1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
|
# pylint: disable=line-too-long,useless-suppression
import functools
import pytest
from devtools_testutils import AzureRecordedTestCase, EnvironmentVariableLoader
from devtools_testutils.aio import recorded_by_proxy_async
from azure.core.credentials import AzureKeyCredential
from azure.ai.language.conversations.authoring.aio import ConversationAuthoringClient
from azure.ai.language.conversations.authoring.models import TrainingJobResult
ConversationsPreparer = functools.partial(
EnvironmentVariableLoader,
"authoring",
authoring_endpoint="https://Sanitized.cognitiveservices.azure.com/",
authoring_key="fake_key",
)
class TestConversationsAsync(AzureRecordedTestCase):
async def create_client(self, endpoint: str, key: str) -> ConversationAuthoringClient:
return ConversationAuthoringClient(endpoint, AzureKeyCredential(key))
class TestConversationsCancelTrainingAsync(TestConversationsAsync):
@ConversationsPreparer()
@recorded_by_proxy_async
@pytest.mark.asyncio
async def test_cancel_training_job_async(self, authoring_endpoint, authoring_key):
client = await self.create_client(authoring_endpoint, authoring_key)
try:
project_name = "Test-data-labels"
job_id = "f0f1760a-f9b9-4a7c-924d-57892aa75ebd_638916768000000000"
project_client = client.get_project_client(project_name)
poller = await project_client.project.begin_cancel_training_job(
job_id=job_id,
)
result = await poller.result() # TrainingJobResult
assert result.training_status.status == "cancelled", 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}")
print(f"Training Mode: {result.training_mode}")
if result.data_generation_status is not None:
print(f"Data Generation Status: {result.data_generation_status.status}")
print(f"Data Generation %: {result.data_generation_status.percent_complete}")
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}")
finally:
await client.close()
|
