




'''simple docstring'''

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


a    :							Optional[Any]										=    logging.get_logger(__name__)

a    :							Any										=    {'openai-gpt': 'https://huggingface.co/openai-gpt/resolve/main/config.json'}






class 		a							(  _lowerCamelCase	):
				snake_case_           =						"openai-gpt"
				snake_case_           =						{
				    "max_position_embeddings": "n_positions",
				    "hidden_size": "n_embd",
				    "num_attention_heads": "n_head",
				    "num_hidden_layers": "n_layer",
				}


				def __init__(						self       :   Dict			,							lowercase_       :   Dict=4_0478			,							lowercase_       :   Optional[Any]=512			,							lowercase_       :   Tuple=768			,							lowercase_       :   Any=12			,							lowercase_       :   int=12			,							lowercase_       :   int="gelu"			,							lowercase_       :   int=0.1			,							lowercase_       :   str=0.1			,							lowercase_       :   Optional[Any]=0.1			,							lowercase_       :   int=1e-5			,							lowercase_       :   int=0.02			,							lowercase_       :   List[Any]="cls_index"			,							lowercase_       :   List[Any]=True			,							lowercase_       :   Optional[int]=None			,							lowercase_       :   str=True			,							lowercase_       :   str=0.1			,							**lowercase_       :   List[Any]			,							):
									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__(**lowercase_   )







'''simple docstring'''

from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
)


a    :							Tuple										=    {
    'configuration_encodec': [
        'ENCODEC_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'EncodecConfig',
    ],
    'feature_extraction_encodec': ['EncodecFeatureExtractor'],
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							a    :							str										=    [
							    'ENCODEC_PRETRAINED_MODEL_ARCHIVE_LIST',
							    'EncodecModel',
							    'EncodecPreTrainedModel',
							]

if TYPE_CHECKING:
							from .configuration_encodec import (
							    ENCODEC_PRETRAINED_CONFIG_ARCHIVE_MAP,
							    EncodecConfig,
							)
							from .feature_extraction_encodec import EncodecFeatureExtractor

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_encodec import (
														    ENCODEC_PRETRAINED_MODEL_ARCHIVE_LIST,
														    EncodecModel,
														    EncodecPreTrainedModel,
														)

else:
							import sys

							a    :							List[Any]										=    _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)

