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create_training_pipeline_video_action_recognition_test.py
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create_training_pipeline_video_action_recognition_test.py
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# 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.
import uuid
import pytest
import os
import helpers
import create_training_pipeline_video_action_recognition_sample
from google.cloud import aiplatform
LOCATION = "us-central1"
PROJECT_ID = os.getenv("BUILD_SPECIFIC_GCLOUD_PROJECT")
DATASET_ID = "6881957627459272704" # permanent_swim_run_videos_action_recognition_dataset
DISPLAY_NAME = f"temp_create_training_pipeline_video_action_recognition_test_{uuid.uuid4()}"
MODEL_DISPLAY_NAME = f"Temp Model for {DISPLAY_NAME}"
MODEL_TYPE = "CLOUD"
API_ENDPOINT = "us-central1-aiplatform.googleapis.com"
@pytest.fixture
def shared_state():
state = {}
yield state
@pytest.fixture
def pipeline_client():
client_options = {"api_endpoint": API_ENDPOINT}
pipeline_client = aiplatform.gapic.PipelineServiceClient(
client_options=client_options
)
yield pipeline_client
@pytest.fixture
def model_client():
client_options = {"api_endpoint": API_ENDPOINT}
model_client = aiplatform.gapic.ModelServiceClient(
client_options=client_options)
yield model_client
@pytest.fixture(scope="function", autouse=True)
def teardown(shared_state, model_client, pipeline_client):
yield
model_client.delete_model(name=shared_state["model_name"])
pipeline_client.delete_training_pipeline(
name=shared_state["training_pipeline_name"]
)
# Training AutoML Vision Model
def test_create_training_pipeline_video_action_recognition_sample(
capsys, shared_state, pipeline_client
):
create_training_pipeline_video_action_recognition_sample.create_training_pipeline_video_action_recognition_sample(
project=PROJECT_ID,
display_name=DISPLAY_NAME,
dataset_id=DATASET_ID,
model_display_name=MODEL_DISPLAY_NAME,
model_type=MODEL_TYPE,
)
out, _ = capsys.readouterr()
assert "response:" in out
# Save resource name of the newly created training pipeline
shared_state["training_pipeline_name"] = helpers.get_name(out)
# Poll until the pipeline succeeds because we want to test the model_upload step as well.
helpers.wait_for_job_state(
get_job_method=pipeline_client.get_training_pipeline,
name=shared_state["training_pipeline_name"],
expected_state="SUCCEEDED",
timeout=5000,
freq=20,
)
training_pipeline = pipeline_client.get_training_pipeline(
name=shared_state["training_pipeline_name"]
)
# Check that the model indeed has been uploaded.
assert training_pipeline.model_to_upload.name != ""
shared_state["model_name"] = training_pipeline.model_to_upload.name