tfdatasets 2.18.0
- New
dataset_rebatch().
dataset_batch() gains args
num_parallel_calls, name.
dataset_interleave() gains args
deterministic, num_parallel_calls,
name.
text_line_dataset() gains args
num_parallel_calls, buffer_size,
name.
- Updated documentation to fix cross links (#96).
tfdatasets 2.17.0
- Updates for TensorFlow v2.17.0, Keras 3.
tfdatasets 2.9.0
- New
dataset_unbatch()
- New
dataset_group_by_window()
- New
dataset_take_while()
- New
as_tensor() and as.array() methods
which can be used on TF Datasets with a single element.
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_columns. (#42)