




from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


UpperCamelCase__ :   Dict						=							{'''configuration_opt''': ['''OPT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''OPTConfig''']}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						UpperCamelCase__ :   Any						=							[
						    '''OPT_PRETRAINED_MODEL_ARCHIVE_LIST''',
						    '''OPTForCausalLM''',
						    '''OPTModel''',
						    '''OPTPreTrainedModel''',
						    '''OPTForSequenceClassification''',
						    '''OPTForQuestionAnswering''',
						]

try:
						if not is_tf_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						UpperCamelCase__ :   Dict						=							['''TFOPTForCausalLM''', '''TFOPTModel''', '''TFOPTPreTrainedModel''']

try:
						if not is_flax_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						UpperCamelCase__ :   str						=							[
						    '''FlaxOPTForCausalLM''',
						    '''FlaxOPTModel''',
						    '''FlaxOPTPreTrainedModel''',
						]


if TYPE_CHECKING:
						from .configuration_opt import OPT_PRETRAINED_CONFIG_ARCHIVE_MAP, OPTConfig

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_opt import (
												    OPT_PRETRAINED_MODEL_ARCHIVE_LIST,
												    OPTForCausalLM,
												    OPTForQuestionAnswering,
												    OPTForSequenceClassification,
												    OPTModel,
												    OPTPreTrainedModel,
												)

						try:
												if not is_tf_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_tf_opt import TFOPTForCausalLM, TFOPTModel, TFOPTPreTrainedModel

						try:
												if not is_flax_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_flax_opt import FlaxOPTForCausalLM, FlaxOPTModel, FlaxOPTPreTrainedModel

else:
						import sys

						UpperCamelCase__ :   Union[str, Any]						=							_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)






'''simple docstring'''



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


UpperCAmelCase					:			Tuple       =	logging.get_logger(__name__)

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







class 		lowerCAmelCase__  ( a   ):



 """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   :			Tuple   ,				__SCREAMING_SNAKE_CASE   :			Tuple=246_534   ,				__SCREAMING_SNAKE_CASE   :			str=256   ,				__SCREAMING_SNAKE_CASE   :			Optional[Any]=1_280   ,				__SCREAMING_SNAKE_CASE   :			Dict=8_192   ,				__SCREAMING_SNAKE_CASE   :			Union[str, Any]=48   ,				__SCREAMING_SNAKE_CASE   :			Dict=16   ,				__SCREAMING_SNAKE_CASE   :			Union[str, Any]=0.1   ,				__SCREAMING_SNAKE_CASE   :			str=0.1   ,				__SCREAMING_SNAKE_CASE   :			Union[str, Any]=1E-6   ,				__SCREAMING_SNAKE_CASE   :			Tuple=0.02   ,				__SCREAMING_SNAKE_CASE   :			Tuple=True   ,				**__SCREAMING_SNAKE_CASE   :			Union[str, Any]   ,				)    ->					Tuple:


      """simple docstring"""




      __SCREAMING_SNAKE_CASE      = vocab_size
      __SCREAMING_SNAKE_CASE      = n_positions
      __SCREAMING_SNAKE_CASE      = n_embd
      __SCREAMING_SNAKE_CASE      = n_layer
      __SCREAMING_SNAKE_CASE      = n_head
      __SCREAMING_SNAKE_CASE      = dff
      __SCREAMING_SNAKE_CASE      = resid_pdrop
      __SCREAMING_SNAKE_CASE      = embd_pdrop
      __SCREAMING_SNAKE_CASE      = layer_norm_epsilon
      __SCREAMING_SNAKE_CASE      = initializer_range

      __SCREAMING_SNAKE_CASE      = use_cache

      super().__init__(**__SCREAMING_SNAKE_CASE     )






