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The output of an LSTM cell or layer of cells is called the hidden state. This is confusing, because each LSTM cell retains an internal state that is not output, called the cell state, or c. The LSTM hidden state output for the last time step. The LSTM hidden state output for the last time step (again).
What is the hidden state?
Hidden states are technically speaking inputs to whatever we do at a given step, and they can only be computed by looking at data at previous time steps. Recurrent neural networks (RNNs) are neural networks with hidden states.
What is memory unit in LSTM?
What is memory unit and cell state in LSTM? LSTMs are recurrent networks where each neuron is replaced by a memory unit. The memory unit contains an actual neuron with a recurrent self-connection. The activations of those neurons within the memory units is called cell state of the LSTM network.
What is the use of LSTM hidden state?
The LSTM hidden state output for the last time step. The LSTM hidden state output for the last time step (again). The LSTM cell state for the last time step. The hidden state and the cell state could in turn be used to initialize the states of another LSTM layer with the same number of cells.
Does an LSTM have a cell state?
Another confusion for me was the following: LSTMs are referred to as fancy versions of vanilla RNNs. These vanilla RNNs do not have a cell state, they only have a hidden state and it is said that this hidden state serves as the memory for RNNs. So the obvious question then is: why does an LSTM have both a cell state and a hidden state?
What is the return_state argument used for in LSTM?
Keras provides the return_state argument to the LSTM layer that will provide access to the hidden state output (state_h) and the cell state (state_c).
Well, c n is the accumulated cell state that gets updated from the output of the previous timestep ( h n − 1 ), and the hidden state h n is the result of applying the output gate o n to some linear combination of the current cell_state c n. It should be noted that the “output” is the same thing as the “hidden state”.