



"""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,
)


lowerCAmelCase_   						=   {
    '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:
							lowerCAmelCase_   						=   ['OwlViTFeatureExtractor']
							lowerCAmelCase_   						=   ['OwlViTImageProcessor']

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowerCAmelCase_   						=   [
							    '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

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







from typing import List

from ...configuration_utils import PretrainedConfig
from ...utils import logging


SCREAMING_SNAKE_CASE_						   =       logging.get_logger(__name__)

SCREAMING_SNAKE_CASE_						   =       {
    """snap-research/efficientformer-l1-300""": (
        """https://huggingface.co/snap-research/efficientformer-l1-300/resolve/main/config.json"""
    ),
}

class 		UpperCamelCase__ (      lowerCAmelCase_   ):



     '''simple docstring'''

     __snake_case    :	int			=			"efficientformer"






     def __init__(							self						:    Optional[int]						,lowerCamelCase__						:    List[int] = [3, 2, 6, 4]						,lowerCamelCase__						:    List[int] = [48, 96, 224, 448]						,lowerCamelCase__						:    List[bool] = [True, True, True, True]						,lowerCamelCase__						:    int = 448						,lowerCamelCase__						:    int = 32						,lowerCamelCase__						:    int = 4						,lowerCamelCase__						:    int = 7						,lowerCamelCase__						:    int = 5						,lowerCamelCase__						:    int = 8						,lowerCamelCase__						:    int = 4						,lowerCamelCase__						:    float = 0.0						,lowerCamelCase__						:    int = 16						,lowerCamelCase__						:    int = 3						,lowerCamelCase__						:    int = 3						,lowerCamelCase__						:    int = 3						,lowerCamelCase__						:    int = 2						,lowerCamelCase__						:    int = 1						,lowerCamelCase__						:    float = 0.0						,lowerCamelCase__						:    int = 1						,lowerCamelCase__						:    bool = True						,lowerCamelCase__						:    bool = True						,lowerCamelCase__						:    float = 1e-5						,lowerCamelCase__						:    str = "gelu"						,lowerCamelCase__						:    float = 0.02						,lowerCamelCase__						:    float = 1e-1_2						,lowerCamelCase__						:    int = 224						,lowerCamelCase__						:    float = 1e-0_5						,**lowerCamelCase__						:    str						,)     ->		None:




           '''simple docstring'''


           super().__init__(**lowerCamelCase__       )

           SCREAMING_SNAKE_CASE		=						hidden_act
           SCREAMING_SNAKE_CASE		=						hidden_dropout_prob
           SCREAMING_SNAKE_CASE		=						hidden_sizes
           SCREAMING_SNAKE_CASE		=						num_hidden_layers
           SCREAMING_SNAKE_CASE		=						num_attention_heads
           SCREAMING_SNAKE_CASE		=						initializer_range
           SCREAMING_SNAKE_CASE		=						layer_norm_eps
           SCREAMING_SNAKE_CASE		=						patch_size
           SCREAMING_SNAKE_CASE		=						num_channels
           SCREAMING_SNAKE_CASE		=						depths
           SCREAMING_SNAKE_CASE		=						mlp_expansion_ratio
           SCREAMING_SNAKE_CASE		=						downsamples
           SCREAMING_SNAKE_CASE		=						dim
           SCREAMING_SNAKE_CASE		=						key_dim
           SCREAMING_SNAKE_CASE		=						attention_ratio
           SCREAMING_SNAKE_CASE		=						resolution
           SCREAMING_SNAKE_CASE		=						pool_size
           SCREAMING_SNAKE_CASE		=						downsample_patch_size
           SCREAMING_SNAKE_CASE		=						downsample_stride
           SCREAMING_SNAKE_CASE		=						downsample_pad
           SCREAMING_SNAKE_CASE		=						drop_path_rate
           SCREAMING_SNAKE_CASE		=						num_metaad_blocks
           SCREAMING_SNAKE_CASE		=						distillation
           SCREAMING_SNAKE_CASE		=						use_layer_scale
           SCREAMING_SNAKE_CASE		=						layer_scale_init_value
           SCREAMING_SNAKE_CASE		=						image_size
           SCREAMING_SNAKE_CASE		=						batch_norm_eps


