def create(cluster: Cluster, name: str, modelversion_id: int,
config: MetricSpecConfig) -> 'MetricSpec':
"""
Create MetricSpec and returns corresponding instance.
:param cluster: active cluster
:param name: name of the metric
:param modelversion_id: ModelVersion for which to create a MetricSpec
:param config: MetricSpecConfig, describing MetricSpec
:return: metricSpec
"""
metric_spec_json = {
'name': name,
'modelVersionId': modelversion_id,
'config': {
'modelVersionId': config.modelversion_id,
'threshold': config.threshold,
'thresholdCmpOperator': {
'kind': config.threshold_op
}
}
}
resp = cluster.request("POST",
MetricSpec._BASE_URL,
json=metric_spec_json)
handle_request_error(
resp,
f"Failed to create a MetricSpec for name={name}, modelversion_id={modelversion_id}. {resp.status_code} {resp.text}"
)
return MetricSpec._from_json(cluster, resp.json())
def build(self, cluster: Cluster) -> Application:
"""
Create an Application in your Hydrosphere cluster.
:return: Application object
"""
if not self.stages:
raise ValueError("No execution stages were provided")
execution_graph = ExecutionGraph(stages=self.stages)
application_json = {
"name": self.name,
"kafkaStreaming":
[sp.to_dict() for sp in self.streaming_parameters],
"executionGraph": execution_graph.to_dict(),
"metadata": self.metadata
}
resp = cluster.request("POST",
Application._BASE_URL,
json=application_json)
handle_request_error(
resp,
f"Failed to create an application {self.name}. {resp.status_code} {resp.text}"
)
return Application._from_json(cluster, resp.json())
def create(
cluster: Cluster,
model_name: str,
version: int,
metadata: Optional[Dict[str, str]] = None,
deployment_configuration: Optional[DeploymentConfiguration] = None
) -> 'Servable':
"""
Deploy an instance of uploaded model version at your cluster.
:param deployment_configuration: k8s configurations used to run this servable
:param cluster: Cluster connected to Hydrosphere
:param model_name: Name of uploaded model
:param version: Version of uploaded model
:param metadata: Information which you can attach to your servable in a form of Dict[str, str]
:raises ServableException:
:return: servable
"""
msg = {
"modelName": model_name,
"version": version,
}
if metadata:
msg['metadata'] = metadata
if deployment_configuration:
msg['deploymentConfigName'] = deployment_configuration.name
resp = cluster.request('POST', Servable._BASE_URL, json=msg)
handle_request_error(
resp,
f"Failed to create a servable. {resp.status_code} {resp.text}")
return Servable._from_json(cluster, resp.json())
def test_training_data_upload(cluster: Cluster,
model_version_builder: ModelVersionBuilder,
training_data: str):
mv: ModelVersion = model_version_builder.build(cluster)
mv.training_data = training_data
data_upload_response = mv.upload_training_data()
data_upload_response.wait(sleep=5)
resp = cluster.request("GET", f"/monitoring/profiles/batch/{mv.id}/status")
assert "Success" == resp.json()["kind"]
def list(cluster: Cluster) -> List['DeploymentConfiguration']:
"""
List all deployment configurations
:param cluster:
:return:
"""
resp = cluster.request("GET", DeploymentConfiguration._BASE_URL)
handle_request_error(resp, f"Failed to get a list of Deployment Configurations - {resp.status_code} {resp.text}")
return [DeploymentConfiguration.parse_obj(app_json) for app_json in resp.json()]
def _upload_s3_file(cluster: Cluster, modelversion_id: int, path: str) -> requests.Response:
"""
Internal method for submitting training data from S3 to Hydrosphere.
:param cluster: Cluster instance
:param url: url to which submit S3 path
:param path: S3 path to training data
"""
url = f'/monitoring/profiles/batch/{modelversion_id}/s3'
return cluster.request("POST", url, json={"path": path})
def find(cluster: Cluster, name: str) -> 'DeploymentConfiguration':
"""
Search a deployment configuration by name
:param cluster:
:param name:
:return:
"""
resp = cluster.request("GET", f"{DeploymentConfiguration._BASE_URL}/{name}")
handle_request_error(resp, f"Failed to find Deployment Configuration named {name} {resp.status_code} {resp.text}")
return DeploymentConfiguration.parse_obj(resp.json())
def delete(cluster: Cluster, name: str) -> dict:
"""
Delete deployment configuration from Hydrosphere cluster
:param cluster: Active Cluster
:param name: Deployment configuration name
:return: json response from the server
"""
resp = cluster.request("DELETE", f"{DeploymentConfiguration._BASE_URL}/{name}")
handle_request_error(resp, f"Failed to delete Deployment Configuration named {name}: {resp.status_code} {resp.text}")
return resp
def list(cluster: Cluster) -> List['MetricSpec']:
"""
Send request and returns list with all available metric specs.
