Comments (6)
context: https://twitter.com/wjarek/status/1103719781830545408
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why you do not support tfx in python 3 version, for pip install , it only accept python 2.7
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from tfx.
you should upgrade your example to 3.6 , 2.7 is no longer used in 2020,January @googlebot
from tfx.
Hi @DanlanChen - the code in the repo and dependent libraries do support Python 3 already, but we're doing more testing before releasing the Py3 package on PyPI. Thank you for your patience!
PS> Is this a Marie Skłodowska photo? :)
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b5e2383 addressed it, supported environment is now shown in the TFX User Guide: https://www.tensorflow.org/tfx/guide
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Related Issues (20)
- [Request] Update to Apache Beam 2.52.0, enable Beam 2.46.0 compatibility HOT 5
- How to pass airflow task configuration to one custom component? HOT 3
- Error executing pip install tfx in new conda environment with python 3.10 HOT 6
- installing tfx 1.13.0 by pip takes so much time HOT 5
- TFX trainer component running in Kubeflow fails although it was successful in the Interactive Context HOT 8
- TFX components in GCP does not display component logs in GCP Vertex AI HOT 17
- DataFlow Job in TFX pipeline fails after running for an hour HOT 6
- TFX component never completes even though Vertex AI custom job succeeds / fails HOT 8
- Upgrade Tensorflow version HOT 3
- documentations for driver class HOT 2
- Custom driver support for KubeflowV2DagRunner HOT 3
- Error when starting Evaluator component HOT 6
- TFX 1.15.0 Issues HOT 1
- R2Score Metric is incompatible with Evaluator Component HOT 2
- Version issues with Savemodel
- Version Issues with Estimator SaveModel
- Python-snappy not found during execution of CSVExampleGen HOT 1
- Dependency Version Constraints error in release notes for version 1.15.0 HOT 1
- TFX for small, single-laptop workflows HOT 4
- TFX 1.15 docker image contains conflicting dependencies HOT 2
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