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fixed pipeline to use Kubeflow instead of using Tekton
1 parent 67d9fb2 commit 9966096

9 files changed

+913
-716
lines changed

1_experiment_train.ipynb

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2_save_model.ipynb

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"metadata": {
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"celltoolbar": "Raw Cell Format",
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"kernelspec": {
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"display_name": "Python 3.9",
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"display_name": "Python 3.11",
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"language": "python",
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"name": "python3"
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},
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.9.18"
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"version": "3.11.9"
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}
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},
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"nbformat": 4,

3_rest_requests_multi_model.ipynb

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"source": [
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"import requests\n",
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"\n",
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"\n",
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"def rest_request(data):\n",
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" json_data = {\n",
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" \"inputs\": [\n",
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"display_name": "Python 3.11",
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"language": "python",
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"name": "python3"
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},
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.11.2"
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"version": "3.11.9"
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}
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},
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"nbformat": 4,

4_grpc_requests_multi_model.ipynb

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@@ -29,8 +29,8 @@
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"metadata": {},
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"outputs": [],
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"source": [
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"!pip install grpcio grpcio-tools\n",
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"!pip install --upgrade pip"
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"!pip install --upgrade pip\n",
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"!pip install grpcio grpcio-tools"
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]
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},
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{
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"import utils.grpc_predict_v2_pb2 as grpc_predict_v2_pb2\n",
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"import utils.grpc_predict_v2_pb2_grpc as grpc_predict_v2_pb2_grpc\n",
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"\n",
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"\n",
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"channel = grpc.insecure_channel(f\"{grpc_host}:{grpc_port}\")\n",
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"stub = grpc_predict_v2_pb2_grpc.GRPCInferenceServiceStub(channel)\n",
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"\n",
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"display_name": "Python 3.11",
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"language": "python",
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"name": "python3"
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},
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.11.2"
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"version": "3.11.9"
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}
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},
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"nbformat": 4,

5 Train Save.pipeline

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@@ -29,12 +29,12 @@
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"kubernetes_tolerations": [],
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"mounted_volumes": [],
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"filename": "1_experiment_train.ipynb",
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"runtime_image": "quay.io/modh/runtime-images@sha256:ba76fd74b7595329a23f710485a7701caa0a7b495e60c89a23d5338ca13cf2e2"
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"runtime_image": "quay.io/modh/runtime-images@sha256:4c3098b7a369b8dad113be97f35ea202dde0a03d3d08a2c010e3b81209b39735"
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},
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"label": "",
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"ui_data": {
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"label": "1_experiment_train.ipynb",
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"image": "/notebook/<your-namespace>/fraud-detection/static/elyra/notebook.svg",
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"image": "/notebook/nerc-demo-5b7ce1/fraud-detection/static/elyra/notebook.svg",
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"x_pos": 118.00000381469727,
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"y_pos": 221,
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"description": "Run notebook file"
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"kubernetes_shared_mem_size": {},
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"kubernetes_tolerations": [],
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"mounted_volumes": [],
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"filename": "2_save_model.ipynb"
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"filename": "2_save_model.ipynb",
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"runtime_image": "quay.io/modh/runtime-images@sha256:4c3098b7a369b8dad113be97f35ea202dde0a03d3d08a2c010e3b81209b39735"
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},
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"label": "",
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"ui_data": {
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"label": "2_save_model.ipynb",
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"image": "/notebook/<your-namespace>/fraud-detection/static/elyra/notebook.svg",
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"image": "/notebook/nerc-demo-5b7ce1/fraud-detection/static/elyra/notebook.svg",
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"x_pos": 387,
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"y_pos": 221,
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"y_pos": 220,
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"description": "Run notebook file"
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}
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},
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"runtime": "Data Science Pipelines",
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"pipeline_defaults": {
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"kubernetes_shared_mem_size": {},
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"kubernetes_tolerations": [],
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"kubernetes_pod_labels": [],
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"mounted_volumes": [],
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"kubernetes_tolerations": [],
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"kubernetes_pod_annotations": [],
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"kubernetes_pod_labels": [],
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"env_vars": [],
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"kubernetes_secrets": [],
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"runtime_image": "quay.io/modh/runtime-images@sha256:ba76fd74b7595329a23f710485a7701caa0a7b495e60c89a23d5338ca13cf2e2"
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"env_vars": [],
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"runtime_image": "quay.io/modh/runtime-images@sha256:4c3098b7a369b8dad113be97f35ea202dde0a03d3d08a2c010e3b81209b39735"
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}
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}
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},
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"runtime_ref": ""
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}
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],
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"schemas": []
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}
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}

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