def test_create_pipeline():
pipeline_yaml = 'pipeline.yaml'
requests = [
pipelines_pb2.PipelinesCreateRequest(
header=BaseClient.get_request_header(),
definition=pipelines_pb2.PipelineDefinitionFile(
path='pipeline.yaml', content=PIPELINE_TEXT))
]
responses = [
pipelines_pb2.PipelinesCreateResponse(
header=common_pb2.ResponseHeader(code=0, messages=[]),
pipeline_id=common_pb2.Identifier(
value='92656d79fa414db6b294069c0e9e6df5'))
]
stub_method_handlers = [('Create', 'stream_unary', (requests, responses))]
# set handlers
MockClaraPipelineServiceClient.stub_method_handlers = stub_method_handlers
def_list = [
pipeline_types.PipelineDefinition(name=pipeline_yaml,
content=PIPELINE_TEXT)
]
with MockClaraPipelineServiceClient('localhost:50051') as client:
pipeline_id = client.create_pipeline(definition=def_list)
print(pipeline_id)
assert pipeline_id.value == '92656d79fa414db6b294069c0e9e6df5'
def pipeline_details(self, pipeline_id: pipeline_types.PipelineId, timeout=None) -> pipeline_types.PipelineDetails:
"""
Requests details of a pipeline, identified by pipeline_types.PipelineId, from Clara.
Args:
pipeline_id (pipeline_types.PipelineId): Unique identifier of the pipeline.
Return:
A pipeline_types.PipelineDetails instance with details on the pipeline specified by 'pipeline_id'
"""
if (self._channel is None) or (self._stub is None):
raise Exception("Connection is currently closed. Please run reconnect() to reopen connection")
if pipeline_id.value is None or pipeline_id.value == "":
raise Exception("Pipeline identifier argument must be initialized with non-null instance")
request = pipelines_pb2.PipelinesDetailsRequest(
header=self.get_request_header(),
pipeline_id=pipeline_id.to_grpc_value(),
)
response = self._stub.Details(request, timeout=timeout)
responses = [resp for resp in response]
if len(responses) > 0:
self.check_response_header(header=responses[0].header)
result = pipeline_types.PipelineDetails(
name=responses[0].name,
pipeline_id=pipeline_types.PipelineId(responses[0].pipeline_id.value),
metadata=responses[0].metadata
)
result_definition = []
for resp in responses:
result_definition.append(
pipeline_types.PipelineDefinition(
name=resp.name,
content=resp.definition
)
)
result.definition = result_definition
return result
return None
from pathlib import Path
from nvidia_clara.pipelines_client import PipelinesClient
import nvidia_clara.pipeline_types as pipeline_types
# Client Creation with IP and Port of running instance of Clara
clara_ip_address = "10.0.0.1"
clara_port = "30031"
pipeline_client = PipelinesClient(target=clara_ip_address, port=clara_port)
# Create list of pipeline_types.PipelineDefinition with local path to pipeline .yaml
file_path = "./liver-tumor-pipeline.yaml"
definitions = [
pipeline_types.PipelineDefinition(name=file_path,
content=Path(file_path).read_text())
]
# Create Pipeline with definition list created
pipeline_id = pipeline_client.create_pipeline(definition=definitions)
print(pipeline_id)
# Get List of Created Pipelines PipelinesClient.list_pipelines()
pipelines = [(pipe_info.pipeline_id.value, pipe_info.name)
for pipe_info in pipeline_client.list_pipelines()]
print(pipelines)
# Get Details of Pipeline with PipelinesClient.pipeline_details()
pipeline_details = pipeline_client.pipeline_details(pipeline_id=pipeline_id)
# Remove Pipeline