KNIME Deep Learning - Keras Integration version 4.3.0.v202012011122 by KNIME AG, Zurich, Switzerland
2D Convolutional Long-Short Term Memory (LSTM) layer. Similar to a normal LSTM, but the input and recurrent transformations are both convolutional. Corresponds to the ConvLSTM2D Keras layer .
ConvLSTM2D
layer.
The shape of the tensor must be [time, height, width, channel] or [time, channel, height, width] for data format channels_last and channels_first respectively.ConvLSTM2D
layer.
Note that if this port is connected, you also have to connect the second hidden state port.
The shape must be [height, width, channel] or [channel, height, width] depending on data format and the dimensionality of the channel dimension must match the number of filters of this layer.ConvLSTM2D
layer.
Note that if this port is connected, you also have to connect the first hidden state port.
The shape must be [height, width, channel] or [channel, height, width] depending on data format and the dimensionality of the channel dimension must match the number of filters of this layer.To use this node in KNIME, install KNIME Deep Learning - Keras Integration from the following update site:
A zipped version of the software site can be downloaded here.
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