


'''simple docstring'''






from typing import TYPE_CHECKING

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


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

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

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__UpperCAmelCase					       =							[
		    '''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

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



'''simple docstring'''






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


__UpperCAmelCase					       =							logging.get_logger(__name__)

__UpperCAmelCase					       =							{'''ctrl''': '''https://huggingface.co/ctrl/resolve/main/config.json'''}




class 	a__       (							a__						):





							'''simple docstring'''






							lowercase__    :     Dict					=   "ctrl"
							lowercase__    :     str					=   ["past_key_values"]
							lowercase__    :     Optional[int]					=   {
							    "max_position_embeddings": "n_positions",
							    "hidden_size": "n_embd",
							    "num_attention_heads": "n_head",
							    "num_hidden_layers": "n_layer",
							}







							def __init__(	self      ,					lowerCamelCase_=24_65_34      ,					lowerCamelCase_=2_56      ,					lowerCamelCase_=12_80      ,					lowerCamelCase_=81_92      ,					lowerCamelCase_=48      ,					lowerCamelCase_=16      ,					lowerCamelCase_=0.1      ,					lowerCamelCase_=0.1      ,					lowerCamelCase_=1e-6      ,					lowerCamelCase_=0.02      ,					lowerCamelCase_=True      ,					**lowerCamelCase_      ,					) ->							Union[str, Any]:
														lowerCAmelCase__      =			vocab_size
														lowerCAmelCase__      =			n_positions
														lowerCAmelCase__      =			n_embd
														lowerCAmelCase__      =			n_layer
														lowerCAmelCase__      =			n_head
														lowerCAmelCase__      =			dff
														lowerCAmelCase__      =			resid_pdrop
														lowerCAmelCase__      =			embd_pdrop
														lowerCAmelCase__      =			layer_norm_epsilon
														lowerCAmelCase__      =			initializer_range

														lowerCAmelCase__      =			use_cache

														super().__init__(**lowerCamelCase_     )