"""simple docstring"""


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


lowerCAmelCase_:					Union[str, Any]     =					logging.get_logger(__name__)

lowerCAmelCase_:					List[Any]     =					{
    '''tanreinama/GPTSAN-2.8B-spout_is_uniform''': (
        '''https://huggingface.co/tanreinama/GPTSAN-2.8B-spout_is_uniform/resolve/main/config.json'''
    ),
}






class    a__    (   snake_case__	):
			snake_case_							=      '''gptsan-japanese'''
			snake_case_							=      [
			    '''past_key_values''',
			]
			snake_case_							=      {
			    '''hidden_size''': '''d_model''',
			    '''num_attention_heads''': '''num_heads''',
			    '''num_hidden_layers''': '''num_layers''',
			}


			def __init__(     self,				_UpperCAmelCase=3_6000,				_UpperCAmelCase=1280,				_UpperCAmelCase=1024,				_UpperCAmelCase=8192,				_UpperCAmelCase=4096,				_UpperCAmelCase=128,				_UpperCAmelCase=10,				_UpperCAmelCase=0,				_UpperCAmelCase=16,				_UpperCAmelCase=16,				_UpperCAmelCase=128,				_UpperCAmelCase=0.0,				_UpperCAmelCase=1E-5,				_UpperCAmelCase=False,				_UpperCAmelCase=0.0,				_UpperCAmelCase="float32",				_UpperCAmelCase=False,				_UpperCAmelCase=False,				_UpperCAmelCase=False,				_UpperCAmelCase=0.002,				_UpperCAmelCase=False,				_UpperCAmelCase=True,				_UpperCAmelCase=3_5998,				_UpperCAmelCase=3_5995,				_UpperCAmelCase=3_5999,				**_UpperCAmelCase,				):
								'''simple docstring'''



								lowercase__				 =							vocab_size
								lowercase__				 =							max_position_embeddings
								lowercase__				 =							d_model
								lowercase__				 =							d_ff
								lowercase__				 =							d_ext
								lowercase__				 =							d_spout
								lowercase__				 =							num_switch_layers
								lowercase__				 =							num_ext_layers
								lowercase__				 =							num_switch_layers + num_ext_layers
								lowercase__				 =							num_heads
								lowercase__				 =							num_experts
								lowercase__				 =							expert_capacity
								lowercase__				 =							dropout_rate
								lowercase__				 =							layer_norm_epsilon
								lowercase__				 =							router_bias
								lowercase__				 =							router_jitter_noise
								lowercase__				 =							router_dtype
								lowercase__				 =							router_ignore_padding_tokens
								lowercase__				 =							output_hidden_states
								lowercase__				 =							output_attentions
								lowercase__				 =							initializer_factor
								lowercase__				 =							output_router_logits
								lowercase__				 =							use_cache

								super().__init__(
								    separator_token_id=_A,				pad_token_id=_A,				eos_token_id=_A,				**_A,				)





"""simple docstring"""


from typing import TYPE_CHECKING

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


lowerCAmelCase_:					Union[str, Any]     =					{
    "configuration_distilbert": [
        "DISTILBERT_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "DistilBertConfig",
        "DistilBertOnnxConfig",
    ],
    "tokenization_distilbert": ["DistilBertTokenizer"],
}

try:
 if not is_tokenizers_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCAmelCase_:					Union[str, Any]     =					["DistilBertTokenizerFast"]

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCAmelCase_:					Any     =					[
     "DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST",
     "DistilBertForMaskedLM",
     "DistilBertForMultipleChoice",
     "DistilBertForQuestionAnswering",
     "DistilBertForSequenceClassification",
     "DistilBertForTokenClassification",
     "DistilBertModel",
     "DistilBertPreTrainedModel",
 ]

try:
 if not is_tf_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCAmelCase_:					Tuple     =					[
     "TF_DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST",
     "TFDistilBertForMaskedLM",
     "TFDistilBertForMultipleChoice",
     "TFDistilBertForQuestionAnswering",
     "TFDistilBertForSequenceClassification",
     "TFDistilBertForTokenClassification",
     "TFDistilBertMainLayer",
     "TFDistilBertModel",
     "TFDistilBertPreTrainedModel",
 ]

try:
 if not is_flax_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCAmelCase_:					Optional[Any]     =					[
     "FlaxDistilBertForMaskedLM",
     "FlaxDistilBertForMultipleChoice",
     "FlaxDistilBertForQuestionAnswering",
     "FlaxDistilBertForSequenceClassification",
     "FlaxDistilBertForTokenClassification",
     "FlaxDistilBertModel",
     "FlaxDistilBertPreTrainedModel",
 ]


if TYPE_CHECKING:
 from .configuration_distilbert import (
     DISTILBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
     DistilBertConfig,
     DistilBertOnnxConfig,
 )
 from .tokenization_distilbert import DistilBertTokenizer

 try:
  if not is_tokenizers_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .tokenization_distilbert_fast import DistilBertTokenizerFast

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_distilbert import (
      DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
      DistilBertForMaskedLM,
      DistilBertForMultipleChoice,
      DistilBertForQuestionAnswering,
      DistilBertForSequenceClassification,
      DistilBertForTokenClassification,
      DistilBertModel,
      DistilBertPreTrainedModel,
  )

 try:
  if not is_tf_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_tf_distilbert import (
      TF_DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
      TFDistilBertForMaskedLM,
      TFDistilBertForMultipleChoice,
      TFDistilBertForQuestionAnswering,
      TFDistilBertForSequenceClassification,
      TFDistilBertForTokenClassification,
      TFDistilBertMainLayer,
      TFDistilBertModel,
      TFDistilBertPreTrainedModel,
  )

 try:
  if not is_flax_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_flax_distilbert import (
      FlaxDistilBertForMaskedLM,
      FlaxDistilBertForMultipleChoice,
      FlaxDistilBertForQuestionAnswering,
      FlaxDistilBertForSequenceClassification,
      FlaxDistilBertForTokenClassification,
      FlaxDistilBertModel,
      FlaxDistilBertPreTrainedModel,
  )

else:
 import sys

 lowerCAmelCase_:					Optional[int]     =					_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)




