library(tensorflow)
use_session_with_seed(42)
use_session_with_seed
Use a session with a random seed
Description
Set various random seeds required to ensure reproducible results. The provided seed
value will establish a new random seed for R, Python, NumPy, and TensorFlow. GPU computations and CPU parallelism will also be disabled by default.
Usage
use_session_with_seed(
seed, disable_gpu = TRUE,
disable_parallel_cpu = TRUE,
quiet = FALSE
)
Arguments
Arguments | Description |
---|---|
seed | A single value, interpreted as an integer |
disable_gpu | TRUE to disable GPU execution (see Parallelism below). |
disable_parallel_cpu | TRUE to disable CPU parallelism (see Parallelism below). |
quiet | TRUE to suppress printing of messages. |
Details
This function must be called at the very top of your script (i.e. immediately after library(tensorflow)
, library(keras)
, etc.). Any existing TensorFlow session is torn down via tf$reset_default_graph()
. This function takes all measures known to promote reproducible results from TensorFlow sessions, however it’s possible that various individual TensorFlow features or dependent libraries escape its effects. If you encounter non-reproducible results please investigate the possible sources of the problem, contributions via pull request are very welcome! Packages which need to be notified before and after the seed is set can register for the “tensorflow.on_before_use_session” and “tensorflow.on_use_session” hooks (see setHook()
) for additional details on hooks).
Section
Parallelism
By default the use_session_with_seed()
function disables GPU and CPU parallelism, since both can result in non-deterministic execution patterns (see https://stackoverflow.com/questions/42022950/). You can optionally enable GPU or CPU parallelism by setting the disable_gpu
and/or disable_parallel_cpu
parameters to FALSE
.
Value
TensorFlow session object, invisibly