c09d7b252a74c0fb4ca6d21516867cb7942b7cf5,ml/kubeflow-pipelines/samples/kubeflow-tf/workflow1.py,,workflow1,#,22

Before Change

          "--stage", "eval",
          "--preprocessing_module", preprocessing_module2]
      )
  tfttrain2 = dsl.ContainerOp(
      name = "tft-train2",
      image = "gcr.io/google-samples/ml-pipeline-dataflow-tftbq-taxi",
      arguments = [ "--input_handle", input_handle_train, "--outfile_prefix", outfile_prefix_train,
          "--working_dir", "%s/%s/tft-train2" % (working_dir, "{{workflow.name}}"),
          "--project", project,
          "--mode", preprocess_mode,
          "--setup_file", tft_setup_file,
          "--max_rows", max_rows,
          "--ts1", ts1,
          "--ts2", ts2,
          "--stage", "train",
          "--preprocessing_module", preprocessing_module2]
      )

  train = dsl.ContainerOp(
      name = "train",
      image = "gcr.io/google-samples/ml-pipeline-kubeflow-tf-taxi",

After Change

          "--stage", "eval",
          "--preprocessing_module", preprocessing_module2]
      ).apply(gcp.use_gcp_secret("user-gcp-sa"))
  tfttrain2 = dsl.ContainerOp(
      name = "tft-train2",
      image = "gcr.io/google-samples/ml-pipeline-dataflow-tftbq-taxi",
      arguments = [ "--input_handle", input_handle_train, "--outfile_prefix", outfile_prefix_train,
          "--working_dir", "%s/%s/tft-train2" % (working_dir, "{{workflow.name}}"),
          "--project", project,
          "--mode", preprocess_mode,
          "--setup_file", tft_setup_file,
          "--max_rows", max_rows,
          "--ts1", ts1,
          "--ts2", ts2,
          "--stage", "train",
          "--preprocessing_module", preprocessing_module2]
      ).apply(gcp.use_gcp_secret("user-gcp-sa"))

  train = dsl.ContainerOp(
      name = "train",
      image = "gcr.io/google-samples/ml-pipeline-kubeflow-tf-taxi",

Instances