tf_sagemaker_init_hyperparamsearch.py

# Define objective
objective_metric_name = 'loss'
objective_type = 'Minimize'
metric_definitions = [{'Name': 'loss',
                       'Regex': 'loss = ([0-9\\.]+)'}]
# Define hyperparameter ranges
hyperparameter_ranges = {
                            'learning_rate': ContinuousParameter(0.0001, 0.01), 
                            'dropout_rate': ContinuousParameter(0.3, 1.0),
                            'nw_depth': IntegerParameter(1, 4),
                            'optimizer_type': CategoricalParameter(['sgd', 'adam']),
                        }  
# Initialise Sagemaker's hyperparametertuner
tuner = HyperparameterTuner(estimator,
                            objective_metric_name,
                            hyperparameter_ranges,
                            metric_definitions,
                            max_jobs=16,
                            max_parallel_jobs=4,
                            objective_type=objective_type)