codingutf8 2023 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 vivit model configuration from configurationutils import pretrainedconfig from utils import logging logger logging getloggername vivitpretrainedconfigarchivemap googlevivitb16x2kinetics400 https huggingface cogooglevivitb16x2kinetics400resolvemainconfig json see all vivit models at https huggingface comodels filtervivit class vivitconfigpretrainedconfig r this is the configuration class to store the configuration of a vivitmodel it is used to instantiate a vivit 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 vivit googlevivitb16x2kinetics400https huggingface cogooglevivitb16x2kinetics400 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 numframes int optional defaults to 32 the number of frames in each video tubeletsize listint optional defaults to 2 16 16 the size resolution of each tubelet numchannels int optional defaults to 3 the number of input channels 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 gelufast the nonlinear activation function function or string in the encoder and pooler if string gelu relu selu gelufast and gelunew are supported hiddendropoutprob float optional defaults to 0 0 the dropout probability 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 1e06 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 example python from transformers import vivitconfig vivitmodel initializing a vivit googlevivitb16x2kinetics400 style configuration configuration vivitconfig initializing a model with random weights from the googlevivitb16x2kinetics400 style configuration model vivitmodelconfiguration accessing the model configuration configuration model config modeltype vivit def init self imagesize224 numframes32 tubeletsize2 16 16 numchannels3 hiddensize768 numhiddenlayers12 numattentionheads12 intermediatesize3072 hiddenactgelufast hiddendropoutprob0 0 attentionprobsdropoutprob0 0 initializerrange0 02 layernormeps1e06 qkvbiastrue kwargs 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 imagesize imagesize self numframes numframes self tubeletsize tubeletsize self numchannels numchannels self qkvbias qkvbias super initkwargs coding utf 8 2023 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 vivit model configuration see all vivit models at https huggingface co models filter vivit this is the configuration class to store the configuration of a vivitmodel it is used to instantiate a vivit 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 vivit google vivit b 16x2 kinetics400 https huggingface co google vivit b 16x2 kinetics400 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 num_frames int optional defaults to 32 the number of frames in each video tubelet_size list int optional defaults to 2 16 16 the size resolution of each tubelet num_channels int optional defaults to 3 the number of input channels 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_fast the non linear activation function function or string in the encoder and pooler if string gelu relu selu gelu_fast and gelu_new are supported hidden_dropout_prob float optional defaults to 0 0 the dropout probability 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 06 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 example python from transformers import vivitconfig vivitmodel initializing a vivit google vivit b 16x2 kinetics400 style configuration configuration vivitconfig initializing a model with random weights from the google vivit b 16x2 kinetics400 style configuration model vivitmodel configuration accessing the model configuration configuration model config
from ...configuration_utils import PretrainedConfig
from ...utils import logging


logger = logging.get_logger(__name__)

VIVIT_PRETRAINED_CONFIG_ARCHIVE_MAP = {
    "google/vivit-b-16x2-kinetics400": (
        "https://huggingface.co/google/vivit-b-16x2-kinetics400/resolve/main/config.json"
    ),
    
}


class VivitConfig(PretrainedConfig):
    r

    model_type = "vivit"

    def __init__(
        self,
        image_size=224,
        num_frames=32,
        tubelet_size=[2, 16, 16],
        num_channels=3,
        hidden_size=768,
        num_hidden_layers=12,
        num_attention_heads=12,
        intermediate_size=3072,
        hidden_act="gelu_fast",
        hidden_dropout_prob=0.0,
        attention_probs_dropout_prob=0.0,
        initializer_range=0.02,
        layer_norm_eps=1e-06,
        qkv_bias=True,
        **kwargs,
    ):
        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.image_size = image_size
        self.num_frames = num_frames
        self.tubelet_size = tubelet_size
        self.num_channels = num_channels
        self.qkv_bias = qkv_bias

        super().__init__(**kwargs)