Logging a metric with a trailing space causes get_metrics to throw "Exception: Malformed metric value"

This issue is provided for reference purposes.

Tested with azureml-sdk version 1.22.0 on the jupyter notebook instance and the current default SKLearn backend.

Example:

```
from azureml.core import Workspace, Experiment, Run
from azureml.train.sklearn import SKLearn
from azureml.train.hyperdrive.sampling import RandomParameterSampling
from azureml.train.hyperdrive.parameter_expressions import choice
from azureml.train.hyperdrive.runconfig import HyperDriveConfig
from azureml.train.hyperdrive.run import PrimaryMetricGoal
from azureml.core.compute import ComputeTarget, AmlCompute

print(azureml.core.VERSION)

ws = Workspace.from_config()
experiment_name = 'test'
experiment = Experiment(ws, experiment_name)

compute_config = AmlCompute.provisioning_configuration(vm_size='Standard_D2_V2',
max_nodes=1)
compute_target = ComputeTarget.create(ws, "test", compute_config)
compute_target.wait_for_completion(show_output=True)

estimator = SKLearn(source_directory=".",
entry_script="train.py",
compute_target=compute_target)

param_sampling = RandomParameterSampling({"--dummy": choice(1)})

run_config = HyperDriveConfig(estimator=estimator,
hyperparameter_sampling=param_sampling,
policy=None,
primary_metric_name="Accuracy",
primary_metric_goal=PrimaryMetricGoal.MAXIMIZE,
max_total_runs=1,
max_concurrent_runs=1)

run = experiment.submit(config=run_config, show_output=True)

run.wait_for_completion(show_output=True)

best_run = run.get_best_run_by_primary_metric()
print('best_run.id: ', best_run.id)

best_run_metrics = best_run.get_metrics()
print("best_run.get_metrics():", best_run_metrics)
```

with the following train.py

```
import argparse

from azureml.core import Run

run = Run.get_context()

def main():
parser = argparse.ArgumentParser()

parser.add_argument('--dummy', type=int, default=1, help="Nothing to do")

args = parser.parse_args()

run.log("Metric ending with a space: ", 0.1)
run.log("Accuracy", 1.0)

if __name__ == "__main__":
main()
```

