


from typing import List, Union

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


snake_case			:      Dict 							=   logging.get_logger(__name__)

snake_case			:      Tuple 							=   {
    '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    __lowercase  (       UpperCamelCase							):

							"""simple docstring"""


							SCREAMING_SNAKE_CASE   :					Tuple        =						"led"
							SCREAMING_SNAKE_CASE   :					int        =						{
							    "num_attention_heads": "encoder_attention_heads",
							    "hidden_size": "d_model",
							    "attention_probs_dropout_prob": "attention_dropout",
							    "initializer_range": "init_std",
							}





							def __init__(    self				, A_=50265				, A_=16384				, A_=1024				, A_=12				, A_=4096				, A_=16				, A_=12				, A_=4096				, A_=16				, A_=0.0				, A_=0.0				, A_=True				, A_=True				, A_="gelu"				, A_=1024				, A_=0.1				, A_=0.0				, A_=0.0				, A_=0.02				, A_=2				, A_=0.0				, A_=1				, A_=0				, A_=2				, A_ = 512				, **A_				, )->	Optional[Any]:
											_SCREAMING_SNAKE_CASE      = vocab_size
											_SCREAMING_SNAKE_CASE      = max_encoder_position_embeddings
											_SCREAMING_SNAKE_CASE      = max_decoder_position_embeddings
											_SCREAMING_SNAKE_CASE      = d_model
											_SCREAMING_SNAKE_CASE      = encoder_ffn_dim
											_SCREAMING_SNAKE_CASE      = encoder_layers
											_SCREAMING_SNAKE_CASE      = encoder_attention_heads
											_SCREAMING_SNAKE_CASE      = decoder_ffn_dim
											_SCREAMING_SNAKE_CASE      = decoder_layers
											_SCREAMING_SNAKE_CASE      = decoder_attention_heads
											_SCREAMING_SNAKE_CASE      = dropout
											_SCREAMING_SNAKE_CASE      = attention_dropout
											_SCREAMING_SNAKE_CASE      = activation_dropout
											_SCREAMING_SNAKE_CASE      = activation_function
											_SCREAMING_SNAKE_CASE      = init_std
											_SCREAMING_SNAKE_CASE      = encoder_layerdrop
											_SCREAMING_SNAKE_CASE      = decoder_layerdrop
											_SCREAMING_SNAKE_CASE      = classifier_dropout
											_SCREAMING_SNAKE_CASE      = use_cache
											_SCREAMING_SNAKE_CASE      = encoder_layers
											_SCREAMING_SNAKE_CASE      = attention_window

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




from typing import TYPE_CHECKING

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


snake_case			:      Optional[int] 							=   {'configuration_vit_hybrid': ['VIT_HYBRID_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ViTHybridConfig']}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							snake_case			:      int 							=   [
							    'VIT_HYBRID_PRETRAINED_MODEL_ARCHIVE_LIST',
							    'ViTHybridForImageClassification',
							    'ViTHybridModel',
							    'ViTHybridPreTrainedModel',
							]

try:
							if not is_vision_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							snake_case			:      Any 							=   ['ViTHybridImageProcessor']


if TYPE_CHECKING:
							from .configuration_vit_hybrid import VIT_HYBRID_PRETRAINED_CONFIG_ARCHIVE_MAP, ViTHybridConfig

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_vit_hybrid import (
														    VIT_HYBRID_PRETRAINED_MODEL_ARCHIVE_LIST,
														    ViTHybridForImageClassification,
														    ViTHybridModel,
														    ViTHybridPreTrainedModel,
														)

							try:
														if not is_vision_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .image_processing_vit_hybrid import ViTHybridImageProcessor


else:
							import sys

							snake_case			:      Optional[int] 							=   _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)
