


'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCAmelCase  =				logging.get_logger(__name__)

lowerCAmelCase  =				{
    """MCG-NJU/videomae-base""": """https://huggingface.co/MCG-NJU/videomae-base/resolve/main/config.json""",
}






class 					lowerCAmelCase_     (    UpperCAmelCase  ):
       __UpperCAmelCase				='videomae'






       def __init__(   self ,    _UpperCamelCase=224 ,    _UpperCamelCase=16 ,    _UpperCamelCase=3 ,    _UpperCamelCase=16 ,    _UpperCamelCase=2 ,    _UpperCamelCase=768 ,    _UpperCamelCase=12 ,    _UpperCamelCase=12 ,    _UpperCamelCase=3072 ,    _UpperCamelCase="gelu" ,    _UpperCamelCase=0.0 ,    _UpperCamelCase=0.0 ,    _UpperCamelCase=0.02 ,    _UpperCamelCase=1e-12 ,    _UpperCamelCase=True ,    _UpperCamelCase=True ,    _UpperCamelCase=6 ,    _UpperCamelCase=384 ,    _UpperCamelCase=4 ,    _UpperCamelCase=1536 ,    _UpperCamelCase=True ,    **_UpperCamelCase ,    )->			Optional[int]:
            super().__init__(**_UpperCamelCase      )

            _A				=       image_size
            _A				=       patch_size
            _A				=       num_channels
            _A				=       num_frames
            _A				=       tubelet_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				=       initializer_range
            _A				=       layer_norm_eps
            _A				=       qkv_bias
            _A				=       use_mean_pooling

            _A				=       decoder_num_attention_heads
            _A				=       decoder_hidden_size
            _A				=       decoder_num_hidden_layers
            _A				=       decoder_intermediate_size
            _A				=       norm_pix_loss









'''simple docstring'''
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
)


lowerCAmelCase  =				{
    """configuration_convnextv2""": [
        """CONVNEXTV2_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """ConvNextV2Config""",
    ]
}

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCAmelCase  =				[
        """CONVNEXTV2_PRETRAINED_MODEL_ARCHIVE_LIST""",
        """ConvNextV2ForImageClassification""",
        """ConvNextV2Model""",
        """ConvNextV2PreTrainedModel""",
        """ConvNextV2Backbone""",
    ]


if TYPE_CHECKING:
    from .configuration_convnextva import (
        CONVNEXTV2_PRETRAINED_CONFIG_ARCHIVE_MAP,
        ConvNextVaConfig,
    )

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_convnextva import (
            CONVNEXTV2_PRETRAINED_MODEL_ARCHIVE_LIST,
            ConvNextVaBackbone,
            ConvNextVaForImageClassification,
            ConvNextVaModel,
            ConvNextVaPreTrainedModel,
        )

else:
    import sys

    lowerCAmelCase  =				_LazyModule(__name__, globals()["""__file__"""], _import_structure)





