TFX 1.4.0-rc0
Pre-release
Pre-release
Major Features and Improvements
- Supported endpoint overwrite for CAIP BulkInferrer.
- Added support for outputting and encoding
tf.RaggedTensor
s in TFX
Transform component. - Added conditional for TFX running on KFPv2 (Vertex).
- Supported component level beam pipeline args for Vertex (KFPV2DagRunner).
- Support exit handler for TFX running on KFPv2 (Vertex).
- Added RangeConfig for QueryBasedExampleGen to select date using query
pattern. - Added support for union of Channels as input to standard TFX components.
Users can use channel.union() to combine multiple Channels and use as input
to these compnents. Artfacts resolved from these channels are expected to
have the same type, and passed to components in no particular order.
Breaking Changes
- Calling
TfxRunner.run(pipeline)
with the Pipeline IR proto will no longer
be supported. Please switch toTfxRunner.run_with_ir(pipeline)
instead.
If you are callingTfxRunner.run(pipeline)
with the Pipeline object, this
change should not affect you.
For Pipeline Authors
- N/A
For Component Authors
- N/A
Deprecations
- Deprecated python3.6 support.
Bug Fixes and Other Changes
- Depends on
google-cloud-aiplatform>=1.5.0,<2
. - Depends on
tensorflow>=1.15.2,!=2.0.*,!=2.1.*,!=2.2.*,!=2.3.*,!=2.4.*,!=2.5.*,<2.7
. - Depends on
pyarrow>=1,<6
. - Fixed FileBasedExampleGen driver for Kubeflow v2 (Vertex). Driver can
update exec_properties for its executor now, which enables {SPAN} feature. - example_gen.utils.dict_to_example now accepts Numpy types
- Updated pytest to include v6.x
- Depends on
apache-beam[gcp]>=2.33,<3
. - Depends on
ml-metadata>=1.4.0,<1.5.0
. - Depends on
struct2tensor>=0.35.0,<0.36.0
. - Depends on
tensorflow-data-validation>=1.4.0,<1.5.0
. - Depends on
tensorflow-model-analysis>=0.35.0,<0.36.0
. - Depends on
tensorflow-transform>=1.4.0,<1.5.0
. - Depends on
tfx-bsl>=1.4.0,<1.5.0
.
Documentation Updates
- N/A