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Keras Convolution 1D Layer

KNIME Deep Learning - Keras Integration version 4.3.0.v202012011122 by KNIME AG, Zurich, Switzerland

This layer creates a convolution kernel that is convolved with the layer input over a single dimension. Corresponds to the Keras Convolution 1D 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
The length of the 1D convolution window.
Strides
The stride length of the convolution. Specifying any stride value != 1 is incompatible with specifying any dilation_rate value != 1.
Padding
Different padding modes to apply to the spatial dimensions (excluding the batch and channel dimensions) of the inputs before the pooling operation. The padding will be done with zeroes. A detailed explanation of the different modes can be found here .
  • Valid: No padding
  • Same: Padding such that the spatial output dimension do not change.
  • Causal: Causal (dilated) convolutions, e.g. output[t] does not depend on input[t + 1] . A zero padding is used such that the output has the same length as the original input. Useful when modeling temporal data where the model should not violate the temporal order. See WaveNet: A Generative Model for Raw Audio, section 2.1
Dilation rate
Specifying the dilation rate to use for dilated convolution. Currently, specifying any dilation_rate value != 1 is incompatible with specifying any stride value != 1.
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

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The Keras deep learning network to which to add a Convolution 1D layer.

Output Ports

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The Keras deep learning network with an added Convolution 1D layer.

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Workflows

Installation

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

KNIME 4.3

A zipped version of the software site can be downloaded here.

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