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


lowerCAmelCase_ : int						  =      logging.get_logger(__name__)

lowerCAmelCase_ : Optional[int]						  =      {
    '''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 							lowercase						(						__lowerCamelCase ):
   lowerCamelCase_    					='glpn'


   def __init__(   self				:	Tuple   ,		__lowerCAmelCase				:	Optional[Any]=3   ,		__lowerCAmelCase				:	Any=4   ,		__lowerCAmelCase				:	Any=[2, 2, 2, 2]   ,		__lowerCAmelCase				:	int=[8, 4, 2, 1]   ,		__lowerCAmelCase				:	int=[32, 64, 160, 256]   ,		__lowerCAmelCase				:	Dict=[7, 3, 3, 3]   ,		__lowerCAmelCase				:	Dict=[4, 2, 2, 2]   ,		__lowerCAmelCase				:	Union[str, Any]=[1, 2, 5, 8]   ,		__lowerCAmelCase				:	Union[str, Any]=[4, 4, 4, 4]   ,		__lowerCAmelCase				:	Optional[int]="gelu"   ,		__lowerCAmelCase				:	List[Any]=0.0   ,		__lowerCAmelCase				:	Any=0.0   ,		__lowerCAmelCase				:	str=0.02   ,		__lowerCAmelCase				:	List[str]=0.1   ,		__lowerCAmelCase				:	str=1e-6   ,		__lowerCAmelCase				:	Union[str, Any]=64   ,		__lowerCAmelCase				:	Tuple=10   ,		__lowerCAmelCase				:	str=-1   ,		**__lowerCAmelCase				:	int   ,		)      ->					Any:
         super().__init__(**UpperCamelCase_)

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







'''simple docstring'''

from typing import TYPE_CHECKING

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


lowerCAmelCase_ : str						  =      {
    "configuration_wav2vec2": ["WAV_2_VEC_2_PRETRAINED_CONFIG_ARCHIVE_MAP", "Wav2Vec2Config"],
    "feature_extraction_wav2vec2": ["Wav2Vec2FeatureExtractor"],
    "processing_wav2vec2": ["Wav2Vec2Processor"],
    "tokenization_wav2vec2": ["Wav2Vec2CTCTokenizer", "Wav2Vec2Tokenizer"],
}


try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowerCAmelCase_ : Union[str, Any]						  =      [
           "WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST",
           "Wav2Vec2ForAudioFrameClassification",
           "Wav2Vec2ForCTC",
           "Wav2Vec2ForMaskedLM",
           "Wav2Vec2ForPreTraining",
           "Wav2Vec2ForSequenceClassification",
           "Wav2Vec2ForXVector",
           "Wav2Vec2Model",
           "Wav2Vec2PreTrainedModel",
       ]

try:
       if not is_tf_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowerCAmelCase_ : int						  =      [
           "TF_WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST",
           "TFWav2Vec2ForCTC",
           "TFWav2Vec2Model",
           "TFWav2Vec2PreTrainedModel",
           "TFWav2Vec2ForSequenceClassification",
       ]

try:
       if not is_flax_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowerCAmelCase_ : Dict						  =      [
           "FlaxWav2Vec2ForCTC",
           "FlaxWav2Vec2ForPreTraining",
           "FlaxWav2Vec2Model",
           "FlaxWav2Vec2PreTrainedModel",
       ]


if TYPE_CHECKING:
       from .configuration_wavaveca import WAV_2_VEC_2_PRETRAINED_CONFIG_ARCHIVE_MAP, WavaVecaConfig
       from .feature_extraction_wavaveca import WavaVecaFeatureExtractor
       from .processing_wavaveca import WavaVecaProcessor
       from .tokenization_wavaveca import WavaVecaCTCTokenizer, WavaVecaTokenizer

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_wavaveca import (
                  WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST,
                  WavaVecaForAudioFrameClassification,
                  WavaVecaForCTC,
                  WavaVecaForMaskedLM,
                  WavaVecaForPreTraining,
                  WavaVecaForSequenceClassification,
                  WavaVecaForXVector,
                  WavaVecaModel,
                  WavaVecaPreTrainedModel,
              )

       try:
              if not is_tf_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_tf_wavaveca import (
                  TF_WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST,
                  TFWavaVecaForCTC,
                  TFWavaVecaForSequenceClassification,
                  TFWavaVecaModel,
                  TFWavaVecaPreTrainedModel,
              )

       try:
              if not is_flax_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_tf_wavaveca import (
                  FlaxWavaVecaForCTC,
                  FlaxWavaVecaForPreTraining,
                  FlaxWavaVecaModel,
                  FlaxWavaVecaPreTrainedModel,
              )


else:
       import sys

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






