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Keras Locally Connected 2D Layer

DeprecatedKNIME Deep Learning - Keras Integration version 4.0.0.v201906111427 by KNIME AG, Zurich, Switzerland

This layer works similarly to a convolution layer, except that weights are unshared, that is, a different set of filters is applied at each different patch of the input. Corresponds to the Keras Locally Connected 2D Layer.

Options

Name prefix
The name prefix of the layer. The prefix is complemented by an index suffix to obtain a unique layer name. If this option is unchecked, the name prefix is derived from the layer type.
Filters
The dimensionality of the output space (i.e. the number of output filters in the convolution).
Kernel size
A tuple of 2 integers, specifying the height and width of the 2D convolution window.
Strides
A tuple of 2 integers, specifying the strides of the convolution along the height and width. Specifying any stride value != 1 is incompatible with specifying any dilation_rate value != 1.
Padding
Locally Connected Layers only support 'valid' padding.
Activation function
The activation function to use.
Use bias?
If checked, a bias vector will be used.
Kernel initializer
Initializer for the kernel weights matrix.
Bias initializer
Initializer for the bias vector.
Kernel regularizer
Regularizer function applied to the kernel weights matrix.
Bias regularizer
Regularizer function applied to the bias vector.
Activation regularizer
Regularizer function applied to the output of the layer (its "activation").
Kernel constraint
Constraint function applied to the kernel matrix.
Bias constraint
Constraint function applied to the bias vector.

Input Ports

The Keras deep learning network to which to add a Locally Connected 2D layer.

Output Ports

The Keras deep learning network with an added Locally Connected 2D layer.

Installation

To use this node in KNIME, install KNIME Deep Learning - Keras Integration from the following update site:

KNIME 4.0
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