Prints layer names, output shapes, trainable scalar counts and parameter bytes. Parameter memory includes weights and biases at their actual element width; activations, object metadata and optimizer state are excluded from this count. Input declarations build the network at construction, so summary is usable before fit. A deferred model must first infer its shape from real data.

model.summary()