Python dsl.pipeline方法代碼示例

# 需要導入模塊: from kfp import dsl [as 別名]
# 或者: from kfp.dsl import pipeline [as 別名]
def container(self):
        """`Container` object that represents the `container` property in 
        `io.argoproj.workflow.v1alpha1.Template`. Can be used to update the
        container configurations. 
        
        Example:
            import kfp.dsl as dsl
            from kubernetes.client.models import V1EnvVar
    
            @dsl.pipeline(name='example_pipeline')
            def immediate_value_pipeline():
                op1 = (dsl.ContainerOp(name='example', image='nginx:alpine')
                          .container
                            .add_env_variable(V1EnvVar(name='HOST', value='foo.bar'))
                            .add_env_variable(V1EnvVar(name='PORT', value='80'))
                            .parent # return the parent `ContainerOp`
                        )
        """
        return self._container 

# 需要導入模塊: from kfp import dsl [as 別名]
# 或者: from kfp.dsl import pipeline [as 別名]
def parse_arguments():
  """Parse command line arguments."""

  parser = argparse.ArgumentParser()
  parser.add_argument('--py',
                      type=str,
                      help='local absolute path to a py file.')
  parser.add_argument('--function',
                      type=str,
                      help='The name of the function to compile if there are multiple.')
  parser.add_argument('--namespace',
                      type=str,
                      help='The namespace for the pipeline function')
  parser.add_argument('--output',
                      type=str,
                      required=True,
                      help='local path to the output workflow yaml file.')
  parser.add_argument('--disable-type-check',
                      action='store_true',
                      help='disable the type check, default is enabled.')

  args = parser.parse_args()
  return args 

# 需要導入模塊: from kfp import dsl [as 別名]
# 或者: from kfp.dsl import pipeline [as 別名]
def _compile_pipeline_function(pipeline_funcs, function_name, output_path, type_check):
  if len(pipeline_funcs) == 0:
    raise ValueError('A function with @dsl.pipeline decorator is required in the py file.')

  if len(pipeline_funcs) > 1 and not function_name:
    func_names = [x.__name__ for x in pipeline_funcs]
    raise ValueError('There are multiple pipelines: %s. Please specify --function.' % func_names)

  if function_name:
    pipeline_func = next((x for x in pipeline_funcs if x.__name__ == function_name), None)
    if not pipeline_func:
      raise ValueError('The function "%s" does not exist. '
                       'Did you forget @dsl.pipeline decoration?' % function_name)
  else:
    pipeline_func = pipeline_funcs[0]

  kfp.compiler.Compiler().compile(pipeline_func, output_path, type_check) 

# 需要導入模塊: from kfp import dsl [as 別名]
# 或者: from kfp.dsl import pipeline [as 別名]
def test_decorator(self):
    """Test @pipeline decorator."""
    @pipeline(
      name='p1',
      description='description1'
    )
    def my_pipeline1():
      pass

    @pipeline(
      name='p2',
      description='description2'
    )
    def my_pipeline2():
      pass
    
    self.assertEqual(my_pipeline1._component_human_name, 'p1')
    self.assertEqual(my_pipeline2._component_human_name, 'p2')
    self.assertEqual(my_pipeline1._component_description, 'description1')
    self.assertEqual(my_pipeline2._component_description, 'description2') 

# 需要導入模塊: from kfp import dsl [as 別名]
# 或者: from kfp.dsl import pipeline [as 別名]
def pipeline(loopidy_doop: list = [3, 5, 7, 9]):
    op0 = dsl.ContainerOp(
        name="my-out-cop0",
        image='python:alpine3.6',
        command=["sh", "-c"],
        arguments=[
            'python -c "import json; import sys; json.dump([i for i in range(20, 31)], open(\'/tmp/out.json\', \'w\'))"'],
        file_outputs={'out': '/tmp/out.json'},
    )

    with dsl.ParallelFor(loopidy_doop) as item:
        op1 = dsl.ContainerOp(
            name="my-in-cop1",
            image="library/bash:4.4.23",
            command=["sh", "-c"],
            arguments=["echo no output global op1, item: %s" % item],
        ).after(op0)

    op_out = dsl.ContainerOp(
        name="my-out-cop2",
        image="library/bash:4.4.23",
        command=["sh", "-c"],
        arguments=["echo no output global op2, outp: %s" % op0.output],
    ) 

