Iterates over the time dimension of a tensor.

step_function RNN step function. Args; input; Tensor with shape (samples, ...) (no time dimension), representing input for the batch of samples at a certain time step. states; List of tensors. Returns; output; Tensor with shape (samples, output_dim) (no time dimension). new_states; List of tensors, same length and shapes as 'states'. The first state in the list must be the output tensor at the previous timestep.
inputs Tensor of temporal data of shape (samples, time, ...) (at least 3D), or nested tensors, and each of which has shape (samples, time, ...).
initial_states Tensor with shape (samples, state_size) (no time dimension), containing the initial values for the states used in the step function. In the case that state_size is in a nested shape, the shape of initial_states will also follow the nested structure.
go_backwards Boolean. If True, do the iteration over the time dimension in reverse order and return the reversed sequence.
mask Binary tensor with shape (samples, time, 1), with a zero for every element that is masked.
constants List of constant values passed at each step.
unroll Whether t