
'''simple docstring'''



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


_lowercase          =						logging.get_logger(__name__)

_lowercase          =						{
    """facebook/data2vec-vision-base-ft""": (
        """https://huggingface.co/facebook/data2vec-vision-base-ft/resolve/main/config.json"""
    ),
}




class     UpperCAmelCase_	(						_SCREAMING_SNAKE_CASE					):






						'''simple docstring'''






						_lowercase						: List[str]										=  '''data2vec-vision'''




						def __init__(   self       ,  _lowercase=768       ,  _lowercase=12       ,  _lowercase=12       ,  _lowercase=3_072       ,  _lowercase="gelu"       ,  _lowercase=0.0       ,  _lowercase=0.0       ,  _lowercase=0.02       ,  _lowercase=1e-12       ,  _lowercase=224       ,  _lowercase=16       ,  _lowercase=3       ,  _lowercase=False       ,  _lowercase=False       ,  _lowercase=False       ,  _lowercase=False       ,  _lowercase=0.1       ,  _lowercase=0.1       ,  _lowercase=True       ,  _lowercase=[3, 5, 7, 11]       ,  _lowercase=[1, 2, 3, 6]       ,  _lowercase=True       ,  _lowercase=0.4       ,  _lowercase=256       ,  _lowercase=1       ,  _lowercase=False       ,  _lowercase=255       ,  **_lowercase       ,  ):

												"""simple docstring"""



												super().__init__(**_lowercase )

												_lowerCAmelCase    		=					hidden_size
												_lowerCAmelCase    		=					num_hidden_layers
												_lowerCAmelCase    		=					num_attention_heads
												_lowerCAmelCase    		=					intermediate_size
												_lowerCAmelCase    		=					hidden_act
												_lowerCAmelCase    		=					hidden_dropout_prob
												_lowerCAmelCase    		=					attention_probs_dropout_prob
												_lowerCAmelCase    		=					initializer_range
												_lowerCAmelCase    		=					layer_norm_eps

												_lowerCAmelCase    		=					image_size
												_lowerCAmelCase    		=					patch_size
												_lowerCAmelCase    		=					num_channels
												_lowerCAmelCase    		=					use_mask_token
												_lowerCAmelCase    		=					use_absolute_position_embeddings
												_lowerCAmelCase    		=					use_relative_position_bias
												_lowerCAmelCase    		=					use_shared_relative_position_bias
												_lowerCAmelCase    		=					layer_scale_init_value
												_lowerCAmelCase    		=					drop_path_rate
												_lowerCAmelCase    		=					use_mean_pooling
												# decode head attributes (semantic segmentation)
												_lowerCAmelCase    		=					out_indices
												_lowerCAmelCase    		=					pool_scales
												# auxiliary head attributes (semantic segmentation)
												_lowerCAmelCase    		=					use_auxiliary_head
												_lowerCAmelCase    		=					auxiliary_loss_weight
												_lowerCAmelCase    		=					auxiliary_channels
												_lowerCAmelCase    		=					auxiliary_num_convs
												_lowerCAmelCase    		=					auxiliary_concat_input
												_lowerCAmelCase    		=					semantic_loss_ignore_index






class     UpperCAmelCase_	(						_SCREAMING_SNAKE_CASE					):






						'''simple docstring'''






						_lowercase						: Union[str, Any]										=  version.parse('''1.11'''					)




						@property
						def    _lowercase      (   self ):

												"""simple docstring"""



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




						@property
						def    _lowercase      (   self ):

												"""simple docstring"""



												return 1e-4


'''simple docstring'''



from typing import TYPE_CHECKING

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


_lowercase          =						{"""configuration_vit_mae""": ["""VIT_MAE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """ViTMAEConfig"""]}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_lowercase          =						[
						    """VIT_MAE_PRETRAINED_MODEL_ARCHIVE_LIST""",
						    """ViTMAEForPreTraining""",
						    """ViTMAELayer""",
						    """ViTMAEModel""",
						    """ViTMAEPreTrainedModel""",
						]

try:
						if not is_tf_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_lowercase          =						[
						    """TFViTMAEForPreTraining""",
						    """TFViTMAEModel""",
						    """TFViTMAEPreTrainedModel""",
						]

if TYPE_CHECKING:
						from .configuration_vit_mae import VIT_MAE_PRETRAINED_CONFIG_ARCHIVE_MAP, ViTMAEConfig

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_vit_mae import (
												    VIT_MAE_PRETRAINED_MODEL_ARCHIVE_LIST,
												    ViTMAEForPreTraining,
												    ViTMAELayer,
												    ViTMAEModel,
												    ViTMAEPreTrainedModel,
												)

						try:
												if not is_tf_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_tf_vit_mae import TFViTMAEForPreTraining, TFViTMAEModel, TFViTMAEPreTrainedModel


else:
						import sys

						_lowercase          =						_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)
