Can't launch local training job without hyperparameters

[leopd]

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System Information

• Framework (e.g. TensorFlow) / Algorithm (e.g. KMeans): Any
• Framework Version: n/a
• Python Version: 3.6
• CPU or GPU: CPU
• Python SDK Version: 1.10.1
• Are you using a custom image: n/a

Describe the problem

If I try to call estimator.fit without hyperparameters, I get an error. I shouldn't need to specify any hyperparameters.

Minimal repro / logs

From a notebook call

import sagemaker
role = sagemaker.get_execution_role()
instance_type = 'local'

estimator = sagemaker.estimator.Estimator(role=role,
                      train_instance_count=1,
                      train_instance_type=instance_type,
                      image_name='simpleexample/cpu',
                      hyperparameters={},
                    )
estimator.fit({})

And I get

INFO:sagemaker:Creating training-job with name: cpu-2018-09-26-01-22-42-326
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-13-98552d1fe99a> in <module>()
      7                     )
      8 
----> 9 estimator.fit({})

~/miniconda3/envs/conda_python3/lib/python3.6/site-packages/sagemaker/estimator.py in fit(self, inputs, wait, logs, job_name)
    176         self._prepare_for_training(job_name=job_name)
    177 
--> 178         self.latest_training_job = _TrainingJob.start_new(self, inputs)
    179         if wait:
    180             self.latest_training_job.wait(logs=logs)

~/miniconda3/envs/conda_python3/lib/python3.6/site-packages/sagemaker/estimator.py in start_new(cls, estimator, inputs)
    361                                           job_name=estimator._current_job_name, output_config=config['output_config'],
    362                                           resource_config=config['resource_config'], hyperparameters=hyperparameters,
--> 363                                           stop_condition=config['stop_condition'], tags=estimator.tags)
    364 
    365         return cls(estimator.sagemaker_session, estimator._current_job_name)

~/miniconda3/envs/conda_python3/lib/python3.6/site-packages/sagemaker/session.py in train(self, image, input_mode, input_config, role, job_name, output_config, resource_config, hyperparameters, stop_condition, tags)
    262         LOGGER.info('Creating training-job with name: {}'.format(job_name))
    263         LOGGER.debug('train request: {}'.format(json.dumps(train_request, indent=4)))
--> 264         self.sagemaker_client.create_training_job(**train_request)
    265 
    266     def tune(self, job_name, strategy, objective_type, objective_metric_name,

TypeError: create_training_job() missing 1 required positional argument: 'HyperParameters'

[iquintero]

Fixed in #375

[ChoiByungWook]

Seems that the fix has been merged in.