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# pylint: disable=line-too-long,useless-suppression
import functools
from devtools_testutils import AzureRecordedTestCase, EnvironmentVariableLoader, recorded_by_proxy
from azure.core.credentials import AzureKeyCredential
from azure.ai.textanalytics.authoring import TextAuthoringClient
from azure.ai.textanalytics.authoring.models import TrainingJobResult
ConversationsPreparer = functools.partial(
EnvironmentVariableLoader,
"authoring",
authoring_endpoint="https://Sanitized.cognitiveservices.azure.com/",
authoring_key="fake_key",
)
class TestConversations(AzureRecordedTestCase):
def create_client(self, endpoint, key):
return TextAuthoringClient(endpoint, AzureKeyCredential(key))
class TestConversationsCancelTrainingSync(TestConversations):
@ConversationsPreparer()
@recorded_by_proxy
def test_cancel_training_job(self, authoring_endpoint, authoring_key):
client = self.create_client(authoring_endpoint, authoring_key)
project_client = client.get_project_client("single-class-project")
job_id = "8bfbd8e2-018f-4dfd-9f8f-75bf76410168_638931456000000000"
poller = project_client.project.begin_cancel_training_job(
job_id=job_id,
)
result = poller.result() # TrainingJobResult
assert (
result.training_status.status == "succeeded"
), f"Cancellation failed with status: {result.training_status.status}"
print(f"Model Label: {result.model_label}")
print(f"Training Config Version: {result.training_config_version}")
if result.training_status is not None:
print(f"Training Status: {result.training_status.status}")
print(f"Training %: {result.training_status.percent_complete}")
if result.evaluation_status is not None:
print(f"Evaluation Status: {result.evaluation_status.status}")
print(f"Evaluation %: {result.evaluation_status.percent_complete}")
print(f"Estimated End: {result.estimated_end_on}")
|
