コード例 #1
0
  def testMrpcPipelineNativeKeras(self):
    pipeline = bert_mrpc_pipeline._create_pipeline(
        pipeline_name=self._pipeline_name,
        data_root=self._data_root,
        module_file=self._module_file,
        serving_model_dir=self._serving_model_dir,
        pipeline_root=self._pipeline_root,
        metadata_path=self._metadata_path,
        beam_pipeline_args=['--direct_num_workers=1'])

    BeamDagRunner().run(pipeline)

    self.assertTrue(tf.io.gfile.exists(self._serving_model_dir))
    self.assertTrue(tf.io.gfile.exists(self._metadata_path))
    expected_execution_count = 9  # 8 components + 1 resolver
    metadata_config = metadata.sqlite_metadata_connection_config(
        self._metadata_path)
    with metadata.Metadata(metadata_config) as m:
      artifact_count = len(m.store.get_artifacts())
      execution_count = len(m.store.get_executions())
      self.assertGreaterEqual(artifact_count, execution_count)
      self.assertEqual(expected_execution_count, execution_count)

    self.assertPipelineExecution()

    # Runs pipeline the second time.
    BeamDagRunner().run(pipeline)

    # All executions but Evaluator and Pusher are cached.
    with metadata.Metadata(metadata_config) as m:
      # Artifact count is increased by 3 caused by Evaluator and Pusher.
      self.assertEqual(artifact_count + 3, len(m.store.get_artifacts()))
      artifact_count = len(m.store.get_artifacts())
      self.assertEqual(expected_execution_count * 2,
                       len(m.store.get_executions()))

    # Runs pipeline the third time.
    BeamDagRunner().run(pipeline)

    # Asserts cache execution.
    with metadata.Metadata(metadata_config) as m:
      # Artifact count is unchanged.
      self.assertEqual(artifact_count, len(m.store.get_artifacts()))
      self.assertEqual(expected_execution_count * 3,
                       len(m.store.get_executions()))
コード例 #2
0
    def testMrpcPipelineNativeKeras(self):
        pipeline = bert_mrpc_pipeline._create_pipeline(
            pipeline_name=self._pipeline_name,
            data_root=self._data_root,
            module_file=self._module_file,
            serving_model_dir=self._serving_model_dir,
            pipeline_root=self._pipeline_root,
            metadata_path=self._metadata_path,
            beam_pipeline_args=[])

        LocalDagRunner().run(pipeline)

        self.assertTrue(fileio.exists(self._serving_model_dir))
        self.assertTrue(fileio.exists(self._metadata_path))
        expected_execution_count = 9  # 8 components + 1 resolver
        metadata_config = metadata.sqlite_metadata_connection_config(
            self._metadata_path)
        with metadata.Metadata(metadata_config) as m:
            artifact_count = len(m.store.get_artifacts())
            execution_count = len(m.store.get_executions())
            self.assertGreaterEqual(artifact_count, execution_count)
            self.assertEqual(expected_execution_count, execution_count)

        self.assertPipelineExecution()