Merge pull request kubeflow#1035 from kbthu/master

Update demo of mnist on kfp version 1.8.19
koor-tech · May 23, 2023 · dcced9d · dcced9d
2 parents 22dfca6 + 05e507a
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diff --git a/pipelines-demo/README.md b/pipelines-demo/README.md
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+# pipelines-demo on Kubeflow/examples
+
+This pipelines-demo contains many examples.
+
+* mnist
+  * create a volume 'mnist-model' on Kubeflow UI
+  * compile yaml: python mnist/mnist-example.py
+  * load mnist-example.py.yaml on Kubeflow UI pipelines
diff --git a/pipelines-demo/mnist/mnist-example.py b/pipelines-demo/mnist/mnist-example.py
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+#  Copyright 2023 kbthu. All Rights Reserved.
+#
+#  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
+#
+#   http://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 kfp
+from kfp import dsl
+
+def mnist_train():
+  cop = dsl.ContainerOp(
+    name='mnist_train',
+    image='kbthu/tf-mnist-example:1.0.1',
+    command=['python3'],
+    arguments=['/mnist/mnist-train.py'],
+    file_outputs={'output': '/model/model.keras'},
+  )
+  cop.container.set_image_pull_policy('IfNotPresent')
+  cop.add_pvolumes({'/model': dsl.PipelineVolume(pvc='mnist-model')})
+  return cop
+
+
+def mnist_test(model):
+  cop = dsl.ContainerOp(
+    name='mnist_test',
+    image='kbthu/tf-mnist-example:1.0.1',
+    command=['python3'],
+    arguments=['/mnist/mnist-test.py'],
+  )
+  cop.container.set_image_pull_policy('IfNotPresent')
+  cop.add_pvolumes({'/model': dsl.PipelineVolume(pvc='mnist-model')})
+  return cop
+
+
+@dsl.pipeline(
+  name='Kubeflow pipeline example',
+  description='Demonstrate the Kubeflow pipeline with Mnist training'
+)
+def kfp_example():
+  _train_op = mnist_train()
+
+  mnist_test(
+    dsl.InputArgumentPath(_train_op.outputs['output'])
+  ).after(_train_op)
+
+
+if __name__ == '__main__':
+  import kfp.compiler as compiler
+  compiler.Compiler().compile(kfp_example, __file__ + '.yaml')