ERROR al implementa usando el método `` deployments.create () #3
Description
como puedo superar este mensaje de error
Instance creation of size small and type scikit-learn0.20 failed.
WMLClientError Traceback (most recent call last)
in
8 deployment_type='online', # No cambie este parámetro
9 deployment_format='Core ML', # No cambie este parámetro
---> 10 meta_props=model_meta # No cambie este parámetro
11 )
/opt/conda/envs/Python36/lib/python3.6/site-packages/watson_machine_learning_client/deployments.py in create(self, artifact_uid, name, description, asynchronous, deployment_type, deployment_format, meta_props, **kwargs)
520 else:
521 print_text_header_h2(u'Deployment creation failed')
--> 522 self._deployment_status_errors_handling(deployment_details, 'creation')
523 elif response.status_code == 201:
524 deployment_details = response.json()
/opt/conda/envs/Python36/lib/python3.6/site-packages/watson_machine_learning_client/deployments.py in _deployment_status_errors_handling(self, deployment_details, operation_name)
52 raise WMLClientError('Deployment ' + operation_name + ' failed. Error: ' + str(deployment_details['entity']['status_message']))
53 except WMLClientError as e:
---> 54 raise e
55 except Exception as e:
56 self._logger.debug('Deployment ' + operation_name + ' failed: ' + str(e))
/opt/conda/envs/Python36/lib/python3.6/site-packages/watson_machine_learning_client/deployments.py in _deployment_status_errors_handling(self, deployment_details, operation_name)
47 else:
48 print(error)
---> 49 raise WMLClientError('Deployment ' + operation_name + ' failed. Errors: ' + str(errors))
50 else:
51 print(deployment_details['entity']['status_message'])
WMLClientError: Deployment creation failed. Errors: [{'code': 'error_in_instance_creation', 'message': 'Instance creation of size small and type scikit-learn0.20 failed.'}]
algún consejo? llevo un buen rato y se me acabaron la ideas.