[GSoC] Add unit tests for tune API

[helenxie-bit]

What this PR does / why we need it:
This PR adds unit tests and fix some minor bugs of tune API.

Which issue(s) this PR fixes (optional, in fixes #<issue number>(, fixes #<issue_number>, ...) format, will close the issue(s) when PR gets merged):
Fixes #

Checklist:

• Docs included if any changes are user facing

[helenxie-bit]

/area gsoc

[helenxie-bit]

Ref: #2339

[andreyvelich]

Thank you for doing this @helenxie-bit!

[helenxie-bit]

@andreyvelich The unit test for tune API is ready. I have also fixed some errors in this PR. Please have a look when you have time. Thanks!

[andreyvelich]

Thank you for doing this @helenxie-bit!
/assign @tenzen-y @johnugeorge @deepanker13 @droctothorpe @Electronic-Waste

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[helenxie-bit]

@andreyvelich Thank you so much for reviewing this! I’ve replied to all your feedback, and please take a look when you have time.

[Electronic-Waste]

Thanks for your great contribution @helenxie-bit ! I left some suggestions about the name of UTs for your reference

I guess it will be more friendly for other developers to understand these UTs if we could specify the scope of each UTs:)

[helenxie-bit]

Thanks for your great contribution @helenxie-bit ! I left some suggestions about the name of UTs for your reference

I guess it will be more friendly for other developers to understand these UTs if we could specify the scope of each UTs:)

@Electronic-Waste Thank you so much for your suggestions! I have incorporated your advice into the UTs.

[helenxie-bit]

@andreyvelich I’ve added the kubeflow-training dependency to the unit tests, allowing values and parameters to be fetched from there instead of redefining them within the Katib unit tests. You can find the change here:

katib/test/unit/v1beta1/requirements.txt

Line 3 in b24b44f

kubeflow-training[huggingface]==1.8.1

Additionally, I have added verification for the experiment object in two valid flow cases in the following section:

katib/sdk/python/v1beta1/kubeflow/katib/api/katib_client_test.py

Lines 587 to 639 in b24b44f

	call_args = mock_create_experiment.call_args
	experiment = call_args[0][0]
	if test_name == "valid flow with custom objective tuning":
	# Verify input_params
	args_content = "".join(
	experiment.spec.trial_template.trial_spec.spec.template.spec.containers[
	0
	].args
	)
	assert "'a': '${trialParameters.a}'" in args_content
	# Verify trial_params
	assert experiment.spec.trial_template.trial_parameters == [
	V1beta1TrialParameterSpec(name="a", reference="a"),
	]
	# Verify experiment_params
	assert experiment.spec.parameters == [
	V1beta1ParameterSpec(
	name="a",
	parameter_type="int",
	feasible_space=V1beta1FeasibleSpace(min="10", max="100"),
	),
	]
	elif test_name == "valid flow with external model tuning":
	# Verify input_params
	args_content = "".join(
	experiment.spec.trial_template.trial_spec.spec.pytorch_replica_specs[
	"Master"
	]
	.template.spec.containers[0]
	.args
	)
	assert (
	'"learning_rate": "${trialParameters.learning_rate}"'
	in args_content
	)
	# Verify trial_params
	assert experiment.spec.trial_template.trial_parameters == [
	V1beta1TrialParameterSpec(
	name="learning_rate", reference="learning_rate"
	),
	]
	# Verify experiment_params
	assert experiment.spec.parameters == [
	V1beta1ParameterSpec(
	name="learning_rate",
	parameter_type="double",
	feasible_space=V1beta1FeasibleSpace(
	min="1e-05", max="5e-05"
	),
	),
	]

Please review when you have time. Thanks!