codingutf8 2022 the huggingface inc team 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 orglicenseslicense2 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 videomae model configuration from configurationutils import pretrainedconfig from utils import logging logger logging getloggername videomaepretrainedconfigarchivemap mcgnjuvideomaebase https huggingface comcgnjuvideomaebaseresolvemainconfig json class videomaeconfigpretrainedconfig r this is the configuration class to store the configuration of a videomaemodel it is used to instantiate a videomae model according to the specified arguments defining the model architecture instantiating a configuration with the defaults will yield a similar configuration to that of the videomae mcgnjuvideomaebasehttps huggingface comcgnjuvideomaebase architecture configuration objects inherit from pretrainedconfig and can be used to control the model outputs read the documentation from pretrainedconfig for more information args imagesize int optional defaults to 224 the size resolution of each image patchsize int optional defaults to 16 the size resolution of each patch numchannels int optional defaults to 3 the number of input channels numframes int optional defaults to 16 the number of frames in each video tubeletsize int optional defaults to 2 the number of tubelets hiddensize int optional defaults to 768 dimensionality of the encoder layers and the pooler layer numhiddenlayers int optional defaults to 12 number of hidden layers in the transformer encoder numattentionheads int optional defaults to 12 number of attention heads for each attention layer in the transformer encoder intermediatesize int optional defaults to 3072 dimensionality of the intermediate i e feedforward layer in the transformer encoder hiddenact str or function optional defaults to gelu the nonlinear activation function function or string in the encoder and pooler if string gelu relu selu and gelunew are supported hiddendropoutprob float optional defaults to 0 0 the dropout probabilitiy for all fully connected layers in the embeddings encoder and pooler attentionprobsdropoutprob float optional defaults to 0 0 the dropout ratio for the attention probabilities initializerrange float optional defaults to 0 02 the standard deviation of the truncatednormalinitializer for initializing all weight matrices layernormeps float optional defaults to 1e12 the epsilon used by the layer normalization layers qkvbias bool optional defaults to true whether to add a bias to the queries keys and values usemeanpooling bool optional defaults to true whether to mean pool the final hidden states instead of using the final hidden state of the cls token decodernumattentionheads int optional defaults to 6 number of attention heads for each attention layer in the decoder decoderhiddensize int optional defaults to 384 dimensionality of the decoder decodernumhiddenlayers int optional defaults to 4 number of hidden layers in the decoder decoderintermediatesize int optional defaults to 1536 dimensionality of the intermediate i e feedforward layer in the decoder normpixloss bool optional defaults to true whether to normalize the target patch pixels example python from transformers import videomaeconfig videomaemodel initializing a videomae videomaebase style configuration configuration videomaeconfig randomly initializing a model from the configuration model videomaemodelconfiguration accessing the model configuration configuration model config modeltype videomae def init self imagesize224 patchsize16 numchannels3 numframes16 tubeletsize2 hiddensize768 numhiddenlayers12 numattentionheads12 intermediatesize3072 hiddenactgelu hiddendropoutprob0 0 attentionprobsdropoutprob0 0 initializerrange0 02 layernormeps1e12 qkvbiastrue usemeanpoolingtrue decodernumattentionheads6 decoderhiddensize384 decodernumhiddenlayers4 decoderintermediatesize1536 normpixlosstrue kwargs super initkwargs self imagesize imagesize self patchsize patchsize self numchannels numchannels self numframes numframes self tubeletsize tubeletsize self hiddensize hiddensize self numhiddenlayers numhiddenlayers self numattentionheads numattentionheads self intermediatesize intermediatesize self hiddenact hiddenact self hiddendropoutprob hiddendropoutprob self attentionprobsdropoutprob attentionprobsdropoutprob self initializerrange initializerrange self layernormeps layernormeps self qkvbias qkvbias self usemeanpooling usemeanpooling self decodernumattentionheads decodernumattentionheads self decoderhiddensize decoderhiddensize self decodernumhiddenlayers decodernumhiddenlayers self decoderintermediatesize decoderintermediatesize self normpixloss normpixloss coding utf 8 2022 the huggingface inc team 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 videomae model configuration this is the configuration class to store the configuration of a videomaemodel it is used to instantiate a videomae model according to the specified arguments defining the model architecture instantiating a configuration with the defaults will yield a similar configuration to that of the videomae mcg nju videomae base https huggingface co mcg nju videomae base architecture configuration objects inherit from pretrainedconfig and can be used to control the model outputs read the documentation from pretrainedconfig for more information args image_size int optional defaults to 224 the size resolution of each image patch_size int optional defaults to 16 the size resolution of each patch num_channels int optional defaults to 3 the number of input channels num_frames int optional defaults to 16 the number of frames in each video tubelet_size int optional defaults to 2 the number of tubelets hidden_size int optional defaults to 768 dimensionality of the encoder layers and the pooler layer num_hidden_layers int optional defaults to 12 number of hidden layers in the transformer encoder num_attention_heads int optional defaults to 12 number of attention heads for each attention layer in the transformer encoder intermediate_size int optional defaults to 3072 dimensionality of the intermediate i e feed forward layer in the transformer encoder hidden_act str or function optional defaults to gelu the non linear activation function function or string in the encoder and pooler if string gelu relu selu and gelu_new are supported hidden_dropout_prob float optional defaults to 0 0 the dropout probabilitiy for all fully connected layers in the embeddings encoder and pooler attention_probs_dropout_prob float optional defaults to 0 0 the dropout ratio for the attention probabilities initializer_range float optional defaults to 0 02 the standard deviation of the truncated_normal_initializer for initializing all weight matrices layer_norm_eps float optional defaults to 1e 12 the epsilon used by the layer normalization layers qkv_bias bool optional defaults to true whether to add a bias to the queries keys and values use_mean_pooling bool optional defaults to true whether to mean pool the final hidden states instead of using the final hidden state of the cls token decoder_num_attention_heads int optional defaults to 6 number of attention heads for each attention layer in the decoder decoder_hidden_size int optional defaults to 384 dimensionality of the decoder decoder_num_hidden_layers int optional defaults to 4 number of hidden layers in the decoder decoder_intermediate_size int optional defaults to 1536 dimensionality of the intermediate i e feed forward layer in the decoder norm_pix_loss bool optional defaults to true whether to normalize the target patch pixels example python from transformers import videomaeconfig videomaemodel initializing a videomae videomae base style configuration configuration videomaeconfig randomly initializing a model from the configuration model videomaemodel configuration accessing the model configuration configuration model config
from ...configuration_utils import PretrainedConfig
from ...utils import logging


