/
cancel_training_pipeline_sample_test.py
78 lines (61 loc) · 2.63 KB
/
cancel_training_pipeline_sample_test.py
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
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
# Copyright 2020 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from uuid import uuid4
import pytest
import os
import helpers
import create_training_pipeline_sample
import cancel_training_pipeline_sample
import delete_training_pipeline_sample
import get_training_pipeline_sample
from google.cloud import aiplatform
PROJECT_ID = os.getenv("BUILD_SPECIFIC_GCLOUD_PROJECT")
LOCATION = "us-central1"
DATASET_ID = "1084241610289446912" # Permanent 50 Flowers Dataset
DISPLAY_NAME = f"temp_create_training_pipeline_test_{uuid4()}"
TRAINING_DEFINITION_GCS_PATH = "gs://google-cloud-aiplatform/schema/trainingjob/definition/automl_image_classification_1.0.0.yaml"
@pytest.fixture(scope="function")
def training_pipeline_id(capsys):
create_training_pipeline_sample.create_training_pipeline_sample(
project=PROJECT_ID,
display_name=DISPLAY_NAME,
training_task_definition=TRAINING_DEFINITION_GCS_PATH,
dataset_id=DATASET_ID,
model_display_name=f"Temp Model for {DISPLAY_NAME}",
)
out, _ = capsys.readouterr()
training_pipeline_name = helpers.get_name(out)
assert "/" in training_pipeline_name
training_pipeline_id = training_pipeline_name.split("/")[-1]
yield training_pipeline_id
delete_training_pipeline_sample.delete_training_pipeline_sample(
project=PROJECT_ID, training_pipeline_id=training_pipeline_id
)
def test_ucaip_generated_cancel_training_pipeline_sample(capsys, training_pipeline_id):
# Run cancel pipeline sample
cancel_training_pipeline_sample.cancel_training_pipeline_sample(
project=PROJECT_ID, training_pipeline_id=training_pipeline_id
)
pipeline_client = aiplatform.gapic.PipelineServiceClient(
client_options={"api_endpoint": "us-central1-aiplatform.googleapis.com"}
)
# Waiting for training pipeline to be in CANCELLED state, otherwise raise error
helpers.wait_for_job_state(
get_job_method=pipeline_client.get_training_pipeline,
name=pipeline_client.training_pipeline_path(
project=PROJECT_ID,
location=LOCATION,
training_pipeline=training_pipeline_id,
),
)