
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


lowerCamelCase__     :		Optional[int]        = logging.get_logger(__name__)

lowerCamelCase__     :		List[Any]        = {
    """google/mobilenet_v1_1.0_224""": """https://huggingface.co/google/mobilenet_v1_1.0_224/resolve/main/config.json""",
    """google/mobilenet_v1_0.75_192""": """https://huggingface.co/google/mobilenet_v1_0.75_192/resolve/main/config.json""",
    # See all MobileNetV1 models at https://huggingface.co/models?filter=mobilenet_v1
}



class    _snake_case (						UpperCAmelCase_				):
 __lowerCAmelCase	:  Optional[int]	   =      'mobilenet_v1'


 def __init__(       self       ,	SCREAMING_SNAKE_CASE_=3       ,	SCREAMING_SNAKE_CASE_=2_24       ,	SCREAMING_SNAKE_CASE_=1.0       ,	SCREAMING_SNAKE_CASE_=8       ,	SCREAMING_SNAKE_CASE_="relu6"       ,	SCREAMING_SNAKE_CASE_=True       ,	SCREAMING_SNAKE_CASE_=0.9_9_9       ,	SCREAMING_SNAKE_CASE_=0.0_2       ,	SCREAMING_SNAKE_CASE_=0.0_0_1       ,	**SCREAMING_SNAKE_CASE_       ,	):


   '''simple docstring'''




   super().__init__(**SCREAMING_SNAKE_CASE_)

   if depth_multiplier <= 0:
     raise ValueError("""depth_multiplier must be greater than zero.""")

   lowercase__	: List[Any]     		=   num_channels
   lowercase__	: Optional[Any]     		=   image_size
   lowercase__	: Union[str, Any]     		=   depth_multiplier
   lowercase__	: Optional[Any]     		=   min_depth
   lowercase__	: Tuple     		=   hidden_act
   lowercase__	: Any     		=   tf_padding
   lowercase__	: int     		=   classifier_dropout_prob
   lowercase__	: Optional[int]     		=   initializer_range
   lowercase__	: Tuple     		=   layer_norm_eps



class    _snake_case (						UpperCAmelCase_				):
 __lowerCAmelCase	:  Tuple	   =      version.parse('1.11'				)


 @property
 def   lowercase__  (       self):


   '''simple docstring'''




   return OrderedDict([("""pixel_values""", {0: """batch"""})])


 @property
 def   lowercase__  (       self):


   '''simple docstring'''




   if self.task == "image-classification":
     return OrderedDict([("""logits""", {0: """batch"""})])
   else:
     return OrderedDict([("""last_hidden_state""", {0: """batch"""}), ("""pooler_output""", {0: """batch"""})])



 @property
 def   lowercase__  (       self):


   '''simple docstring'''




   return 1E-4








from collections import OrderedDict
from typing import Mapping

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


lowerCamelCase__     :		List[Any]        = logging.get_logger(__name__)

lowerCamelCase__     :		Union[str, Any]        = {
    """YituTech/conv-bert-base""": """https://huggingface.co/YituTech/conv-bert-base/resolve/main/config.json""",
    """YituTech/conv-bert-medium-small""": (
        """https://huggingface.co/YituTech/conv-bert-medium-small/resolve/main/config.json"""
    ),
    """YituTech/conv-bert-small""": """https://huggingface.co/YituTech/conv-bert-small/resolve/main/config.json""",
    # See all ConvBERT models at https://huggingface.co/models?filter=convbert
}



class    _snake_case (						UpperCAmelCase_				):
 __lowerCAmelCase	:  Union[str, Any]	   =      'convbert'


 def __init__(       self       ,	SCREAMING_SNAKE_CASE_=3_05_22       ,	SCREAMING_SNAKE_CASE_=7_68       ,	SCREAMING_SNAKE_CASE_=12       ,	SCREAMING_SNAKE_CASE_=12       ,	SCREAMING_SNAKE_CASE_=30_72       ,	SCREAMING_SNAKE_CASE_="gelu"       ,	SCREAMING_SNAKE_CASE_=0.1       ,	SCREAMING_SNAKE_CASE_=0.1       ,	SCREAMING_SNAKE_CASE_=5_12       ,	SCREAMING_SNAKE_CASE_=2       ,	SCREAMING_SNAKE_CASE_=0.0_2       ,	SCREAMING_SNAKE_CASE_=1E-12       ,	SCREAMING_SNAKE_CASE_=1       ,	SCREAMING_SNAKE_CASE_=0       ,	SCREAMING_SNAKE_CASE_=2       ,	SCREAMING_SNAKE_CASE_=7_68       ,	SCREAMING_SNAKE_CASE_=2       ,	SCREAMING_SNAKE_CASE_=9       ,	SCREAMING_SNAKE_CASE_=1       ,	SCREAMING_SNAKE_CASE_=None       ,	**SCREAMING_SNAKE_CASE_       ,	):


   '''simple docstring'''




   super().__init__(
       pad_token_id=SCREAMING_SNAKE_CASE_       ,	bos_token_id=SCREAMING_SNAKE_CASE_       ,	eos_token_id=SCREAMING_SNAKE_CASE_       ,	**SCREAMING_SNAKE_CASE_       ,	)

   lowercase__	: Dict     		=   vocab_size
   lowercase__	: List[Any]     		=   hidden_size
   lowercase__	: Optional[Any]     		=   num_hidden_layers
   lowercase__	: Union[str, Any]     		=   num_attention_heads
   lowercase__	: List[str]     		=   intermediate_size
   lowercase__	: Optional[int]     		=   hidden_act
   lowercase__	: Tuple     		=   hidden_dropout_prob
   lowercase__	: List[str]     		=   attention_probs_dropout_prob
   lowercase__	: Tuple     		=   max_position_embeddings
   lowercase__	: Dict     		=   type_vocab_size
   lowercase__	: Union[str, Any]     		=   initializer_range
   lowercase__	: Dict     		=   layer_norm_eps
   lowercase__	: Tuple     		=   embedding_size
   lowercase__	: List[str]     		=   head_ratio
   lowercase__	: Dict     		=   conv_kernel_size
   lowercase__	: Dict     		=   num_groups
   lowercase__	: int     		=   classifier_dropout



class    _snake_case (						UpperCAmelCase_				):


 @property
 def   lowercase__  (       self):


   '''simple docstring'''




   if self.task == "multiple-choice":
     lowercase__	: Union[str, Any]     		=   {0: """batch""", 1: """choice""", 2: """sequence"""}
   else:
     lowercase__	: str     		=   {0: """batch""", 1: """sequence"""}
   return OrderedDict(
       [
           ("""input_ids""", dynamic_axis),
           ("""attention_mask""", dynamic_axis),
           ("""token_type_ids""", dynamic_axis),
       ])