logger = logging.get_logger(__name__)

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


class VideoMAEConfig(PretrainedConfig):
    r

    model_type = "videomae"

    def __init__(
        self,
        image_size=224,
        patch_size=16,
        num_channels=3,
        num_frames=16,
        tubelet_size=2,
        hidden_size=768,
        num_hidden_layers=12,
        num_attention_heads=12,
        intermediate_size=3072,
        hidden_act="gelu",
        hidden_dropout_prob=0.0,
        attention_probs_dropout_prob=0.0,
        initializer_range=0.02,
        layer_norm_eps=1e-12,
        qkv_bias=True,
        use_mean_pooling=True,
        decoder_num_attention_heads=6,
        decoder_hidden_size=384,
        decoder_num_hidden_layers=4,
        decoder_intermediate_size=1536,
        norm_pix_loss=True,
        **kwargs,
    ):
        super().__init__(**kwargs)

        self.image_size = image_size
        self.patch_size = patch_size
        self.num_channels = num_channels
        self.num_frames = num_frames
        self.tubelet_size = tubelet_size

        self.hidden_size = hidden_size
        self.num_hidden_layers = num_hidden_layers
        self.num_attention_heads = num_attention_heads
        self.intermediate_size = intermediate_size
        self.hidden_act = hidden_act
        self.hidden_dropout_prob = hidden_dropout_prob
        self.attention_probs_dropout_prob = attention_probs_dropout_prob
        self.initializer_range = initializer_range
        self.layer_norm_eps = layer_norm_eps
        self.qkv_bias = qkv_bias
        self.use_mean_pooling = use_mean_pooling

        self.decoder_num_attention_heads = decoder_num_attention_heads
        self.decoder_hidden_size = decoder_hidden_size
        self.decoder_num_hidden_layers = decoder_num_hidden_layers
        self.decoder_intermediate_size = decoder_intermediate_size
        self.norm_pix_loss = norm_pix_loss