specify tf.while_loop options — ag_while

See https://www.tensorflow.org/versions/r2.0/api_docs/python/tf/while_loop for additional details.

ag_while_opts(
  ...,
  shape_invariants = NULL,
  parallel_iterations = 10L,
  back_prop = TRUE,
  swap_memory = FALSE,
  maximum_iterations = NULL
)

Arguments

...	Ignored, used to ensure all arguments supplied are named.
shape_invariants	The shape invariants for the loop variables.
parallel_iterations	The number of iterations allowed to run in parallel. It must be a positive integer.
back_prop	Deprecated (optional). `FALSE` disables support for back propagation. Prefer using `tf$stop_gradient` instead.
swap_memory	Whether GPU-CPU memory swap is enabled for this loop.
maximum_iterations	Optional maximum number of iterations of the while loop to run. If provided, the `cond` output is AND-ed with an additional condition ensuring the number of iterations executed is no greater than `maximum_iterations`.

Value

`NULL`` invisibly, called for it's side effect.

Note

Use ag_name() to supply name and ag_loop_vars() to supply loop_vars directly.

This is only applicable when autograph in graph mode, otherwise this has no effect.

Examples

if (FALSE) {
## use tf_function() to enter graph mode:
tf_function(autograph(function(n) {
  ag_name("silly-example")
  ag_while_opts(back_prop = FALSE)
  while(n > 0)
    n <- n - 1
}))
}