Define a custom target storage format.
Define a custom target storage format for the
format argument of tar_target() or tar_option_set().
tar_format(
read = function(path) { readRDS(path) },
write = function(object, path) { saveRDS(object = object, file = path, version =
3L) },
marshal = function(object) { identity(object) },
unmarshal = function(object) { identity(object) },
repository = c("default", "aws")
)read |
A function with a single argument named |
write |
A function with two arguments: |
marshal |
A function with a single argument named |
unmarshal |
A function with a single argument named |
repository |
Character of length 1, |
A character string of length 1 encoding the custom format.
You can supply this string directly to the format
argument of tar_target() or tar_option_set().
If an object can only be used in the R session
where it was created, it is called "non-exportable".
Examples of non-exportable R objects are Keras models,
Torch objects, xgboost matrices, xml2 documents,
rstan model objects, sparklyr data objects, and
database connection objects. These objects cannot be
exported to parallel workers (e.g. for tar_make_future())
without special treatment. To send an non-exportable
object to a parallel worker, the object must be marshalled:
converted into a form that can be exported safely
(similar to serialization but not always the same).
Then, the worker must unmarshal the object: convert it
into a form that is usable and valid in the current R session.
Arguments marshal and unmarshal of tar_format()
let you control how marshalling and unmarshalling happens.
In tar_format(), functions like read, write,
marshal, and unmarshal must be perfectly pure
and perfectly self-sufficient.
They must load or namespace all their own packages,
and they must not depend on any custom user-defined
functions or objects in the global environment of your pipeline.
targets converts each function to and from text,
so it must not rely on any data in the closure.
This disqualifies functions produced by Vectorize(),
for example.
Other targets:
tar_cue(),
tar_target_raw(),
tar_target()
# The following target is equivalent to
# tar_target(name, command(), format = "keras"):
tar_target(
name,
command(),
format = tar_format(
read = function(path) {
keras::load_model_hdf5(path)
},
write = function(object, path) {
keras::save_model_hdf5(object = object, filepath = path)
},
marshal = function(object) {
keras::serialize_model(object)
},
unmarshal = function(object) {
keras::unserialize_model(object)
},
repository = "default" # Could be "aws" (same as format = "aws_keras")
)
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