Sets all random seeds (Python, NumPy, and backend framework, e.g. TF).
meridian
.
backend
.
set_random_seed
(
seed
)
You can use this utility to make almost any Keras program fully deterministic. Some limitations apply in cases where network communications are involved (e.g. parameter server distribution), which creates additional sources of randomness, or when certain non-deterministic cuDNN ops are involved.
Calling this utility is equivalent to the following:
import
random
random
.
seed
(
seed
)
import
numpy
as
np
np
.
random
.
seed
(
seed
)
import
tensorflow
as
tf
# Only if TF is installed
tf
.
random
.
set_seed
(
seed
)
import
torch
# Only if the backend is 'torch'
torch
.
manual_seed
(
seed
)
Note that the TensorFlow seed is set even if you're not using TensorFlow
as your backend framework, since many workflows leverage tf.data
pipelines (which feature random shuffling). Likewise many workflows
might leverage NumPy APIs.
