
'''simple docstring'''


from collections import OrderedDict
from typing import Mapping

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


__lowercase							:				Tuple					=       logging.get_logger(__name__)

__lowercase							:				Union[str, Any]					=       {
    '''squeezebert/squeezebert-uncased''': (
        '''https://huggingface.co/squeezebert/squeezebert-uncased/resolve/main/config.json'''
    ),
    '''squeezebert/squeezebert-mnli''': '''https://huggingface.co/squeezebert/squeezebert-mnli/resolve/main/config.json''',
    '''squeezebert/squeezebert-mnli-headless''': (
        '''https://huggingface.co/squeezebert/squeezebert-mnli-headless/resolve/main/config.json'''
    ),
}

class 		__lowercase			(					_lowercase      ):
   lowerCamelCase     :						Union[str, Any]		 =     SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP
   lowerCamelCase     :						Any		 =     "squeezebert"

   def __init__(self     ,				A=3_0_5_2_2     ,				A=7_6_8     ,				A=1_2     ,				A=1_2     ,				A=3_0_7_2     ,				A="gelu"     ,				A=0.1     ,				A=0.1     ,				A=5_1_2     ,				A=2     ,				A=0.02     ,				A=1E-12     ,				A=0     ,				A=7_6_8     ,				A=4     ,				A=4     ,				A=4     ,				A=1     ,				A=4     ,				A=4     ,				**A     ,				):
        super().__init__(pad_token_id=A     ,				**A )

        lowerCamelCase_   : Optional[int]       =						vocab_size
        lowerCamelCase_   : Optional[int]       =						hidden_size
        lowerCamelCase_   : List[str]       =						num_hidden_layers
        lowerCamelCase_   : Any       =						num_attention_heads
        lowerCamelCase_   : Union[str, Any]       =						hidden_act
        lowerCamelCase_   : str       =						intermediate_size
        lowerCamelCase_   : Union[str, Any]       =						hidden_dropout_prob
        lowerCamelCase_   : Any       =						attention_probs_dropout_prob
        lowerCamelCase_   : Dict       =						max_position_embeddings
        lowerCamelCase_   : Tuple       =						type_vocab_size
        lowerCamelCase_   : Tuple       =						initializer_range
        lowerCamelCase_   : str       =						layer_norm_eps
        lowerCamelCase_   : Tuple       =						embedding_size
        lowerCamelCase_   : int       =						q_groups
        lowerCamelCase_   : Union[str, Any]       =						k_groups
        lowerCamelCase_   : Union[str, Any]       =						v_groups
        lowerCamelCase_   : Optional[Any]       =						post_attention_groups
        lowerCamelCase_   : List[Any]       =						intermediate_groups
        lowerCamelCase_   : str       =						output_groups

class 		__lowercase			(					_lowercase      ):

   @property
   def     UpperCAmelCase__	(self ):
        if self.task == "multiple-choice":
             lowerCamelCase_   : List[str]       =						{0: '''batch''', 1: '''choice''', 2: '''sequence'''}
        else:
             lowerCamelCase_   : Tuple       =						{0: '''batch''', 1: '''sequence'''}
        return OrderedDict(
            [
                ('''input_ids''', dynamic_axis),
                ('''attention_mask''', dynamic_axis),
                ('''token_type_ids''', dynamic_axis),
            ] )




'''simple docstring'''


from typing import TYPE_CHECKING

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


__lowercase							:				List[str]					=       {
    '''configuration_sam''': [
        '''SAM_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''SamConfig''',
        '''SamMaskDecoderConfig''',
        '''SamPromptEncoderConfig''',
        '''SamVisionConfig''',
    ],
    '''processing_sam''': ['''SamProcessor'''],
}


try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					__lowercase							:				List[Any]					=       [
					    '''SAM_PRETRAINED_MODEL_ARCHIVE_LIST''',
					    '''SamModel''',
					    '''SamPreTrainedModel''',
					]
try:
					if not is_tf_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					__lowercase							:				int					=       [
					    '''TF_SAM_PRETRAINED_MODEL_ARCHIVE_LIST''',
					    '''TFSamModel''',
					    '''TFSamPreTrainedModel''',
					]
try:
					if not is_vision_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					__lowercase							:				str					=       ['''SamImageProcessor''']


if TYPE_CHECKING:
					from .configuration_sam import (
					    SAM_PRETRAINED_CONFIG_ARCHIVE_MAP,
					    SamConfig,
					    SamMaskDecoderConfig,
					    SamPromptEncoderConfig,
					    SamVisionConfig,
					)
					from .processing_sam import SamProcessor

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_sam import SAM_PRETRAINED_MODEL_ARCHIVE_LIST, SamModel, SamPreTrainedModel

					try:
										if not is_tf_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_tf_sam import TF_SAM_PRETRAINED_MODEL_ARCHIVE_LIST, TFSamModel, TFSamPreTrainedModel

					try:
										if not is_vision_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .image_processing_sam import SamImageProcessor

else:
					import sys

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


