Input
Input is a Keras constructor that creates a symbolic tensor specifying the shape and data type accepted by a model.
Deep Learning with Python, Third Edition
A Keras constructor used to create symbolic input objects that specify the expected shape and dtype of model inputs.
- How it is used
- Creates symbolic model inputs for Functional graphs and prebuilds Sequential models so shapes are available during construction.
- How deep it goes
- Defines shape, dtype, naming, symbolic propagation, and multi-input use, but does not detail Input implementation internals.
- Examples
- Uses a two-Dense-layer classifier, a three-input ticket model, and an advance-shaped Sequential model.
- What you can do after
- Build Functional and prebuilt Sequential models by declaring input specifications before supplying data.
Read how Deep Learning with Python, Third Edition explains Input →
Deep Learning with R, Third Edition
keras_input() is a Keras function that creates a symbolic input tensor specifying the shape and data type accepted by a model.
- How it is used
- Defines the accepted data specifications when constructing Functional API models.
- How deep it goes
- Explains symbolic metadata and layer connections, stopping short of actual data processing.
- Examples
- Uses a three-feature Dense model and a ticket classifier with title, body, and tag inputs.
- What you can do after
- Build it from scratch by declaring model inputs and connecting them to layers and outputs.
Read how Deep Learning with R, Third Edition explains Input →
Related concepts
- symbolic tensorproduces · A symbolic tensor is a tensor-like placeholder that specifies shape and data type without containing actual data values.
- generationconfigures · Generation is the computational production of outputs from supplied inputs or context, often by applying a model to produce predictions or new content.
- inputkind of · An input is a value, information, or signal supplied to a system, computation, or interface for processing or to influence its behavior.
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