


'''simple docstring'''






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


a_   :      str				    =      logging.get_logger(__name__)

a_   :      Union[str, Any]				    =      {
    'vinvino02/glpn-kitti': 'https://huggingface.co/vinvino02/glpn-kitti/resolve/main/config.json',
    # See all GLPN models at https://huggingface.co/models?filter=glpn
}




class 	a       (       __SCREAMING_SNAKE_CASE    ):
 _lowerCAmelCase	   =		"""glpn"""
 def __init__(	self ,			__magic_name__=3 ,			__magic_name__=4 ,			__magic_name__=[2, 2, 2, 2] ,			__magic_name__=[8, 4, 2, 1] ,			__magic_name__=[32, 64, 1_60, 2_56] ,			__magic_name__=[7, 3, 3, 3] ,			__magic_name__=[4, 2, 2, 2] ,			__magic_name__=[1, 2, 5, 8] ,			__magic_name__=[4, 4, 4, 4] ,			__magic_name__="gelu" ,			__magic_name__=0.0 ,			__magic_name__=0.0 ,			__magic_name__=0.0_2 ,			__magic_name__=0.1 ,			__magic_name__=1e-6 ,			__magic_name__=64 ,			__magic_name__=10 ,			__magic_name__=-1 ,			**__magic_name__ ,			)   ->							str:
      super().__init__(**_SCREAMING_SNAKE_CASE  )

      _a      =							num_channels
      _a      =							num_encoder_blocks
      _a      =							depths
      _a      =							sr_ratios
      _a      =							hidden_sizes
      _a      =							patch_sizes
      _a      =							strides
      _a      =							mlp_ratios
      _a      =							num_attention_heads
      _a      =							hidden_act
      _a      =							hidden_dropout_prob
      _a      =							attention_probs_dropout_prob
      _a      =							initializer_range
      _a      =							drop_path_rate
      _a      =							layer_norm_eps
      _a      =							decoder_hidden_size
      _a      =							max_depth
      _a      =							head_in_index





'''simple docstring'''






from typing import TYPE_CHECKING

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


a_   :      int				    =      {
    "configuration_gpt_neox_japanese": ["GPT_NEOX_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MAP", "GPTNeoXJapaneseConfig"],
    "tokenization_gpt_neox_japanese": ["GPTNeoXJapaneseTokenizer"],
}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 a_   :      List[str]				    =      [
     "GPT_NEOX_JAPANESE_PRETRAINED_MODEL_ARCHIVE_LIST",
     "GPTNeoXJapaneseForCausalLM",
     "GPTNeoXJapaneseLayer",
     "GPTNeoXJapaneseModel",
     "GPTNeoXJapanesePreTrainedModel",
 ]


if TYPE_CHECKING:
 from .configuration_gpt_neox_japanese import GPT_NEOX_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTNeoXJapaneseConfig
 from .tokenization_gpt_neox_japanese import GPTNeoXJapaneseTokenizer

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_gpt_neox_japanese import (
      GPT_NEOX_JAPANESE_PRETRAINED_MODEL_ARCHIVE_LIST,
      GPTNeoXJapaneseForCausalLM,
      GPTNeoXJapaneseLayer,
      GPTNeoXJapaneseModel,
      GPTNeoXJapanesePreTrainedModel,
  )


else:
 import sys

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