:param cluster: active cluster
:return: list with all available metric specs
"""
resp = cluster.request("GET", MetricSpec._BASE_URL)
handle_request_error(
resp,
f"Failed to list MetricSpecs. {resp.status_code} {resp.text}")
return [MetricSpec._from_json(cluster, x) for x in resp.json()]
def delete(cluster: Cluster, id: int) -> dict:
"""
Delete MetricSpec.
:return: result of deletion
"""
resp = cluster.request("DELETE", f"{MetricSpec._BASE_URL}/{id}")
handle_request_error(
resp,
f"Failed to delete MetricSpec for id={id}. {resp.status_code} {resp.text}"
)
return resp.json()
def _upload_local_file(cluster: Cluster, modelversion_id: int, path: str,
chunk_size=1024) -> requests.Response:
"""
Internal method for uploading local training data to Hydrosphere.
:param cluster: active cluster
:param modelversion_id: modelversion_id for which to upload training data
:param path: path to a local file
:param chunk_size: chunk size to use for streaming
"""
gen = read_in_chunks(path, chunk_size)
url = f'/monitoring/profiles/batch/{modelversion_id}'
return cluster.request("POST", url, data=gen, stream=True)
def find(cluster: Cluster, name: str, version: int) -> 'ModelVersion':
"""
Find a ModelVersion on the cluster by model name and a version.
:param cluster: active cluster
:param name: name of the model
:param version: version of the model
:return: ModelVersion object
"""
resp = cluster.request("GET", f"{ModelVersion._BASE_URL}/version/{name}/{version}")
handle_request_error(
resp, f"Failed to find model_version for name={name}, version={version}. {resp.status_code} {resp.text}")
return ModelVersion._from_json(cluster, resp.json())
def list(cluster: Cluster) -> List['ModelVersion']:
"""
List all model versions on the cluster.
:param cluster: active cluster
:return: list of ModelVersions
"""
resp = cluster.request("GET", f"{ModelVersion._BASE_URL}/version")
handle_request_error(
resp, f"Failed to list model versions. {resp.status_code} {resp.text}")
return [ModelVersion._from_json(cluster, modelversion_json)
for modelversion_json in resp.json()]
def find_by_id(cluster: Cluster, id: int) -> 'MetricSpec':
"""
Find MetricSpec by id.
:param cluster: active cluster
:param id:
:return: MetricSpec
"""
resp = cluster.request("GET", f"{MetricSpec._BASE_URL}/{id}")
handle_request_error(
resp,
f"Failed to retrieve MetricSpec for id={id}. {resp.status_code} {resp.text}"
)
return MetricSpec._from_json(cluster, resp.json())
def list(cluster: Cluster) -> List['Servable']:
"""
Retrieve a list of all servables available at your cluster
:param cluster: Hydrosphere cluster
:return: List of all Servables available at your cluster
"""
resp = cluster.request("GET", Servable._BASE_URL)
handle_request_error(
resp, f"Failed to list servables. {resp.status_code} {resp.text}")
return [
Servable._from_json(cluster, servable_json)
for servable_json in resp.json()
]
def find(cluster: Cluster, application_name: str) -> 'Application':
"""
Search for an application by name.
:param cluster: active cluster
:param application_name: application name
:return: deserialized application object
"""
resp = cluster.request("GET",
f"{Application._BASE_URL}/{application_name}")
handle_request_error(
resp,
f"Failed to find an application by name={application_name}. {resp.status_code} {resp.text}"
)
return Application._from_json(cluster, resp.json())
def find_by_id(cluster: Cluster, id: int) -> 'ModelVersion':
"""
Find a ModelVersion on the cluster by id.
:param cluster: active cluster
:param id: model version id
:return: ModelVersion object
"""
resp = cluster.request("GET", f"{ModelVersion._BASE_URL}/version")
handle_request_error(
resp, f"Failed to retrieve model_version by id={id}. {resp.status_code} {resp.text}")
for modelversion_json in resp.json():
if modelversion_json['id'] == id:
return ModelVersion._from_json(cluster, modelversion_json)
raise BadRequestException(f"Failed to retrieve model_version by id={id}.")
def delete(cluster: Cluster, application_name: str) -> dict:
"""
Delete an application by name.
