metaclass=DummyObject):\n    _backends = {1}\n\n    def __init__(self, *args, **kwargs):\n        requires_backends(self, {1})\n"


SCREAMING_SNAKE_CASE_    =   "\ndef {0}(*args, **kwargs):\n    requires_backends({0}, {1})\n"

def   lowerCamelCase__       (      a__):



    """simple docstring"""







    if _re_test_backend.search(a__) is None:
        return None
    _snake_case : str												=		[b[0] for b in _re_backend.findall(a__)]
    backends.sort()
    return "_and_".join(a__)

def   lowerCamelCase__       (      ):



    """simple docstring"""







    with open(os.path.join(a__			,      '__init__.py')			,      'r'			,      encoding='utf-8'			,      newline='\n') as f:
        _snake_case : List[Any]												=		f.readlines()

    # Get to the point we do the actual imports for type checking
    _snake_case : str												=		0
    while not lines[line_index].startswith('if TYPE_CHECKING'):
        line_index += 1

    _snake_case : Any												=		{}
    # Go through the end of the file
    while line_index < len(a__):
        # If the line is an if is_backend_available, we grab all objects associated.
        _snake_case : Tuple												=		find_backend(lines[line_index])
        if backend is not None:
            while not lines[line_index].startswith('    else:'):
                line_index += 1
            line_index += 1

            _snake_case : List[str]												=		[]
            # Until we unindent, add backend objects to the list
            while len(lines[line_index]) <= 1 or lines[line_index].startswith(' ' * 8):
                _snake_case : int												=		lines[line_index]
                _snake_case : Optional[Any]												=		_re_single_line_import.search(a__)
                if single_line_import_search is not None:
                    objects.extend(single_line_import_search.groups()[0].split(', '))
                elif line.startswith(' ' * 1_2):
                    objects.append(line[1_2:-2])
                line_index += 1

            _snake_case : Tuple												=		objects
        else:
            line_index += 1

    return backend_specific_objects

def   lowerCamelCase__       (      a__			,      a__):



    """simple docstring"""







    if name.isupper():
        return DUMMY_CONSTANT.format(a__)
    elif name.islower():
        return DUMMY_FUNCTION.format(a__			,      a__)
    else:
        return DUMMY_CLASS.format(a__			,      a__)

def   lowerCamelCase__       (      a__=None):



    """simple docstring"""







    if backend_specific_objects is None:
        _snake_case : Union[str, Any]												=		read_init()
    # For special correspondence backend to module name as used in the function requires_modulename
    _snake_case : Any												=		{}

    for backend, objects in backend_specific_objects.items():
        _snake_case : Any												=		'[' + ', '.join(F"""\"{b}\"""" for b in backend.split('_and_')) + ']'
        _snake_case : List[str]												=		'# This file is autogenerated by the command `make fix-copies`, do not edit.\n'
        dummy_file += "from ..utils import DummyObject, requires_backends\n\n"
        dummy_file += "\n".join([create_dummy_object(a__			,      a__) for o in objects])
        _snake_case : Optional[int]												=		dummy_file

    return dummy_files

def   lowerCamelCase__       (      a__=False):



    """simple docstring"""







    _snake_case : Dict												=		create_dummy_files()
    # For special correspondence backend to shortcut as used in utils/dummy_xxx_objects.py
    _snake_case : Optional[Any]												=		{'torch': 'pt'}

    # Locate actual dummy modules and read their content.
    _snake_case : List[str]												=		os.path.join(a__			,      'utils')
    _snake_case : List[Any]												=		{
        backend: os.path.join(a__			,      F"""dummy_{short_names.get(a__			,      a__)}_objects.py""")
        for backend in dummy_files.keys()
    }

    _snake_case : int												=		{}
    for backend, file_path in dummy_file_paths.items():
        if os.path.isfile(a__):
            with open(a__			,      'r'			,      encoding='utf-8'			,      newline='\n') as f:
                _snake_case : Union[str, Any]												=		f.read()
        else:
            _snake_case : Optional[int]												=		''

    for backend in dummy_files.keys():
        if dummy_files[backend] != actual_dummies[backend]:
            if overwrite:
                print(
                    F"""Updating transformers.utils.dummy_{short_names.get(a__			,      a__)}_objects.py as the main """
                    '__init__ has new objects.')
                with open(dummy_file_paths[backend]			,      'w'			,      encoding='utf-8'			,      newline='\n') as f:
                    f.write(dummy_files[backend])
            else:
                raise ValueError(
                    'The main __init__ has objects that are not present in '
                    F"""transformers.utils.dummy_{short_names.get(a__			,      a__)}_objects.py. Run `make fix-copies` """
                    'to fix this.')


