



'''simple docstring'''





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


_lowerCAmelCase      						=	logging.get_logger(__name__)

_lowerCAmelCase      						=	{
    '''google/fnet-base''': '''https://huggingface.co/google/fnet-base/resolve/main/config.json''',
    '''google/fnet-large''': '''https://huggingface.co/google/fnet-large/resolve/main/config.json'''
    # See all FNet models at https://huggingface.co/models?filter=fnet
}






class        lowerCAmelCase_(				SCREAMING_SNAKE_CASE_     ):
  '''simple docstring'''




  __lowercase							:      Optional[Any]				=      '''fnet'''




  def __init__(    self  ,__UpperCAmelCase=3_2000  ,__UpperCAmelCase=768  ,__UpperCAmelCase=12  ,__UpperCAmelCase=3072  ,__UpperCAmelCase="gelu_new"  ,__UpperCAmelCase=0.1  ,__UpperCAmelCase=512  ,__UpperCAmelCase=4  ,__UpperCAmelCase=0.0_2  ,__UpperCAmelCase=1E-12  ,__UpperCAmelCase=False  ,__UpperCAmelCase=512  ,__UpperCAmelCase=3  ,__UpperCAmelCase=1  ,__UpperCAmelCase=2  ,**__UpperCAmelCase  ,)    ->		str:
      super().__init__(pad_token_id=__UpperCAmelCase  ,bos_token_id=__UpperCAmelCase  ,eos_token_id=__UpperCAmelCase  ,**__UpperCAmelCase      )

      lowerCAmelCase__ :  Optional[Any]							      =					vocab_size
      lowerCAmelCase__ :  Union[str, Any]							      =					max_position_embeddings
      lowerCAmelCase__ :  Tuple							      =					hidden_size
      lowerCAmelCase__ :  List[Any]							      =					num_hidden_layers
      lowerCAmelCase__ :  Dict							      =					intermediate_size
      lowerCAmelCase__ :  str							      =					hidden_act
      lowerCAmelCase__ :  str							      =					hidden_dropout_prob
      lowerCAmelCase__ :  List[str]							      =					initializer_range
      lowerCAmelCase__ :  str							      =					type_vocab_size
      lowerCAmelCase__ :  Optional[int]							      =					layer_norm_eps
      lowerCAmelCase__ :  int							      =					use_tpu_fourier_optimizations
      lowerCAmelCase__ :  int							      =					tpu_short_seq_length






"""simple docstring"""


A     :   int			    =			{
    "Pillow": "Pillow",
    "accelerate": "accelerate>=0.11.0",
    "compel": "compel==0.1.8",
    "black": "black~=23.1",
    "datasets": "datasets",
    "filelock": "filelock",
    "flax": "flax>=0.4.1",
    "hf-doc-builder": "hf-doc-builder>=0.3.0",
    "huggingface-hub": "huggingface-hub>=0.13.2",
    "requests-mock": "requests-mock==1.10.0",
    "importlib_metadata": "importlib_metadata",
    "invisible-watermark": "invisible-watermark",
    "isort": "isort>=5.5.4",
    "jax": "jax>=0.2.8,!=0.3.2",
    "jaxlib": "jaxlib>=0.1.65",
    "Jinja2": "Jinja2",
    "k-diffusion": "k-diffusion>=0.0.12",
    "torchsde": "torchsde",
    "note_seq": "note_seq",
    "librosa": "librosa",
    "numpy": "numpy",
    "omegaconf": "omegaconf",
    "parameterized": "parameterized",
    "protobuf": "protobuf>=3.20.3,<4",
    "pytest": "pytest",
    "pytest-timeout": "pytest-timeout",
    "pytest-xdist": "pytest-xdist",
    "ruff": "ruff>=0.0.241",
    "safetensors": "safetensors",
    "sentencepiece": "sentencepiece>=0.1.91,!=0.1.92",
    "scipy": "scipy",
    "onnx": "onnx",
    "regex": "regex!=2019.12.17",
    "requests": "requests",
    "tensorboard": "tensorboard",
    "torch": "torch>=1.4",
    "torchvision": "torchvision",
    "transformers": "transformers>=4.25.1",
    "urllib3": "urllib3<=2.0.0",
}




