





'''simple docstring'''






from typing import List, Union

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


A__       :     int          =logging.get_logger(__name__)

A__       :     Any          ={
    '''allenai/led-base-16384''': '''https://huggingface.co/allenai/led-base-16384/resolve/main/config.json''',
    # See all LED models at https://huggingface.co/models?filter=led
}




class 				UpperCAmelCase  (    snake_case_     ):
      _lowercase:    Optional[Any]		  =     '''led'''
      _lowercase:    Optional[Any]		  =     {
          '''num_attention_heads''': '''encoder_attention_heads''',
          '''hidden_size''': '''d_model''',
          '''attention_probs_dropout_prob''': '''attention_dropout''',
          '''initializer_range''': '''init_std''',
      }




      def __init__(    self    :				str    ,    __snake_case    :				Optional[int]=5_02_65    ,    __snake_case    :				Dict=1_63_84    ,    __snake_case    :				Optional[Any]=10_24    ,    __snake_case    :				Dict=12    ,    __snake_case    :				Dict=40_96    ,    __snake_case    :				List[Any]=16    ,    __snake_case    :				Dict=12    ,    __snake_case    :				str=40_96    ,    __snake_case    :				Union[str, Any]=16    ,    __snake_case    :				List[Any]=0.0    ,    __snake_case    :				Optional[int]=0.0    ,    __snake_case    :				Union[str, Any]=True    ,    __snake_case    :				int=True    ,    __snake_case    :				str="gelu"    ,    __snake_case    :				Tuple=10_24    ,    __snake_case    :				Dict=0.1    ,    __snake_case    :				str=0.0    ,    __snake_case    :				Dict=0.0    ,    __snake_case    :				List[str]=0.02    ,    __snake_case    :				Union[str, Any]=2    ,    __snake_case    :				Optional[int]=0.0    ,    __snake_case    :				List[str]=1    ,    __snake_case    :				List[Any]=0    ,    __snake_case    :				Tuple=2    ,    __snake_case    :				Union[List[int], int] = 5_12    ,    **__snake_case    :				Dict    ,    )       ->   Dict:
            _lowerCAmelCase							  =							vocab_size
            _lowerCAmelCase							  =							max_encoder_position_embeddings
            _lowerCAmelCase							  =							max_decoder_position_embeddings
            _lowerCAmelCase							  =							d_model
            _lowerCAmelCase							  =							encoder_ffn_dim
            _lowerCAmelCase							  =							encoder_layers
            _lowerCAmelCase							  =							encoder_attention_heads
            _lowerCAmelCase							  =							decoder_ffn_dim
            _lowerCAmelCase							  =							decoder_layers
            _lowerCAmelCase							  =							decoder_attention_heads
            _lowerCAmelCase							  =							dropout
            _lowerCAmelCase							  =							attention_dropout
            _lowerCAmelCase							  =							activation_dropout
            _lowerCAmelCase							  =							activation_function
            _lowerCAmelCase							  =							init_std
            _lowerCAmelCase							  =							encoder_layerdrop
            _lowerCAmelCase							  =							decoder_layerdrop
            _lowerCAmelCase							  =							classifier_dropout
            _lowerCAmelCase							  =							use_cache
            _lowerCAmelCase							  =							encoder_layers
            _lowerCAmelCase							  =							attention_window

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













'''simple docstring'''






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


A__       :     Tuple          ={
    '''configuration_oneformer''': ['''ONEFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''OneFormerConfig'''],
    '''processing_oneformer''': ['''OneFormerProcessor'''],
}

try:
      if not is_vision_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      A__       :     List[str]          =['''OneFormerImageProcessor''']

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      A__       :     Dict          =[
          '''ONEFORMER_PRETRAINED_MODEL_ARCHIVE_LIST''',
          '''OneFormerForUniversalSegmentation''',
          '''OneFormerModel''',
          '''OneFormerPreTrainedModel''',
      ]

if TYPE_CHECKING:
      from .configuration_oneformer import ONEFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, OneFormerConfig
      from .processing_oneformer import OneFormerProcessor

      try:
            if not is_vision_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .image_processing_oneformer import OneFormerImageProcessor
      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_oneformer import (
                ONEFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
                OneFormerForUniversalSegmentation,
                OneFormerModel,
                OneFormerPreTrainedModel,
            )


else:
      import sys

      A__       :     Optional[Any]          =_LazyModule(__name__, globals()['''__file__'''], _import_structure)






