Reshapes tensors in sample to have shape [rows, num_steps, ...].

This function takes a structure sample and for each tensor t, it truncates the tensor's outer dimension to be the highest possible multiple of num_steps.

This is done by first calculating rows = tf.shape(t[0]) // num_steps, then truncating the tensor to shape t_trunc = t[: (rows * num_steps), ...]. For each tensor, it returns tf.reshape(t_trunc, [rows, num_steps, ...]).

sample Nest of tensors.
num_steps Python integer.

A next with tensors reshaped to [rows, num_steps, ...].