:param cluster: active cluster
:param application_name: application name
:return: response from the cluster
"""
resp = cluster.request("DELETE",
f"{Application._BASE_URL}/{application_name}")
handle_request_error(
resp,
f"Failed to delete application for name={application_name}. {resp.status_code} {resp.text}"
)
return resp.json()
def find_by_name(cluster: Cluster, servable_name: str) -> 'Servable':
"""
Finds a serving servable in a cluster
:param cluster: active cluster
:param servable_name: a name of the servable
:raises ServableException:
:return: Servable
"""
resp = cluster.request("GET", f"{Servable._BASE_URL}/{servable_name}")
handle_request_error(
resp,
f"Failed to find servable for name={servable_name}. {resp.status_code} {resp.text}"
)
return Servable._from_json(cluster, resp.json())
def find_by_modelversion(cluster: Cluster,
modelversion_id: int) -> List['MetricSpec']:
"""
Find MetricSpecs by model version.
:param cluster: active cluster
:param modelversion_id: ModelVersions for which to return metrics.
:return: list of MetricSpec objects
"""
resp = cluster.request(
"GET", f"{MetricSpec._BASE_URL}/modelversion/{modelversion_id}")
handle_request_error(
resp,
f"Failed to list MetricSpecs for modelversion_id={modelversion_id}. {resp.status_code} {resp.text}"
)
return [MetricSpec._from_json(cluster, x) for x in resp.json()]
def list(cluster: Cluster) -> List['Application']:
"""
List all available applications from the cluster.
:param cluster: active cluster
:return: deserialized list of application objects
"""
resp = cluster.request("GET", Application._BASE_URL)
handle_request_error(
resp,
f"Failed to list all applications. {resp.status_code} {resp.text}")
applications = [
Application._from_json(cluster, app_json)
for app_json in resp.json()
]
return applications
def build(self, cluster: Cluster) -> DeploymentConfiguration:
"""
Create the Deployment Configuration in your Hydrosphere cluster.
:return: Deployment Configuration object from the Hydrosphere cluster
"""
config = DeploymentConfiguration(
name=self.name,
hpa=self.hpa,
pod=self.pod_spec,
container=self.container_spec,
deployment=self.deployment_spec
)
resp = cluster.request("POST", DeploymentConfiguration._BASE_URL, json=config.to_dict())
handle_request_error(resp, f"Failed to upload new Deployment Configuration. {resp.status_code} {resp.text}")
return DeploymentConfiguration.parse_obj(resp.json())
def delete(cluster: Cluster, servable_name: str) -> dict:
"""
Shut down and delete servable instance.
:param cluster: active cluster
:param servable_name: name of the servable
:return: json response from serve
.. warnings also::
Use with caution. Predictors previously associated with this servable will not be able to connect to it.
"""
resp = cluster.request("DELETE",
f"{Servable._BASE_URL}/{servable_name}")
handle_request_error(
resp,
f"Failed to delete the servable with name={servable_name}. {resp.status_code} {resp.text}"
)
return resp.json()
def build_external(self, cluster: Cluster) -> 'ModelVersion':
"""
Create an external ModelVersion on the cluster.
:param cluster: active cluster
:return: ModelVersion object
"""
if self.signature is None:
raise ValueError("signature is not specified for the model")
model = {
"name": self.name,
"signature": ModelSignature_to_signature_dict(self.signature),
"metadata": self.metadata
}
resp = cluster.request("POST", "/api/v2/externalmodel", json=model)
handle_request_error(
resp, f"Failed to create an external model. {resp.status_code} {resp.text}")
json_dict = resp.json()
json_dict['isExternal'] = True
return ModelVersion._from_json(cluster, json_dict)
def build(self, cluster: Cluster) -> 'ModelVersion':
"""
Upload local model instance to the cluster.
:param cluster: active cluster
:return: ModelVersion object
"""
if self.runtime is None:
raise ValueError("runtime is not specified for the model")
if self.signature is None:
raise ValueError("signature is not specified for the model")
meta = {
"name": self.name,
"runtime": self.runtime.dict(),
"modelSignature": ModelSignature_to_signature_dict(self.signature),
"installCommand": self.install_command,
"metadata": self.metadata
}
if self.monitoring_configuration:
meta.update({"monitoringConfiguration": self.monitoring_configuration.to_dict()})
tarpath = self.__create_tarball()
encoder = MultipartEncoder(
fields={
"payload": ("filename", open(tarpath, "rb")),
"metadata": json.dumps(meta)
}
)
resp = cluster.request("POST", "/api/v2/model/upload",
data=encoder, headers={'Content-Type': encoder.content_type})
handle_request_error(
resp, f"Failed to upload local model. {resp.status_code} {resp.text}")
modelversion = ModelVersion._from_json(cluster, resp.json())
modelversion.training_data = self.training_data
return modelversion