The exception is thrown

```
---------------------------------------------------------------------------
Exception Traceback (most recent call last)
in
----> 1 best_run_metrics = best_run.get_metrics()
2 print("best_run.get_metrics():", best_run_metrics)

/anaconda/envs/azureml_py36/lib/python3.6/site-packages/azureml/core/run.py in get_metrics(self, name, recursive, run_type, populate)
1272 """
1273 return self._client.get_metrics(name=name, recursive=recursive, run_type=run_type,
-> 1274 populate=populate, root_run_id=self._root_run_id)
1275
1276 def _get_outputs_datapath(self):

/anaconda/envs/azureml_py36/lib/python3.6/site-packages/azureml/_run_impl/run_history_facade.py in get_metrics(self, name, recursive, run_type, populate, root_run_id, run_ids, use_batch)
363 return self.metrics.get_all_metrics_v2(name=name, run_ids=run_ids, populate=populate,
364 artifact_client=self.artifacts,
--> 365 data_container=self._data_container_id)
366
367 return self.metrics.get_all_metrics(run_ids=run_ids, populate=populate, artifact_client=self.artifacts,

/anaconda/envs/azureml_py36/lib/python3.6/site-packages/azureml/_restclient/metrics_client.py in get_all_metrics_v2(self, name, run_ids, populate, artifact_client, data_container, after_timestamp, custom_headers)
311 return self.get_metrics_for_run_ids_v2(name=name, run_ids=run_ids, start_time=after_timestamp,
312 populate=populate, artifact_client=artifact_client,
--> 313 data_container=data_container, custom_headers=custom_headers)
314
315 def get_all_metrics(self, run_ids=None, populate=False, artifact_client=None,

/anaconda/envs/azureml_py36/lib/python3.6/site-packages/azureml/_restclient/metrics_client.py in get_metrics_for_run_ids_v2(self, name, run_ids, start_time, end_time, populate, artifact_client, data_container, custom_headers)
298 end_time=end_time, populate=populate,
299 artifact_client=artifact_client, data_container=data_container,
--> 300 custom_headers=custom_headers)
301 if len(metrics) != 0:
302 returned_metrics_for_runs[run_id] = metrics

/anaconda/envs/azureml_py36/lib/python3.6/site-packages/azureml/_restclient/metrics_client.py in get_metrics_for_run_v2(self, run_id, name, start_time, end_time, populate, artifact_client, data_container, custom_headers)
284 metric = self.get_metric_for_run_v2(metric_name, run_id=run_id, start_time=start_time,
285 end_time=end_time, artifact_client=artifact_client,
--> 286 populate=populate, custom_headers=custom_headers)
287 if metric is not None:
288 returned_metrics[metric_name] = metric

/anaconda/envs/azureml_py36/lib/python3.6/site-packages/azureml/_restclient/metrics_client.py in get_metric_for_run_v2(self, name, run_id, start_time, end_time, artifact_client, populate, custom_headers)
263 if metric_dto is None or len(metric_dto.value) == 0:
264 return None
--> 265 return MetricsClient.dto_v2_to_metric_cells(metric_dto, artifact_client, populate)
266
267 def get_metrics_for_run_v2(self, run_id=None, name=None, start_time=None, end_time=None, populate=False,

/anaconda/envs/azureml_py36/lib/python3.6/site-packages/azureml/_restclient/metrics_client.py in dto_v2_to_metric_cells(cls, metric_dto, artifact_client, populate)
115 metric_type = metric_dto.properties.ux_metric_type
116 if metric_type in INLINE_METRICS:
--> 117 return InlineMetric.get_cells_from_metric_v2_dto(metric_dto)
118
119 if populate and artifact_client is None:

/anaconda/envs/azureml_py36/lib/python3.6/site-packages/azureml/core/_metrics.py in get_cells_from_metric_v2_dto(metric_dto)
415 values = []
416 for metric_value in metric_dto.value:
--> 417 cell = InlineMetric.get_cell_v2(columns, metric_value, metric_dto.name)
418 values.append(cell)
419 if len(values) == 1:

/anaconda/envs/azureml_py36/lib/python3.6/site-packages/azureml/core/_metrics.py in get_cell_v2(columns, metric_v2_value, column_name)
424 def get_cell_v2(columns, metric_v2_value, column_name):
425 if column_name not in columns.keys() or column_name not in metric_v2_value.data.keys():
--> 426 raise Exception("Malformed metric value")
427 cell_type = str.lower(columns[column_name])
428 value = metric_v2_value.data[column_name]

Exception: Malformed metric value
```

---
#### Document Details

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* ID: 9a70336d-fb4a-4c18-26d0-68784b5b3d72
* Version Independent ID: e28876d8-08a0-8546-4bd1-6e434c8c7826
* Content: [azureml.core.Run class - Azure Machine Learning Python](https://docs.microsoft.com/en-us/python/api/azureml-core/azureml.core.run(class)?view=azure-ml-py)
* Content Source: [AzureML-Docset/stable/docs-ref-autogen/azureml-core/azureml.core.Run(class).yml](https://github.com/MicrosoftDocs/MachineLearning-Python-pr/blob/live/AzureML-Docset/stable/docs-ref-autogen/azureml-core/azureml.core.Run(class).yml)
* Service: **machine-learning**
* Sub-service: **core**
* GitHub Login: @DebFro
* Microsoft Alias: **debfro**

Reproduza o exemplo no notebook com azureml-sdk 1.22.0 e, em seguida, inspecione azureml/core/_metrics.py e azureml/_restclient/metrics_client.py nos locais indicados pelo traceback. Está concluído quando get_metrics() lidar com a métrica que contém um espaço no final sem gerar "Malformed metric value", enquanto continua retornando as métricas registradas.

Escrita pelo modelo de indexação a partir do texto da issue.