



"""simple docstring"""


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


snake_case_				     =       logging.get_logger(__name__)

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







class       A_			(     SCREAMING_SNAKE_CASE_				):



						"""simple docstring"""
						__UpperCamelCase						=							"""openai-gpt"""
						__UpperCamelCase						=							{
						    """max_position_embeddings""": """n_positions""",
						    """hidden_size""": """n_embd""",
						    """num_attention_heads""": """n_head""",
						    """num_hidden_layers""": """n_layer""",
						}






						def __init__(					self :Optional[int]   ,  lowercase_ :Optional[int]=4_04_78   ,  lowercase_ :List[Any]=5_12   ,  lowercase_ :List[str]=7_68   ,  lowercase_ :int=12   ,  lowercase_ :Dict=12   ,  lowercase_ :Union[str, Any]="gelu"   ,  lowercase_ :Union[str, Any]=0.1   ,  lowercase_ :str=0.1   ,  lowercase_ :List[str]=0.1   ,  lowercase_ :Optional[Any]=1E-5   ,  lowercase_ :Optional[int]=0.02   ,  lowercase_ :Optional[Any]="cls_index"   ,  lowercase_ :List[str]=True   ,  lowercase_ :List[str]=None   ,  lowercase_ :str=True   ,  lowercase_ :int=0.1   ,  **lowercase_ :List[Any]   ,  )				->			str:
												UpperCAmelCase             = vocab_size
												UpperCAmelCase             = n_positions
												UpperCAmelCase             = n_embd
												UpperCAmelCase             = n_layer
												UpperCAmelCase             = n_head
												UpperCAmelCase             = afn
												UpperCAmelCase             = resid_pdrop
												UpperCAmelCase             = embd_pdrop
												UpperCAmelCase             = attn_pdrop
												UpperCAmelCase             = layer_norm_epsilon
												UpperCAmelCase             = initializer_range
												UpperCAmelCase             = summary_type
												UpperCAmelCase             = summary_use_proj
												UpperCAmelCase             = summary_activation
												UpperCAmelCase             = summary_first_dropout
												UpperCAmelCase             = summary_proj_to_labels
												super().__init__(**lowercase_					)









from typing import TYPE_CHECKING

from ...file_utils import _LazyModule, is_tokenizers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable


lowerCAmelCase           =		{'''configuration_gpt_neox''': ['''GPT_NEOX_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GPTNeoXConfig''']}

try:
	if not is_tokenizers_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	lowerCAmelCase           =		['''GPTNeoXTokenizerFast''']

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	lowerCAmelCase           =		[
	    '''GPT_NEOX_PRETRAINED_MODEL_ARCHIVE_LIST''',
	    '''GPTNeoXForCausalLM''',
	    '''GPTNeoXForQuestionAnswering''',
	    '''GPTNeoXForSequenceClassification''',
	    '''GPTNeoXForTokenClassification''',
	    '''GPTNeoXLayer''',
	    '''GPTNeoXModel''',
	    '''GPTNeoXPreTrainedModel''',
	]


if TYPE_CHECKING:
	from .configuration_gpt_neox import GPT_NEOX_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTNeoXConfig

	try:
		if not is_tokenizers_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_gpt_neox_fast import GPTNeoXTokenizerFast

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_gpt_neox import (
		    GPT_NEOX_PRETRAINED_MODEL_ARCHIVE_LIST,
		    GPTNeoXForCausalLM,
		    GPTNeoXForQuestionAnswering,
		    GPTNeoXForSequenceClassification,
		    GPTNeoXForTokenClassification,
		    GPTNeoXLayer,
		    GPTNeoXModel,
		    GPTNeoXPreTrainedModel,
		)


else:
	import sys

	lowerCAmelCase           =		_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)






