






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


a__       =     logging.get_logger(__name__)

a__       =     {"""openai-gpt""": """https://huggingface.co/openai-gpt/resolve/main/config.json"""}


class    _lowerCAmelCase			(		_snake_case      ):



				"""simple docstring"""



				_lowercase				:   Optional[Any]      =  """openai-gpt"""
				_lowercase				:   Dict      =  {
				    """max_position_embeddings""": """n_positions""",
				    """hidden_size""": """n_embd""",
				    """num_attention_heads""": """n_head""",
				    """num_hidden_layers""": """n_layer""",
				}



				def __init__(      self    :    Optional[int]			,		UpperCamelCase__    :    Optional[Any]=4_0_4_7_8			,		UpperCamelCase__    :    Any=5_1_2			,		UpperCamelCase__    :    Optional[int]=7_6_8			,		UpperCamelCase__    :    Union[str, Any]=1_2			,		UpperCamelCase__    :    Dict=1_2			,		UpperCamelCase__    :    Tuple="gelu"			,		UpperCamelCase__    :    str=0.1			,		UpperCamelCase__    :    Optional[int]=0.1			,		UpperCamelCase__    :    Dict=0.1			,		UpperCamelCase__    :    Dict=1E-5			,		UpperCamelCase__    :    int=0.02			,		UpperCamelCase__    :    str="cls_index"			,		UpperCamelCase__    :    List[Any]=True			,		UpperCamelCase__    :    Union[str, Any]=None			,		UpperCamelCase__    :    Optional[int]=True			,		UpperCamelCase__    :    Tuple=0.1			,		**UpperCamelCase__    :    Dict			,		):






											'''simple docstring'''







											snake_case__	  =       vocab_size
											snake_case__	  =       n_positions
											snake_case__	  =       n_embd
											snake_case__	  =       n_layer
											snake_case__	  =       n_head
											snake_case__	  =       afn
											snake_case__	  =       resid_pdrop
											snake_case__	  =       embd_pdrop
											snake_case__	  =       attn_pdrop
											snake_case__	  =       layer_norm_epsilon
											snake_case__	  =       initializer_range
											snake_case__	  =       summary_type
											snake_case__	  =       summary_use_proj
											snake_case__	  =       summary_activation
											snake_case__	  =       summary_first_dropout
											snake_case__	  =       summary_proj_to_labels
											super().__init__(**snake_case_)








from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


a__       =     {
    """configuration_autoformer""": [
        """AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """AutoformerConfig""",
    ],
}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	a__       =     [
	    """AUTOFORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
	    """AutoformerForPrediction""",
	    """AutoformerModel""",
	    """AutoformerPreTrainedModel""",
	]


if TYPE_CHECKING:
	from .configuration_autoformer import (
	    AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
	    AutoformerConfig,
	)

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_autoformer import (
		    AUTOFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
		    AutoformerForPrediction,
		    AutoformerModel,
		    AutoformerPreTrainedModel,
		)

else:
	import sys

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