feat(components): PyTorch - Added the Create PyTorch Model Archive co…

…mponent (#5630)

* Components - PyTorch - Added the Create PyTorch Model Archive component

* Added component to the sample pipeline

components/PyTorch/Create_PyTorch_Model_Archive/component.yaml

@@ -0,0 +1,39 @@
+name: Create PyTorch Model Archive
+inputs:
+- {name: Model, type: PyTorchScriptModule}
+- {name: Model name, type: String, default: model}
+- {name: Model version, type: String, default: "1.0"}
+- {name: Handler, type: PythonCode, description: "See https://github.com/pytorch/serve/blob/master/docs/custom_service.md"}
+outputs:
+- {name: Model archive, type: PyTorchModelArchive}
+metadata:
+  annotations:
+    author: Alexey Volkov <alexey.volkov@ark-kun.com>
+implementation:
+  container:
+    image: pytorch/torchserve:0.3.0-cpu
+    command:
+    - bash
+    - -exc
+    - |
+      model_path=$0
+      handler_path=$1
+      model_name=$2
+      model_version=$3
+      output_model_archive_path=$4
+      
+      mkdir -p "$(dirname "$output_model_archive_path")"
+
+      # torch-model-archiver needs the handler to have .py extension
+      cp "$handler_path" handler.py
+      torch-model-archiver --model-name "$model_name" --version "$model_version" --serialized-file "$model_path" --handler handler.py
+      
+      # torch-model-archiver does not allow specifying the output path, but always writes to "${model_name}.<format>"
+      expected_model_archive_path="${model_name}.mar"
+      mv "$expected_model_archive_path" "$output_model_archive_path"
+
+    - {inputPath: Model}
+    - {inputPath: Handler}
+    - {inputValue: Model name}
+    - {inputValue: Model version}
+    - {outputPath: Model archive}

components/PyTorch/_samples/Train_fully-connected_network.pipeline.py

@@ -3,10 +3,12 @@
 
 chicago_taxi_dataset_op = components.load_component_from_url('https://raw.githubusercontent.com/kubeflow/pipelines/e3337b8bdcd63636934954e592d4b32c95b49129/components/datasets/Chicago%20Taxi/component.yaml')
 pandas_transform_csv_op = components.load_component_from_url('https://raw.githubusercontent.com/kubeflow/pipelines/6162d55998b176b50267d351241100bb0ee715bc/components/pandas/Transform_DataFrame/in_CSV_format/component.yaml')
+download_op = components.load_component_from_url('https://raw.githubusercontent.com/kubeflow/pipelines/240543e483076ae718f82c6f280441daa2f041fd/components/web/Download/component.yaml')
 
 create_fully_connected_pytorch_network_op = components.load_component_from_url('https://raw.githubusercontent.com/kubeflow/pipelines/4e1facea1a270535b515a9e8cc59422d1ad76a9e/components/PyTorch/Create_fully_connected_network/component.yaml')
 train_pytorch_model_from_csv_op = components.load_component_from_url('https://raw.githubusercontent.com/kubeflow/pipelines/603342c4b88fe2d69ff07682f702cd3601e883bb/components/PyTorch/Train_PyTorch_model/from_CSV/component.yaml')
 convert_to_onnx_from_pytorch_script_module_op = components.load_component_from_url('https://raw.githubusercontent.com/kubeflow/pipelines/e011e4affa85542ef2b24d63fdac27f8d939bbee/components/PyTorch/Convert_to_OnnxModel_from_PyTorchScriptModule/component.yaml')
+create_pytorch_model_archive_op = components.load_component_from_url('https://raw.githubusercontent.com/kubeflow/pipelines/abc180be2b2b5538d19eb87124684629ec45e620/components/PyTorch/Create_PyTorch_Model_Archive/component.yaml')
 
 
 def pytorch_pipeline():
@@ -47,6 +49,16 @@ def pytorch_pipeline():
         list_of_input_shapes=[[len(feature_columns)]],
     )
 
+    # TODO: Use a real working regression handler here. See https://github.com/pytorch/serve/issues/987
+    serving_handler = download_op('https://raw.githubusercontent.com/pytorch/serve/5c03e711a401387a1d42fc01072fcc38b4995b66/ts/torch_handler/base_handler.py').output
+
+    model_archive = create_pytorch_model_archive_op(
+        model=trained_model,
+        handler=serving_handler,
+        # model_name="model",  # Optional
+        # model_version="1.0",  # Optional
+    ).output
+
 if __name__ == '__main__':
     import kfp
     kfp_endpoint=None