You are viewing a plain text version of this content. The canonical link for it is here.
Posted to commits@beam.apache.org by an...@apache.org on 2023/12/12 02:27:44 UTC

(beam) 01/01: Skip TFT test. revert commit once done

This is an automated email from the ASF dual-hosted git repository.

anandinguva pushed a commit to branch criteo_mltransform
in repository https://gitbox.apache.org/repos/asf/beam.git

commit 12df8cf9a5f422540d5e718e17740f9ca017ad3f
Author: Anand Inguva <an...@google.com>
AuthorDate: Tue Dec 12 02:07:46 2023 +0000

    Skip TFT test. revert commit once done
---
 sdks/python/apache_beam/examples/ml_transform/ml_transform_it_test.py    | 1 +
 .../apache_beam/testing/benchmarks/cloudml/cloudml_benchmark_test.py     | 1 +
 2 files changed, 2 insertions(+)

diff --git a/sdks/python/apache_beam/examples/ml_transform/ml_transform_it_test.py b/sdks/python/apache_beam/examples/ml_transform/ml_transform_it_test.py
index 17adb9c7c6a..1e8a21c3ae6 100644
--- a/sdks/python/apache_beam/examples/ml_transform/ml_transform_it_test.py
+++ b/sdks/python/apache_beam/examples/ml_transform/ml_transform_it_test.py
@@ -57,6 +57,7 @@ def _publish_metrics(pipeline, metric_value, metrics_table, metric_name):
   )])
 
 
+@unittest.skip('Uncomment this line to run this test.')
 @pytest.mark.uses_tft
 class LargeMovieReviewDatasetProcessTest(unittest.TestCase):
   def test_process_large_movie_review_dataset(self):
diff --git a/sdks/python/apache_beam/testing/benchmarks/cloudml/cloudml_benchmark_test.py b/sdks/python/apache_beam/testing/benchmarks/cloudml/cloudml_benchmark_test.py
index ea2d93512fd..ccaf2681c2d 100644
--- a/sdks/python/apache_beam/testing/benchmarks/cloudml/cloudml_benchmark_test.py
+++ b/sdks/python/apache_beam/testing/benchmarks/cloudml/cloudml_benchmark_test.py
@@ -55,6 +55,7 @@ def _publish_metrics(pipeline, metric_value, metrics_table, metric_name):
   )])
 
 
+@unittest.skip('Remve this line to run this test')
 @pytest.mark.uses_tft
 class CloudMLTFTBenchmarkTest(unittest.TestCase):
   def test_cloudml_benchmark_criteo_small(self):