View Source Bumblebee.Vision.ConvNext (Bumblebee v0.5.3)
ConvNeXT model family.
Architectures
:base- plain ConvNeXT without any head on top:for_image_classification- ConvNeXT with a classification head. The head consists of a single dense layer on top of the pooled features
Inputs
"pixel_values"- {batch_size, height, width, num_channels}Featurized image pixel values (224x224).
Configuration
:num_channels- the number of channels in the input. Defaults to3:patch_size- the size of the patch spatial dimensions. Defaults to4:hidden_sizes- the dimensionality of hidden layers at each stage. Defaults to[96, 192, 384, 768]:depths- the depth (number of residual blocks) at each stage. Defaults to[3, 3, 9, 3]:activation- the activation function. Defaults to:gelu:scale_initial_value- the initial value for scaling layers. Defaults to1.0e-6:drop_path_rate- the drop path rate used to for stochastic depth. Defaults to0.0:layer_norm_epsilon- the epsilon used by the layer normalization layers. Defaults to1.0e-12:initializer_scale- the standard deviation of the normal initializer used for initializing kernel parameters. Defaults to0.02:output_hidden_states- whether the model should return all hidden states. Defaults tofalse:num_labels- the number of labels to use in the last layer for the classification task. Defaults to2:id_to_label- a map from class index to label. Defaults to%{}