import warnings
from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


UpperCAmelCase_			    =							logging.get_logger(__name__)

UpperCAmelCase_			    =							{
    '''nvidia/segformer-b0-finetuned-ade-512-512''': (
        '''https://huggingface.co/nvidia/segformer-b0-finetuned-ade-512-512/resolve/main/config.json'''
    ),
    # See all SegFormer models at https://huggingface.co/models?filter=segformer
}




class  __magic_name__  (		__a    ):





   """simple docstring"""




   lowerCAmelCase      :    Optional[Any]  			=   '''segformer'''



   def __init__(	self					:  int		,  _lowercase					:  Tuple=3		,  _lowercase					:  Dict=4		,  _lowercase					:  List[Any]=[2, 2, 2, 2]		,  _lowercase					:  Any=[8, 4, 2, 1]		,  _lowercase					:  List[str]=[32, 64, 160, 256]		,  _lowercase					:  str=[7, 3, 3, 3]		,  _lowercase					:  int=[4, 2, 2, 2]		,  _lowercase					:  Optional[int]=[1, 2, 5, 8]		,  _lowercase					:  Optional[int]=[4, 4, 4, 4]		,  _lowercase					:  Optional[int]="gelu"		,  _lowercase					:  List[Any]=0.0		,  _lowercase					:  str=0.0		,  _lowercase					:  List[str]=0.1		,  _lowercase					:  Union[str, Any]=0.02		,  _lowercase					:  Dict=0.1		,  _lowercase					:  Optional[int]=1E-6		,  _lowercase					:  List[Any]=256		,  _lowercase					:  Optional[Any]=255		,  **_lowercase					:  Any		,  ):



    """simple docstring"""



    super().__init__(**_lowercase							)

    if "reshape_last_stage" in kwargs and kwargs["reshape_last_stage"] is False:
     warnings.warn(
         '''Reshape_last_stage is set to False in this config. This argument is deprecated and will soon be'''
         ''' removed, as the behaviour will default to that of reshape_last_stage = True.'''		,  _lowercase		,  )

    _UpperCamelCase:     Tuple							= num_channels
    _UpperCamelCase:     List[Any]							= num_encoder_blocks
    _UpperCamelCase:     Tuple							= depths
    _UpperCamelCase:     Any							= sr_ratios
    _UpperCamelCase:     Optional[int]							= hidden_sizes
    _UpperCamelCase:     int							= patch_sizes
    _UpperCamelCase:     Optional[Any]							= strides
    _UpperCamelCase:     Optional[Any]							= mlp_ratios
    _UpperCamelCase:     Tuple							= num_attention_heads
    _UpperCamelCase:     Union[str, Any]							= hidden_act
    _UpperCamelCase:     Tuple							= hidden_dropout_prob
    _UpperCamelCase:     str							= attention_probs_dropout_prob
    _UpperCamelCase:     List[Any]							= classifier_dropout_prob
    _UpperCamelCase:     str							= initializer_range
    _UpperCamelCase:     Any							= drop_path_rate
    _UpperCamelCase:     Tuple							= layer_norm_eps
    _UpperCamelCase:     List[str]							= decoder_hidden_size
    _UpperCamelCase:     str							= kwargs.get('''reshape_last_stage'''		,  _lowercase							)
    _UpperCamelCase:     Tuple							= semantic_loss_ignore_index




class  __magic_name__  (		__a    ):





   """simple docstring"""




   lowerCAmelCase      :    Tuple  			=   version.parse('''1.11'''    )



   @property
   def   lowerCAmelCase						(	self					:  Tuple							):



    """simple docstring"""



    return OrderedDict(
        [
            ('''pixel_values''', {0: '''batch''', 1: '''num_channels''', 2: '''height''', 3: '''width'''}),
        ]							)



   @property
   def   lowerCAmelCase						(	self					:  Tuple							):



    """simple docstring"""



    return 1E-4



   @property
   def   lowerCAmelCase						(	self					:  Dict							):



    """simple docstring"""



    return 12
from typing import TYPE_CHECKING

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


UpperCAmelCase_			    =							{
    '''configuration_blenderbot''': [
        '''BLENDERBOT_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''BlenderbotConfig''',
        '''BlenderbotOnnxConfig''',
    ],
    '''tokenization_blenderbot''': ['''BlenderbotTokenizer'''],
}

try:
  if not is_tokenizers_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCAmelCase_			    =							['''BlenderbotTokenizerFast''']

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCAmelCase_			    =							[
      '''BLENDERBOT_PRETRAINED_MODEL_ARCHIVE_LIST''',
      '''BlenderbotForCausalLM''',
      '''BlenderbotForConditionalGeneration''',
      '''BlenderbotModel''',
      '''BlenderbotPreTrainedModel''',
  ]


try:
  if not is_tf_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCAmelCase_			    =							[
      '''TFBlenderbotForConditionalGeneration''',
      '''TFBlenderbotModel''',
      '''TFBlenderbotPreTrainedModel''',
  ]


try:
  if not is_flax_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCAmelCase_			    =							[
      '''FlaxBlenderbotForConditionalGeneration''',
      '''FlaxBlenderbotModel''',
      '''FlaxBlenderbotPreTrainedModel''',
  ]


if TYPE_CHECKING:
  from .configuration_blenderbot import (
      BLENDERBOT_PRETRAINED_CONFIG_ARCHIVE_MAP,
      BlenderbotConfig,
      BlenderbotOnnxConfig,
  )
  from .tokenization_blenderbot import BlenderbotTokenizer

  try:
    if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .tokenization_blenderbot_fast import BlenderbotTokenizerFast

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_blenderbot import (
        BLENDERBOT_PRETRAINED_MODEL_ARCHIVE_LIST,
        BlenderbotForCausalLM,
        BlenderbotForConditionalGeneration,
        BlenderbotModel,
        BlenderbotPreTrainedModel,
    )

  try:
    if not is_tf_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_tf_blenderbot import (
        TFBlenderbotForConditionalGeneration,
        TFBlenderbotModel,
        TFBlenderbotPreTrainedModel,
    )

  try:
    if not is_flax_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_flax_blenderbot import (
        FlaxBlenderbotForConditionalGeneration,
        FlaxBlenderbotModel,
        FlaxBlenderbotPreTrainedModel,
    )

else:
  import sys

  UpperCAmelCase_			    =							_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)