def build_client(resource: OdahuflowCloudResourceUpdatePair,
api_client: RemoteAPIClient) -> typing.Optional[object]:
"""
Build client for particular resource (e.g. it builds ModelTrainingClient for ModelTraining resource)
:param resource: target resource
:param api_client: base API client to extract connection options from
:return: remote client or None
"""
if isinstance(resource.resource, ModelTraining):
return ModelTrainingClient.construct_from_other(api_client)
elif isinstance(resource.resource, ModelDeployment):
return ModelDeploymentClient.construct_from_other(api_client)
elif isinstance(resource.resource, Connection):
return ConnectionClient.construct_from_other(api_client)
elif isinstance(resource.resource, ToolchainIntegration):
return ToolchainIntegrationClient.construct_from_other(api_client)
elif isinstance(resource.resource, ModelRoute):
return ModelRouteClient.construct_from_other(api_client)
elif isinstance(resource.resource, ModelPackaging):
return ModelPackagingClient.construct_from_other(api_client)
elif isinstance(resource.resource, PackagingIntegration):
return PackagingIntegrationClient.construct_from_other(api_client)
else:
raise InvalidResourceType('{!r} is invalid resource '.format(
resource.resource))
def run(client: ModelTrainingClient, train_id: str, manifest_file: List[str],
manifest_dir: List[str], output_dir: str):
"""
\b
Start a training process locally.
\b
Usage example:
* odahuflowctl local train run --id examples-git
\f
"""
entities: List[OdahuflowCloudResourceUpdatePair] = []
for file_path in manifest_file:
entities.extend(parse_resources_file(file_path).changes)
for dir_path in manifest_dir:
entities.extend(parse_resources_dir(dir_path))
mt: Optional[ModelTraining] = None
# find a training
toolchains: Dict[str, ToolchainIntegration] = {}
for entity in map(lambda x: x.resource, entities):
if isinstance(entity, ToolchainIntegration):
toolchains[entity.id] = entity
elif isinstance(entity, ModelTraining) and entity.id == train_id:
mt = entity
if not mt:
click.echo(
f'{train_id} training not found. Trying to retrieve it from API server'
)
mt = client.get(train_id)
toolchain = toolchains.get(mt.spec.toolchain)
if not toolchain:
click.echo(
f'{toolchain} toolchain not found. Trying to retrieve it from API server'
)
toolchain = ToolchainIntegrationClient.construct_from_other(
client).get(mt.spec.toolchain)
trainer = K8sTrainer(
model_training=mt,
toolchain_integration=toolchain,
)
start_train(trainer, output_dir)