Keras Convolutional LSTM 2D Layer (deprecated)

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 .

Input ports

1. Type: Keras Deep Learning Network
   Keras Network
   The Keras deep learning network to which to add an 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.
2. Type: PortObject
   Keras Network
   An optional Keras deep learning network providing the first initial state for this 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.
3. Type: PortObject
   Keras Network
   > An optional Keras deep learning network providing the second initial state for this 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.

Output ports

1. Type: Keras Deep Learning Network
   Keras Network
   The Keras deep learning network with an added ConvLSTM2D layer.

External resources

• KNIME Deep Learning Keras Integration