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Call()

call() is the Keras method that defines the forward computation a layer or model performs on its inputs.

How 2 Manning books explain it

Deep Learning with R, Third Edition

A call method defines the forward computation performed when a neural-network layer or model receives inputs.

How it is used
Defines the forward data transformation executed when a Keras layer or model receives inputs.
How deep it goes
Explains implementation through custom dense and diffusion examples, while deferring detailed build() behavior.
Examples
Uses SimpleDense, shape inference, diffusion denoising, and PyTorch linear models to demonstrate forward computation.
What you can do after
Build custom Keras layers that transform inputs and return outputs through a call() method.

Read how Deep Learning with R, Third Edition explains call() →

Deep Learning with Python, Third Edition

A Keras layer or model method that defines the forward computation applied to inputs.

How it is used
Defines the forward computation inside custom Keras layers and models.
How deep it goes
Explains implementation with matrix multiplication and activation, while deferring broader build mechanics to adjacent treatment.
Examples
Uses a SimpleDense layer that multiplies inputs by W, adds b, applies ReLU, and maps 784 features to 32 outputs.
What you can do after
Build it from scratch by implementing call() for a custom Keras layer’s forward computation.

Read how Deep Learning with Python, Third Edition explains call() →

Related concepts

These guides are generated from the text of Manning books by Manning's knowledge graph and link to the sections they draw on. The full books are available on liveBook and at manning.com.