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()andas.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_callsand- deterministic.
- dataset_padded_batch(): Fixed error raised when- drop_remainder=TRUEwith 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 ofdataset_map().
- New dataset_snapshot()for persisting the output of a
dataset to disk.
- range_dataset()gains a- dtypeargument.
- dataset_prefetch()argument- buffer_sizeis
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_windowmethod.
- Allow purrrstyle lambda functions indataset_map.
- Added a NEWS.mdfile to track changes to the
package.
- Added a new feature spec interface that can be used to easily create
feature_columns. (#42)