Thin wrapper around tf.map_fn()
with the following
differences:
accepts purrr
style ~
lambda syntax to define function fn
.
The order of elems
and fn
is switched to make it more pipe %>%
friendly and consistent with R mappers lapply()
and purrr::map()
.
tf_map( elems, fn, dtype = NULL, parallel_iterations = NULL, back_prop = TRUE, swap_memory = FALSE, infer_shape = TRUE, name = NULL )
elems | A tensor or (possibly nested) sequence of tensors, each of which
will be unpacked along their first dimension. The nested sequence of the
resulting slices will be applied to |
---|---|
fn | An R function, specified using |
dtype | (optional) The output type(s) of fn. If fn returns a structure of Tensors differing from the structure of elems, then dtype is not optional and must have the same structure as the output of fn. |
parallel_iterations | (optional) The number of iterations allowed to run in parallel. When graph building, the default value is 10. While executing eagerly, the default value is set to 1. |
back_prop | (optional) True enables support for back propagation. |
swap_memory | (optional) True enables GPU-CPU memory swapping. |
infer_shape | (optional) False disables tests for consistent output shapes. |
name | (optional) Name prefix for the returned tensors. |
A tensor or (possibly nested) sequence of tensors. Each tensor packs the results of applying fn to tensors unpacked from elems along the first dimension, from first to last.