tfdatasets 2.7.0
- Added compatability with Tensorflow version 2.7
as_iterator()
, iter_next()
and iterate()
are is now reexported from {reticualte}.
- New
as_array_iterator()
, for converting a dataset into an iterable that yields R arrays. (as_iterator()
yields tensorflow tensors)
- New
dataset_bucket_by_sequence_length()
- New
dataset_rejection_resample()
- New
dataset_unique()
- New
choose_from_datasets()
sample_from_datasets()
gains argument stop_on_empty_dataset
.
dataset_batch()
gains arguments num_parallel_calls
and deterministic
.
dataset_padded_batch()
: Fixed error raised when drop_remainder=TRUE
with recent TF versions. Added examples, docs, and tests.
dataset_concatenate()
gains ...
and the ability to combine multiple datasets in one call.
tfdatasets 2.6.0
- New
dataset_options()
for setting and getting dataset options.
- New
length()
method for tensorflow datasets.
- New
dataset_enumerate()
.
- New
random_integer_dataset()
.
- New
dataset_scan()
, a stateful variant of dataset_map()
.
- New
dataset_snapshot()
for persisting the output of a dataset to disk.
range_dataset()
gains a dtype
argument.
dataset_prefetch()
argument buffer_size
is now optional, defaults to tf$data$AUTOTUNE
tfdatasets 2.4.0
- Fixed problem when saving models with feature specs (#82).
tfdatasets 1.13.1
- Add
datatset_window
method.
- Allow
purrr
style lambda functions in dataset_map
.
- Added a
NEWS.md
file to track changes to the package.
- Added a new feature spec interface that can be used to easily create
feature_column
s. (#42)