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TFX is an end-to-end platform for deploying production ML pipelines

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https://github.com/tensorflow/tfx/tree/master/tfx/components/trainer/rewriting Any plan to move it out as a dedicated component? Similar like Pusher.

type:feature
stat:awaiting response

I am using TFX on Kubeflow. I have written a custom component that does some work. I want that library (defining the custom_component) to be available on the Dataflow runner....

type:feature
stat:awaiting response

Add 'tfma_eval' model_type in model_specs to replace the hard-coded estimator model with signature='eval' pattern.

I'm requesting constructs to facilitate the **composition of sub-pipelines**. This would enable platform owners using TFX to provide predefined sub-pipeline "recipes" that users can then piece together—passing relevant artifact references...

type:feature
stat:awaiting tensorflower

Got the following error while running the codes in Colab and reaching this section (second to last section) **Make REST requests Newest version of the servable** **Cell**: `# docs_infra: no_execute...

type:support

User migration to native sequence example support for Transform.

Run the tfx taxi pipeline, in the trainer component when I submit job to the AI platform, this job failed with the error "ValueError: Expect custom_config to be a dict...

type:support
stat:awaiting response
stat:awaiting tensorflower

This is a real ease-of-use killer, especially for new users (and those of us who don't install new versions often). Consider this page: `https://www.tensorflow.org/tfx/tutorials/tfx/components#export_to_pipeline` It makes no reference that you...

type:docs
stat:awaiting response