Add tags on endpoints

[pm3310]

Issue #, if available:

Description of changes:

Option to add Tags on SageMaker Endpoints. I'd like this option so that to tag endpoints for auditing and linking IDs of trained models to endpoints. The latter is very important because I can know which models are dpeloyed in production.

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[codecov-io]

Codecov Report

Merging #253 into master will increase coverage by <.01%.
The diff coverage is 100%.

@@            Coverage Diff             @@
##           master     #253      +/-   ##
==========================================
+ Coverage   92.27%   92.27%   +<.01%     
==========================================
  Files          49       49              
  Lines        3261     3264       +3     
==========================================
+ Hits         3009     3012       +3     
  Misses        252      252

Impacted Files	Coverage Δ
src/sagemaker/model.py	95.52% <100%> (ø)	⬆️
src/sagemaker/session.py	86.82% <100%> (+0.11%)	⬆️

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[laurenyu]

Thanks for the contribution!

[laurenyu]

the integ tests are failing with this error:

        with timeout_and_delete_endpoint_by_name(endpoint_name, sagemaker_session):
            estimator = Estimator.attach(training_job_name=training_job_name, sagemaker_session=sagemaker_session)
            model = estimator.create_model()
>           predictor = model.deploy(1, 'ml.m4.xlarge', endpoint_name=endpoint_name)

tests/integ/test_byo_estimator.py:154: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
.tox/py27/lib/python2.7/site-packages/sagemaker/model.py:102: in deploy
    self.sagemaker_session.endpoint_from_production_variants(self.endpoint_name, [production_variant], tags)
.tox/py27/lib/python2.7/site-packages/sagemaker/session.py:665: in endpoint_from_production_variants
    EndpointConfigName=name, ProductionVariants=production_variants, Tags=tags)
.tox/py27/lib/python2.7/site-packages/botocore/client.py:314: in _api_call
    return self._make_api_call(operation_name, kwargs)
.tox/py27/lib/python2.7/site-packages/botocore/client.py:586: in _make_api_call
    api_params, operation_model, context=request_context)
.tox/py27/lib/python2.7/site-packages/botocore/client.py:621: in _convert_to_request_dict
    api_params, operation_model)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

self = <botocore.validate.ParamValidationDecorator object at 0x7fa197e2bb50>
parameters = {'EndpointConfigName': 'byo-2018-06-25-16-42-17-111', 'ProductionVariants': [{'InitialInstanceCount': 1, 'InitialVaria... 1, 'InstanceType': 'ml.m4.xlarge', 'ModelName': 'factorization-machines-2018-06-25-16-46-03-730', ...}], 'Tags': None}
operation_model = OperationModel(name=CreateEndpointConfig)

    def serialize_to_request(self, parameters, operation_model):
        input_shape = operation_model.input_shape
        if input_shape is not None:
            report = self._param_validator.validate(parameters,
                                                    operation_model.input_shape)
            if report.has_errors():
>               raise ParamValidationError(report=report.generate_report())
E               ParamValidationError: Parameter validation failed:
E               Invalid type for parameter Tags, value: None, type: <type 'NoneType'>, valid types: <type 'list'>, <type 'tuple'>

Can you modify your change to not pass along tags to the SageMaker call if it's None?

[pm3310]

Hey @laurenyu , I fixed it :-)

[laurenyu]

what do you think of doing it this way?

config_options = {'EndpointConfigName': name, 'ProductionVariants': production_variants}

if tags:
    config_options['Tags'] = tags

self.sagemaker_client.create_endpoint_config(**config_options)

[pm3310]

@laurenyu great idea. Done!