# 需要導入模塊: from kfp import dsl [as 別名]
# 或者: from kfp.dsl import pipeline [as 別名]
def pipeline(my_pipe_param: int = 10):
    loop_args = [{'a': 1, 'b': 2}, {'a': 10, 'b': 20}]
    with dsl.ParallelFor(loop_args) as item:
        op1 = dsl.ContainerOp(
            name="my-in-coop1",
            image="library/bash:4.4.23",
            command=["sh", "-c"],
            arguments=["echo op1 %s %s" % (item.a, my_pipe_param)],
        )

        op2 = dsl.ContainerOp(
            name="my-in-coop2",
            image="library/bash:4.4.23",
            command=["sh", "-c"],
            arguments=["echo op2 %s" % item.b],
        )

    op_out = dsl.ContainerOp(
        name="my-out-cop",
        image="library/bash:4.4.23",
        command=["sh", "-c"],
        arguments=["echo %s" % my_pipe_param],
    ) 

# 需要導入模塊: from kfp import dsl [as 別名]
# 或者: from kfp.dsl import pipeline [as 別名]
def pipeline():
    op0 = dsl.ContainerOp(
        name="my-out-cop0",
        image='python:alpine3.6',
        command=["sh", "-c"],
        arguments=['python -c "import json; import sys; json.dump([{\'a\': 1, \'b\': 2}, {\'a\': 10, \'b\': 20}], open(\'/tmp/out.json\', \'w\'))"'],
        file_outputs={'out': '/tmp/out.json'},
    )

    with dsl.ParallelFor(op0.output) as item:
        op1 = dsl.ContainerOp(
            name="my-in-cop1",
            image="library/bash:4.4.23",
            command=["sh", "-c"],
            arguments=["echo do output op1 item.a: %s" % item.a],
        )

    op_out = dsl.ContainerOp(
        name="my-out-cop2",
        image="library/bash:4.4.23",
        command=["sh", "-c"],
        arguments=["echo do output op2, outp: %s" % op0.output],
    ) 

# 需要導入模塊: from kfp import dsl [as 別名]
# 或者: from kfp.dsl import pipeline [as 別名]
def save_most_frequent_word(message: str, outputpath: str):
  """A pipeline function describing the orchestration of the workflow."""

  exit_op = ExitHandlerOp('exiting')
  with dsl.ExitHandler(exit_op):
    counter = GetFrequentWordOp(
          name='get-Frequent',
          message=message)
    counter.set_memory_request('200M')

    saver = SaveMessageOp(
          name='save',
          message=counter.output,
          output_path=outputpath)
    saver.set_cpu_limit('0.5')
    saver.set_gpu_limit('2')
    saver.add_node_selector_constraint('cloud.google.com/gke-accelerator', 'nvidia-tesla-k80')
    saver.apply(gcp.use_tpu(tpu_cores = 8, tpu_resource = 'v2', tf_version = '1.12')) 

# 需要導入模塊: from kfp import dsl [as 別名]
# 或者: from kfp.dsl import pipeline [as 別名]
def test_basic_workflow_without_decorator(self):
    """Test compiling a workflow and appending pipeline params."""
    test_data_dir = os.path.join(os.path.dirname(__file__), 'testdata')
    sys.path.append(test_data_dir)
    import basic_no_decorator
    tmpdir = tempfile.mkdtemp()
    try:
      compiled_workflow = compiler.Compiler().create_workflow(
          basic_no_decorator.save_most_frequent_word,
          'Save Most Frequent',
          'Get Most Frequent Word and Save to GCS',
          [
            basic_no_decorator.message_param,
            basic_no_decorator.output_path_param
          ])
      with open(os.path.join(test_data_dir, 'basic_no_decorator.yaml'), 'r') as f:
        golden = yaml.safe_load(f)

      for workflow in golden, compiled_workflow:
        del workflow['metadata']

      self.assertEqual(golden, compiled_workflow)
    finally:
      shutil.rmtree(tmpdir) 

