
"""simple docstring"""


from __future__ import annotations

from typing import Dict

from ...configuration_utils import PretrainedConfig


_lowercase				 =					{
    '''susnato/ernie-m-base_pytorch''': '''https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json''',
    '''susnato/ernie-m-large_pytorch''': '''https://huggingface.co/susnato/ernie-m-large_pytorch/blob/main/config.json''',
}







class 					lowerCAmelCase_					(   _lowercase     ):



						'''simple docstring'''


						_lowerCamelCase:     Union[str, Any]   =     '''ernie_m'''
						_lowerCamelCase:     Dict[str, str]   =     {"dropout": "classifier_dropout", "num_classes": "num_labels"}


						def __init__(			self  :   Optional[Any]	,A_  :   int = 25_0002	,A_  :   int = 768	,A_  :   int = 12	,A_  :   int = 12	,A_  :   int = 3072	,A_  :   str = "gelu"	,A_  :   float = 0.1	,A_  :   float = 0.1	,A_  :   int = 514	,A_  :   float = 0.02	,A_  :   int = 1	,A_  :   float = 1e-05	,A_  :   Tuple=None	,A_  :   str=False	,A_  :   Tuple=0.0	,**A_  :   Optional[Any]	,)  -> Dict:
							super().__init__(pad_token_id=A_	,**A_   )
							A     = vocab_size
							A     = hidden_size
							A     = num_hidden_layers
							A     = num_attention_heads
							A     = intermediate_size
							A     = hidden_act
							A     = hidden_dropout_prob
							A     = attention_probs_dropout_prob
							A     = max_position_embeddings
							A     = initializer_range
							A     = layer_norm_eps
							A     = classifier_dropout
							A     = is_decoder
							A     = act_dropout



'''simple docstring'''





from typing import TYPE_CHECKING

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


UpperCAmelCase__  			=				{
    '''configuration_owlvit''': [
        '''OWLVIT_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''OwlViTConfig''',
        '''OwlViTOnnxConfig''',
        '''OwlViTTextConfig''',
        '''OwlViTVisionConfig''',
    ],
    '''processing_owlvit''': ['''OwlViTProcessor'''],
}


try:
					if not is_vision_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					UpperCAmelCase__  			=				['''OwlViTFeatureExtractor''']
					UpperCAmelCase__  			=				['''OwlViTImageProcessor''']

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					UpperCAmelCase__  			=				[
					    '''OWLVIT_PRETRAINED_MODEL_ARCHIVE_LIST''',
					    '''OwlViTModel''',
					    '''OwlViTPreTrainedModel''',
					    '''OwlViTTextModel''',
					    '''OwlViTVisionModel''',
					    '''OwlViTForObjectDetection''',
					]

if TYPE_CHECKING:
					from .configuration_owlvit import (
					    OWLVIT_PRETRAINED_CONFIG_ARCHIVE_MAP,
					    OwlViTConfig,
					    OwlViTOnnxConfig,
					    OwlViTTextConfig,
					    OwlViTVisionConfig,
					)
					from .processing_owlvit import OwlViTProcessor

					try:
										if not is_vision_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .feature_extraction_owlvit import OwlViTFeatureExtractor
										from .image_processing_owlvit import OwlViTImageProcessor

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_owlvit import (
										    OWLVIT_PRETRAINED_MODEL_ARCHIVE_LIST,
										    OwlViTForObjectDetection,
										    OwlViTModel,
										    OwlViTPreTrainedModel,
										    OwlViTTextModel,
										    OwlViTVisionModel,
										)

else:
					import sys

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



