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Reshapes tensors in sample to have shape [rows, num_steps, ...].
tf_agents.replay_buffers.reverb_replay_buffer.truncate_reshape_rows_by_num_steps(
sample, 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, ...]).
Args | |
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sample
|
Nest of tensors. |
num_steps
|
Python integer. |
Returns | |
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A next with tensors reshaped to [rows, num_steps, ...].
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