The base LSTMCell class implements the main functionality required, such as the build method, whereas the LSTM class only container an entry point: the call method, as well as a bunch of getters to retrieve attribute values. LSTMCell is the base class, which is used as a cell that is used inside the LSTM class.
as normal we used to use the standard LSTM class in your model as a normal layer. If you have a GPU at your disposal, you might want to use the version of the layer that is optimised with CUDA for execution on a GPU. As per the documentation:
Note that this cell is not optimized for performance on GPU. Please use tf.keras.layers.CuDNNLSTM for better performance on GPU.
There is also a GRU layer as well as a CuDNNGRU layer.
If you want to tweak how things work under the hood, you might create a class and inherit from the LSTMCell, or even the base class:
But you would have to implement many things for yourself.
来自于
https://datascience.stackexchange.com/questions/54549/in-tensorflow-2-0-what-is-the-different-between-lstm-and-lstmcell-objects