# 需要導入模塊: from kfp import dsl [as 別名]
# 或者: from kfp.dsl import pipeline [as 別名]
def _test_py_compile_yaml(self, file_base_name):
    test_data_dir = os.path.join(os.path.dirname(__file__), 'testdata')
    py_file = os.path.join(test_data_dir, file_base_name + '.py')
    tmpdir = tempfile.mkdtemp()
    try:
      target_yaml = os.path.join(tmpdir, file_base_name + '-pipeline.yaml')
      subprocess.check_call([
          'dsl-compile', '--py', py_file, '--output', target_yaml])
      with open(os.path.join(test_data_dir, file_base_name + '.yaml'), 'r') as f:
        golden = yaml.safe_load(f)

      with open(os.path.join(test_data_dir, target_yaml), 'r') as f:
        compiled = yaml.safe_load(f)

      for workflow in golden, compiled:
        del workflow['metadata']
        for template in workflow['spec']['templates']:
          template.pop('metadata', None)

      self.maxDiff = None
      self.assertEqual(golden, compiled)
    finally:
      shutil.rmtree(tmpdir) 

# 需要導入模塊: from kfp import dsl [as 別名]
# 或者: from kfp.dsl import pipeline [as 別名]
def test_set_parallelism(self):
    """Test a pipeline with parallelism limits."""
    def some_op():
        return dsl.ContainerOp(
            name='sleep',
            image='busybox',
            command=['sleep 1'],
        )

    @dsl.pipeline()
    def some_pipeline():
      some_op()
      some_op()
      some_op()
      dsl.get_pipeline_conf().set_parallelism(1)

    workflow_dict = kfp.compiler.Compiler()._compile(some_pipeline)
    self.assertEqual(workflow_dict['spec']['parallelism'], 1) 

# 需要導入模塊: from kfp import dsl [as 別名]
# 或者: from kfp.dsl import pipeline [as 別名]
def test_set_ttl_seconds_after_finished(self):
    """Test a pipeline with ttl after finished."""
    def some_op():
        return dsl.ContainerOp(
            name='sleep',
            image='busybox',
            command=['sleep 1'],
        )

    @dsl.pipeline()
    def some_pipeline():
      some_op()
      dsl.get_pipeline_conf().set_ttl_seconds_after_finished(86400)

    workflow_dict = kfp.compiler.Compiler()._compile(some_pipeline)
    self.assertEqual(workflow_dict['spec']['ttlSecondsAfterFinished'], 86400) 

# 需要導入模塊: from kfp import dsl [as 別名]
# 或者: from kfp.dsl import pipeline [as 別名]
def test_op_transformers(self):
    def some_op():
      return dsl.ContainerOp(
          name='sleep',
          image='busybox',
          command=['sleep 1'],
      )

    @dsl.pipeline(name='some_pipeline')
    def some_pipeline():
      task1 = some_op()
      task2 = some_op()
      task3 = some_op()

      dsl.get_pipeline_conf().op_transformers.append(lambda op: op.set_retry(5))

    workflow_dict = compiler.Compiler()._compile(some_pipeline)
    for template in workflow_dict['spec']['templates']:
      container = template.get('container', None)
      if container:
        self.assertEqual(template['retryStrategy']['limit'], 5) 

# 需要導入模塊: from kfp import dsl [as 別名]
# 或者: from kfp.dsl import pipeline [as 別名]
def test_image_pull_policy(self):
    def some_op():
      return dsl.ContainerOp(
          name='sleep',
          image='busybox',
          command=['sleep 1'],
      )

    @dsl.pipeline(name='some_pipeline')
    def some_pipeline():
      task1 = some_op()
      task2 = some_op()
      task3 = some_op()

      dsl.get_pipeline_conf().set_image_pull_policy(policy="Always")
    workflow_dict = compiler.Compiler()._compile(some_pipeline)
    for template in workflow_dict['spec']['templates']:
      container = template.get('container', None)
      if container:
        self.assertEqual(template['container']['imagePullPolicy'], "Always") 

# 需要導入模塊: from kfp import dsl [as 別名]
# 或者: from kfp.dsl import pipeline [as 別名]
def test_set_default_pod_node_selector(self):
    """Test a pipeline with node selector."""
    def some_op():
        return dsl.ContainerOp(
            name='sleep',
            image='busybox',
            command=['sleep 1'],
        )

    @dsl.pipeline()
    def some_pipeline():
      some_op()
      dsl.get_pipeline_conf().set_default_pod_node_selector(label_name="cloud.google.com/gke-accelerator", value="nvidia-tesla-p4")

    workflow_dict = kfp.compiler.Compiler()._compile(some_pipeline)
    self.assertEqual(workflow_dict['spec']['nodeSelector'], {"cloud.google.com/gke-accelerator":"nvidia-tesla-p4"})