Error when running hyperparameter tuning job locally

**Describe the bug**
Running a hyperparameter tuning job locally using a sample code as given below produces an error: `AttributeError: 'LocalSagemakerClient' object has no attribute 'create_hyper_parameter_tuning_job'`.

```
tuner = HyperparameterTuner(estimator,
objective_metric_name,
hyperparameter_ranges,
metric_definitions,
max_jobs=4,
max_parallel_jobs=2,
objective_type=objective_type,
base_tuning_job_name="hpo-tuning-demo"
)

tuner.fit(inputs=channels)
```

**To reproduce**
Use the Amazon AWS example from the link: https://github.com/aws/amazon-sagemaker-examples/tree/master/hyperparameter_tuning/keras_bring_your_own, and change instance_type to 'local'. For Hyperparameter tuning job, instead of using configurations as in the example, just use HyperparmeterTuner class as shown above.

**Expected behavior**
I'd expect it to work without the error.

**Screenshots or logs**
Screenshot of the error output given below.

**System information**
A description of your system. Please provide:
- **SageMaker Python SDK version**: 2.15
- **Framework name (eg. PyTorch) or algorithm (eg. KMeans)**: TensorFlow
- **Framework version**: 2.3.1
- **Python version**: 3.8
- **CPU or GPU**: CPU
- **Custom Docker image (Y/N)**: Y (Dockerfile from the AWS example code)

**Additional context**
Instead of using the AWS instances, trying to use the SageMaker hyperparameter tuning job locally for testing purposes.