




"""simple docstring"""






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowercase__     						=						{
    """configuration_table_transformer""": [
        """TABLE_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """TableTransformerConfig""",
        """TableTransformerOnnxConfig""",
    ]
}

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			lowercase__     						=						[
			    """TABLE_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
			    """TableTransformerForObjectDetection""",
			    """TableTransformerModel""",
			    """TableTransformerPreTrainedModel""",
			]


if TYPE_CHECKING:
			from .configuration_table_transformer import (
			    TABLE_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
			    TableTransformerConfig,
			    TableTransformerOnnxConfig,
			)

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_table_transformer import (
						    TABLE_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
						    TableTransformerForObjectDetection,
						    TableTransformerModel,
						    TableTransformerPreTrainedModel,
						)

else:
			import sys

			lowercase__     						=						_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)





"""simple docstring"""






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


lowercase__     						=						logging.get_logger(__name__)

lowercase__     						=						{"""ctrl""": """https://huggingface.co/ctrl/resolve/main/config.json"""}






class lowerCAmelCase__	(     lowercase						):






			'''simple docstring'''



			lowerCamelCase__      =			"""ctrl"""
			lowerCamelCase__      =			["""past_key_values"""]
			lowerCamelCase__      =			{
			    """max_position_embeddings""": """n_positions""",
			    """hidden_size""": """n_embd""",
			    """num_attention_heads""": """n_head""",
			    """num_hidden_layers""": """n_layer""",
			}
			def __init__(  self  ,      lowercase=246534  ,      lowercase=256  ,      lowercase=1280  ,      lowercase=8192  ,      lowercase=48  ,      lowercase=16  ,      lowercase=0.1  ,      lowercase=0.1  ,      lowercase=1E-6  ,      lowercase=0.02  ,      lowercase=True  ,      **lowercase  ,      ):
							_lowerCamelCase     :			Any    =    vocab_size
							_lowerCamelCase     :			Dict    =    n_positions
							_lowerCamelCase     :			Optional[int]    =    n_embd
							_lowerCamelCase     :			str    =    n_layer
							_lowerCamelCase     :			Union[str, Any]    =    n_head
							_lowerCamelCase     :			Any    =    dff
							_lowerCamelCase     :			int    =    resid_pdrop
							_lowerCamelCase     :			Dict    =    embd_pdrop
							_lowerCamelCase     :			Union[str, Any]    =    layer_norm_epsilon
							_lowerCamelCase     :			Tuple    =    initializer_range

							_lowerCamelCase     :			str    =    use_cache

							super().__init__(**lowercase  )