model.md

Model

Model groups layers into an object with training and inference features.

Methods

• Build - build model from config.
• inputs - get model inputs.
• outputs - get model outputs.
• getLayer - get layer by name.
• params - get all parameters of model.
• layers - get model layers.
• state - get model state.
• cfg - get model config.
• train - set training or evaluation mode.
• compile - create backend instance.
• forward - runs forward pass to compute outputs of each layer.
• backward - runs backward pass to accumulate gradients of each layer.

Example

dw::Placeholder in(dw::Shape{32, 100});
dw::Placeholder out = dw::Linear(50, "linear_0")(in);
                out = dw::ReLU("relu_1")(out);
                out = dw::Linear(10, "linear_2")(out);
                out = dw::Softmax("probs")(out);

dw::Model model(in, out);
model.compile();

dw::Tensor input(in.shape());
dw::Tensor output(model.outputs()[0].shape());
model.forward(input, output);