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 timesformer model configuration from configurationutils import pretrainedconfig from utils import logging logger logging getloggername timesformerpretrainedconfigarchivemap facebooktimesformer https huggingface cofacebooktimesformerresolvemainconfig json class timesformerconfigpretrainedconfig r this is the configuration class to store the configuration of a timesformermodel it is used to instantiate a timesformer 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 timesformer facebooktimesformerbasefinetunedk600https huggingface cofacebooktimesformerbasefinetunedk600 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 8 the number of frames in each video 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 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 attentiontype str optional defaults to dividedspacetime the attention type to use must be one of dividedspacetime spaceonly jointspacetime droppathrate float optional defaults to 0 the dropout ratio for stochastic depth example python from transformers import timesformerconfig timesformermodel initializing a timesformer timesformerbase style configuration configuration timesformerconfig initializing a model from the configuration model timesformermodelconfiguration accessing the model configuration configuration model config modeltype timesformer def init self imagesize224 patchsize16 numchannels3 numframes8 hiddensize768 numhiddenlayers12 numattentionheads12 intermediatesize3072 hiddenactgelu hiddendropoutprob0 0 attentionprobsdropoutprob0 0 initializerrange0 02 layernormeps1e6 qkvbiastrue attentiontypedividedspacetime droppathrate0 kwargs super initkwargs self imagesize imagesize self patchsize patchsize self numchannels numchannels self numframes numframes 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 attentiontype attentiontype self droppathrate droppathrate 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 timesformer model configuration this is the configuration class to store the configuration of a timesformermodel it is used to instantiate a timesformer 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 timesformer facebook timesformer base finetuned k600 https huggingface co facebook timesformer base finetuned k600 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 8 the number of frames in each video 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 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 attention_type str optional defaults to divided_space_time the attention type to use must be one of divided_space_time space_only joint_space_time drop_path_rate float optional defaults to 0 the dropout ratio for stochastic depth example python from transformers import timesformerconfig timesformermodel initializing a timesformer timesformer base style configuration configuration timesformerconfig initializing a model from the configuration model timesformermodel configuration accessing the model configuration configuration model config
from ...configuration_utils import PretrainedConfig
from ...utils import logging


logger = logging.get_logger(__name__)

TIMESFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP = {
    "facebook/timesformer": "https://huggingface.co/facebook/timesformer/resolve/main/config.json",
}


class TimesformerConfig(PretrainedConfig):
    r

    model_type = "timesformer"

    def __init__(
        self,
        image_size=224,
        patch_size=16,
        num_channels=3,
        num_frames=8,
        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-6,
        qkv_bias=True,
        attention_type="divided_space_time",
        drop_path_rate=0,
        **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.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.attention_type = attention_type
        self.drop_path_rate = drop_path_rate