





"""simple docstring"""
from typing import TYPE_CHECKING

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


__UpperCamelCase     :						Optional[Any]						       =  {
    '''configuration_falcon''': ['''FALCON_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''FalconConfig'''],
}

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __UpperCamelCase     :						Any						       =  [
           '''FALCON_PRETRAINED_MODEL_ARCHIVE_LIST''',
           '''FalconForCausalLM''',
           '''FalconModel''',
           '''FalconPreTrainedModel''',
           '''FalconForSequenceClassification''',
           '''FalconForTokenClassification''',
           '''FalconForQuestionAnswering''',
       ]


if TYPE_CHECKING:
       from .configuration_falcon import FALCON_PRETRAINED_CONFIG_ARCHIVE_MAP, FalconConfig

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_falcon import (
                  FALCON_PRETRAINED_MODEL_ARCHIVE_LIST,
                  FalconForCausalLM,
                  FalconForQuestionAnswering,
                  FalconForSequenceClassification,
                  FalconForTokenClassification,
                  FalconModel,
                  FalconPreTrainedModel,
              )


else:
       import sys

       __UpperCamelCase     :						str						       =  _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)













from collections import OrderedDict
from typing import List, Mapping

from packaging import version

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


__a:     Dict   					=					logging.get_logger(__name__)

__a:     Optional[int]   					=					{
    '''google/efficientnet-b7''': '''https://huggingface.co/google/efficientnet-b7/resolve/main/config.json''',
}
class 		SCREAMING_SNAKE_CASE__	(  UpperCAmelCase     ):

  '''simple docstring'''







  _lowerCamelCase    =  '''efficientnet'''


  def __init__(      self		:			Dict       ,				lowerCamelCase		:			int = 3       ,				lowerCamelCase		:			int = 600       ,				lowerCamelCase		:			float = 2.0       ,				lowerCamelCase		:			float = 3.1       ,				lowerCamelCase		:			int = 8       ,				lowerCamelCase		:			List[int] = [3, 3, 5, 3, 5, 5, 3]       ,				lowerCamelCase		:			List[int] = [32, 16, 24, 40, 80, 112, 192]       ,				lowerCamelCase		:			List[int] = [16, 24, 40, 80, 112, 192, 320]       ,				lowerCamelCase		:			List[int] = []       ,				lowerCamelCase		:			List[int] = [1, 2, 2, 2, 1, 2, 1]       ,				lowerCamelCase		:			List[int] = [1, 2, 2, 3, 3, 4, 1]       ,				lowerCamelCase		:			List[int] = [1, 6, 6, 6, 6, 6, 6]       ,				lowerCamelCase		:			float = 0.25       ,				lowerCamelCase		:			str = "swish"       ,				lowerCamelCase		:			int = 2560       ,				lowerCamelCase		:			str = "mean"       ,				lowerCamelCase		:			float = 0.02       ,				lowerCamelCase		:			float = 0.001       ,				lowerCamelCase		:			float = 0.99       ,				lowerCamelCase		:			float = 0.5       ,				lowerCamelCase		:			float = 0.2       ,				**lowerCamelCase		:			List[str]       ,				)						->	Union[str, Any]:


         """simple docstring"""
         super().__init__(**lowerCamelCase							)

         _UpperCAmelCase							=    num_channels
         _UpperCAmelCase							=    image_size
         _UpperCAmelCase							=    width_coefficient
         _UpperCAmelCase							=    depth_coefficient
         _UpperCAmelCase							=    depth_divisor
         _UpperCAmelCase							=    kernel_sizes
         _UpperCAmelCase							=    in_channels
         _UpperCAmelCase							=    out_channels
         _UpperCAmelCase							=    depthwise_padding
         _UpperCAmelCase							=    strides
         _UpperCAmelCase							=    num_block_repeats
         _UpperCAmelCase							=    expand_ratios
         _UpperCAmelCase							=    squeeze_expansion_ratio
         _UpperCAmelCase							=    hidden_act
         _UpperCAmelCase							=    hidden_dim
         _UpperCAmelCase							=    pooling_type
         _UpperCAmelCase							=    initializer_range
         _UpperCAmelCase							=    batch_norm_eps
         _UpperCAmelCase							=    batch_norm_momentum
         _UpperCAmelCase							=    dropout_rate
         _UpperCAmelCase							=    drop_connect_rate
         _UpperCAmelCase							=    sum(lowerCamelCase							) * 4



class 		SCREAMING_SNAKE_CASE__	(  UpperCAmelCase     ):

  '''simple docstring'''







  _lowerCamelCase    =  version.parse('''1.11'''     )


  @property
  def  lowerCamelCase       (      self		:			Optional[Any]							)						->	Mapping[str, Mapping[int, str]]:


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





  @property
  def  lowerCamelCase       (      self		:			Dict							)						->	float:


         """simple docstring"""
         return 1E-5