Create tuning job not working with deepar

I am trying to lunch a grid search using HyperparameterTuner but it seems that the job does not start.
This is the relevant part of my code:

`from sagemaker.amazon.amazon_estimator import get_image_uri
image_name = get_image_uri(boto3.Session().region_name, 'forecasting-deepar')

estimator = sagemaker.estimator.Estimator(
sagemaker_session=sagemaker_session,
image_name=image_name,
role=role,
train_instance_count=1,
train_instance_type='ml.c4.xlarge',
base_job_name='DEMO-deepar',
output_path="s3://" + s3_output_path
)_

param_grid = {
'context_length_param' : ["60"],
'num_cells_param' : ["50"],
'epocs_param' : ["50"],
'learning_rate_param' : ["0.01"],
'embedding_dimension_param' : ["5"]}

hyperparameter_ranges = {
'num_layers': IntegerParameter(2, 3, scaling_type="Auto")
}

objective_metric_name = 'test:RMSE'
tuner_random = HyperparameterTuner(
estimator,
objective_metric_name,
hyperparameter_ranges,
max_jobs=2,
max_parallel_jobs=2,
strategy='Random',
objective_type = 'Minimize'
)

tuner_random.fit(inputs=data_channels)
tuner_random
`

and the output i am getting is

does not seem that any training is taking place

Any idea what am I missing?

The reproduction is the Python snippet using HyperparameterTuner and tuner_random.fit(inputs=data_channels); no repository file or test is named. Start by running the example and checking the SageMaker tuning-job status and logs, then determine the missing configuration or error and document the verified fix.

Written by the indexing model from the issue text.