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create_training_pipeline_tabular_regression_sample_test.py
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create_training_pipeline_tabular_regression_sample_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 os
from uuid import uuid4
import create_training_pipeline_tabular_regression_sample
import pytest
import helpers
PROJECT_ID = os.getenv("BUILD_SPECIFIC_GCLOUD_PROJECT")
DATASET_ID = "3019804287640272896" # bq all
DISPLAY_NAME = f"temp_create_training_pipeline_test_{uuid4()}"
TARGET_COLUMN = "FLOAT_5000unique_REQUIRED"
PREDICTION_TYPE = "regression"
@pytest.fixture(scope="function", autouse=True)
def teardown(teardown_training_pipeline):
yield
def test_ucaip_generated_create_training_pipeline_sample(capsys, shared_state):
# The return of the cancellation can be flaky; max of 20 runs was 215 sec.
shared_state["cancel_batch_prediction_job_timeout"] = 300
create_training_pipeline_tabular_regression_sample.create_training_pipeline_tabular_regression_sample(
project=PROJECT_ID,
display_name=DISPLAY_NAME,
dataset_id=DATASET_ID,
model_display_name=f"Temp Model for {DISPLAY_NAME}",
target_column=TARGET_COLUMN,
)
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)