* SDK - Client - Added a way to set experiment name using environment variables
This is useful for launching notebooks or pipeline files that submit
themselves for execution.
* Switched to subprocess.run which supports env
* Setting the environment variable differently
Looks like `subprocess.run` uses `PATH` to search for the program.
* Convert return code to string
* Changed the way the experiment name is being set
* Changed how the notebook installs the SDK
Notebook is overriding the SDK that's being tested.
* Not installing the KFP SDK package
* Removed the experiment_name from samples and configs.
* Changed the SDK installation lines in samples
Otherwise the sample tests do not correctly test the new SDK code.
Reduced boilerplate code in samples by switching to `kfp.Client().create_run_from_pipeline_package` which:
* compiles the pipeline
* gets or creates the experiment (name is optional)
* generates unique run name
* submits the run
* Add logic to detect extension name.
* Rename notebook samples
* Change to use config yaml for papermill preprocess.
* Remove ad hoc logic
* Remove duplicated logic
* Refactor
* Add run_pipeline flag in config yaml
* Add run pipeline flag for .py sample as well.
* Fix extension name
* Fix
* Fix problems in docstring.
* refactor run_sample_test.py into two functions
* Refactor the procedure into 3 steps
* Fix bug in exit code format
* Remove two redundant functions.
* Explicitly added mlpipeline outputs to the components that actually produce them
* Updated samples
* SDK - DSL - Stopped adding mlpipeline artifacts to every compiled template
Fixes https://github.com/kubeflow/pipelines/issues/1421
Fixes https://github.com/kubeflow/pipelines/issues/1422
* Updated the Lighweight sample
* Updated the compiler tests
* Fixed the lightweight sample
* Reverted the change to one contrib/samples/openvino
The sample will still work fine as it is now.
I'll add the change to that file as a separate PR.
* Remove redundant import.
* Simplify sample_test.yaml by using withItem syntax.
* Simplify sample_test.yaml by using withItem syntax.
* Change dict to str in withItems.
* Move tensorflow installation into notebooks.