Sagemaker PipelineModel Doesn't Support tags when create model

[wangajing]

Describe the bug
When create sagemaker PipelineModel and deploy it(https://github.com/aws/sagemaker-python-sdk/blob/master/src/sagemaker/pipeline.py#L175-L181), sagemaker PipelineModel doesn't allow passing tags when call create_model.

To reproduce

See the source code here https://github.com/aws/sagemaker-python-sdk/blob/master/src/sagemaker/pipeline.py#L175-L181
And tags are not passed when call session.create_model()

Expected behavior
when create sageamaker PipelineModel object, tags should be allowed to be passed, and then propagate it to necessary resources.

Screenshots or logs
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System information
A description of your system. Please provide:

• SageMaker Python SDK version:
• Framework name (eg. PyTorch) or algorithm (eg. KMeans):
• Framework version:
• Python version:
• CPU or GPU:
• Custom Docker image (Y/N):

Additional context
Add any other context about the problem here.

[inverts]

This is still an issue, here is a permalink to the code where we would likely need tags to be passed through (original description link is out of date)

sagemaker-python-sdk/src/sagemaker/pipeline.py

Lines 282 to 313 in 19115a2

	def create(self, instance_type: str):
	"""Create a SageMaker Model Entity
	Args:
	instance_type (str): The EC2 instance type that this Model will be
	used for, this is only used to determine if the image needs GPU
	support or not.
	"""
	self._create_sagemaker_pipeline_model(instance_type)
	def _create_sagemaker_pipeline_model(self, instance_type):
	"""Create a SageMaker Model Entity
	Args:
	instance_type (str): The EC2 instance type that this Model will be
	used for, this is only used to determine if the image needs GPU
	support or not.
	"""
	if not self.sagemaker_session:
	self.sagemaker_session = Session()
	containers = self.pipeline_container_def(instance_type)
	self.name = self.name or name_from_image(containers[0]["Image"])
	create_model_args = dict(
	name=self.name,
	role=self.role,
	container_defs=containers,
	vpc_config=self.vpc_config,
	enable_network_isolation=self.enable_network_isolation,
	)
	self.sagemaker_session.create_model(**create_model_args)

Perhaps something as simple as accepting **kwargs on PipelineModel's create function, and just passing them along through _create_sagemaker_pipeline_model and on to the create_model call would be adequate without adding much complexity.

Similar issues:
#3447
#3733

For now, we can workaround by basically just copying what the source code does and adding in tags. It would just be nice to be able to use the convenient create method.
eg.

pipeline_model = PipelineModel(**model_args, models=models, sagemaker_session=sagemaker_session)
containers = pipeline_model.pipeline_container_def(instance_type)
sagemaker_session.create_model(**model_args, container_defs=containers, tags=my_tags)

Note that the above doesn't do some default value resolution that would otherwise happen for the model_args params.

[qidewenwhen]

FYI PipelineModel is not owned or managed by SageMaker Pipeline service, though the name is confusing. Thus removing the component: pipelines tag and leave it in the more proper queue of component: hosting