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

   check_dummies(args.fix_and_overwrite)






'''simple docstring'''



import copy

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


SCREAMING_SNAKE_CASE_    =   logging.get_logger(__name__)

SCREAMING_SNAKE_CASE_    =   {}

class 			SCREAMING_SNAKE_CASE					(							lowercase_					):






      '''simple docstring'''






      SCREAMING_SNAKE_CASE__ :				Optional[Any]    =				'''fsmt_decoder'''




      def __init__(					self :		Any     ,					snake_case :		int=0     ,					snake_case :		Dict=0   ):



          """simple docstring"""





          super().__init__()
          _snake_case : int												=		vocab_size
          _snake_case : Dict												=		bos_token_id



class 			SCREAMING_SNAKE_CASE					(							lowercase_					):






      '''simple docstring'''






      SCREAMING_SNAKE_CASE__ :				Union[str, Any]    =				'''fsmt'''
      SCREAMING_SNAKE_CASE__ :				Union[str, Any]    =				{'''num_attention_heads''': '''encoder_attention_heads''', '''hidden_size''': '''d_model'''}




      def __init__(					self :		Optional[int]     ,					snake_case :		Tuple=["en", "de"]     ,					snake_case :		Optional[int]=42024     ,					snake_case :		List[str]=42024     ,					snake_case :		Union[str, Any]="relu"     ,					snake_case :		Optional[Any]=1024     ,					snake_case :		Union[str, Any]=200     ,					snake_case :		int=1024     ,					snake_case :		str=4096     ,					snake_case :		Dict=12     ,					snake_case :		str=16     ,					snake_case :		List[str]=0.0     ,					snake_case :		List[Any]=4096     ,					snake_case :		str=12     ,					snake_case :		str=16     ,					snake_case :		Optional[int]=0.0     ,					snake_case :		Optional[int]=0.0     ,					snake_case :		str=0.1     ,					snake_case :		Tuple=0.0     ,					snake_case :		Optional[int]=0.02     ,					snake_case :		List[str]=2     ,					snake_case :		int=True     ,					snake_case :		Any=True     ,					snake_case :		str=False     ,					snake_case :		Union[str, Any]=5     ,					snake_case :		Dict=1.0     ,					snake_case :		Union[str, Any]=False     ,					snake_case :		Optional[Any]=True     ,					snake_case :		Optional[int]=1     ,					snake_case :		int=0     ,					snake_case :		Optional[int]=2     ,					snake_case :		Optional[Any]=2     ,					**snake_case :		Any     ,					):



          """simple docstring"""





          _snake_case : int												=		langs
          _snake_case : str												=		src_vocab_size
          _snake_case : List[Any]												=		tgt_vocab_size
          _snake_case : Optional[int]												=		d_model  # encoder_embed_dim and decoder_embed_dim

          _snake_case : Optional[Any]												=		encoder_ffn_dim
          _snake_case : Dict												=		encoder_layers
          _snake_case : List[Any]												=		encoder_attention_heads
          _snake_case : Any												=		encoder_layerdrop
          _snake_case : List[str]												=		decoder_layerdrop
          _snake_case : str												=		decoder_ffn_dim
          _snake_case : Union[str, Any]												=		decoder_layers
          _snake_case : Tuple												=		decoder_attention_heads
          _snake_case : str												=		max_position_embeddings
          _snake_case : Dict												=		init_std  # Normal(0, this parameter)
          _snake_case : List[str]												=		activation_function

          _snake_case : Any												=		DecoderConfig(vocab_size=snake_case     ,					bos_token_id=snake_case   )
          if "decoder" in common_kwargs:
              del common_kwargs["decoder"]

          _snake_case : str												=		scale_embedding  # scale factor will be sqrt(d_model) if True

          # 3 Types of Dropout
          _snake_case : int												=		attention_dropout
          _snake_case : List[Any]												=		activation_dropout
          _snake_case : Optional[int]												=		dropout

          _snake_case : Union[str, Any]												=		use_cache
          super().__init__(
              pad_token_id=snake_case     ,					bos_token_id=snake_case     ,					eos_token_id=snake_case     ,					decoder_start_token_id=snake_case     ,					is_encoder_decoder=snake_case     ,					tie_word_embeddings=snake_case     ,					forced_eos_token_id=snake_case     ,					max_length=snake_case     ,					num_beams=snake_case     ,					length_penalty=snake_case     ,					early_stopping=snake_case     ,					**snake_case     ,					)




      def 	__UpperCAmelCase			(					self :		Optional[int]   ):



          """simple docstring"""





          _snake_case : Any												=		copy.deepcopy(self.__dict__   )
          _snake_case : str												=		self.decoder.to_dict()
          _snake_case : Dict												=		self.__class__.model_type
          return output



