The `keras.engine.InputSpec` class in Python's Keras library provides a specification for the shape and data type of input tensors in a neural network model. It allows users to define the expected properties of input data, such as the number of dimensions, the size of each dimension, and the data type of the elements. The `InputSpec` class is useful for ensuring compatibility between layers in a model, as it allows for consistent and predictable input shapes and types. By specifying the input requirements, the `InputSpec` class helps to validate and enforce the correct data format for the model, leading to more effective and reliable neural network training and inference.
Python InputSpec - 30 examples found. These are the top rated real world Python examples of keras.engine.InputSpec extracted from open source projects. You can rate examples to help us improve the quality of examples.