build new iris model as gs://seldon-models/v1.10.0-dev/sklearn/iris (and moviesentiment)

README.md

@@ -60,7 +60,7 @@ We provide optimized model servers for some of the most popular Deep Learning an
 You only have to upload your model binaries into your preferred object store, in this case we have a trained scikit-learn iris model in a Google bucket:
 
 ```console
-gs://seldon-models/sklearn/iris/model.joblib
+gs://seldon-models/v1.10.0-dev/sklearn/iris/model.joblib
 ```
 
 Create a namespace to run your model in:
@@ -83,7 +83,7 @@ spec:
   predictors:
   - graph:
       implementation: SKLEARN_SERVER
-      modelUri: gs://seldon-models/sklearn/iris
+      modelUri: gs://seldon-models/v1.10.0-dev/sklearn/iris
       name: classifier
     name: default
     replicas: 1

doc/source/graph/protocols.md

@@ -66,7 +66,7 @@ spec:
   - graph:
       children: []
       implementation: SKLEARN_SERVER
-      modelUri: gs://seldon-models/sklearn/iris
+      modelUri: gs://seldon-models/v1.10.0-dev/sklearn/iris
       name: classifier
       parameters:
         - name: method

doc/source/rollouts/abtests.md

@@ -46,7 +46,7 @@ spec:
     traffic: 100    
     graph:
       name: classifier
-      modelUri: gs://seldon-models/sklearn/iris
+      modelUri: gs://seldon-models/v1.10.0-dev/sklearn/iris
       implementation: SKLEARN_SERVER
   - name: candidate
     traffic: 0
@@ -360,7 +360,7 @@ spec:
   - name: default
     graph:
       name: classifier
-      modelUri: gs://seldon-models/sklearn/iris
+      modelUri: gs://seldon-models/v1.10.0-dev/sklearn/iris
       implementation: SKLEARN_SERVER
 ```
 

doc/source/servers/kfserving-storage-initializer.md

@@ -175,7 +175,7 @@ spec:
   - graph:
       children: []
       implementation: SKLEARN_SERVER
-      modelUri: gs://seldon-models/sklearn/iris
+      modelUri: gs://seldon-models/v1.10.0-dev/sklearn/iris
       serviceAccountName: user-gcp-sa
       name: classifier
     name: default

doc/source/servers/overview.md

@@ -22,7 +22,7 @@ spec:
       graph:
         name: classifier
         implementation: SKLEARN_SERVER
-        modelUri: gs://seldon-models/sklearn/iris
+        modelUri: gs://seldon-models/v1.10.0-dev/sklearn/iris
 ```
 
 By default only public models published to Google Cloud Storage will be accessible.
@@ -162,7 +162,7 @@ spec:
     graph:
       name: classifier
       implementation: SKLEARN_SERVER
-      modelUri: gs://seldon-models/sklearn/iris
+      modelUri: gs://seldon-models/v1.10.0-dev/sklearn/iris
 ```
 
 The image name and other details will be added when this is deployed automatically.

doc/source/servers/sklearn.md

@@ -40,7 +40,7 @@ spec:
   - graph:
       children: []
       implementation: SKLEARN_SERVER
-      modelUri: gs://seldon-models/sklearn/iris
+      modelUri: gs://seldon-models/v1.10.0-dev/sklearn/iris
       name: classifier
     name: default
     replicas: 1
@@ -68,7 +68,7 @@ spec:
   - graph:
       children: []
       implementation: SKLEARN_SERVER
-      modelUri: gs://seldon-models/sklearn/iris
+      modelUri: gs://seldon-models/v1.10.0-dev/sklearn/iris
       name: classifier
       parameters:
         - name: method
@@ -111,7 +111,7 @@ spec:
   - graph:
       children: []
       implementation: SKLEARN_SERVER
-      modelUri: gs://seldon-models/sklearn/iris
+      modelUri: gs://seldon-models/v1.10.0-dev/sklearn/iris
       name: classifier
       parameters:
         - name: method
@@ -159,7 +159,7 @@ spec:
     graph:
       children: []
       implementation: SKLEARN_SERVER
-      modelUri: gs://seldon-models/sklearn/iris
+      modelUri: gs://seldon-models/v1.10.0-dev/sklearn/iris
       name: classifier
     name: default
     replicas: 1

doc/source/workflow/quickstart.md

@@ -70,9 +70,9 @@ Export your model binaries using the instructions provided in the requirements o
 
 ```python
 >>my_sklearn_model.train(...)
->>pickle.dumps(my_sklearn_model, "model.pickle")
+>>joblib.dump(my_sklearn_model, "model.joblib")
 
-[Created file at /mypath/model.pickle]
+[Created file at /mypath/model.joblib]
 ```
 
 **2. Upload your model to an object store**
@@ -82,9 +82,9 @@ You can upload your models into any of the object stores supported by our pre-pa
 For simplicity we have already uploaded it to the bucket so you can just proceed to the next step and run your model on Seldon Core.
 
 ```console
-$ gsutil cp model.pickle gs://seldon-models/sklearn/iris/model.pickle
+$ gsutil cp model.joblib gs://seldon-models/v1.10.0-dev/sklearn/iris/model.joblib
 
-[ Saved into gs://seldon-models/sklearn/iris/model.pickle ]
+[ Saved into gs://seldon-models/v1.10.0-dev/sklearn/iris/model.joblib ]
 ```
 
 **3. Deploy to Seldon Core in Kubernetes**
@@ -103,7 +103,7 @@ spec:
   predictors:
   - graph:
       implementation: SKLEARN_SERVER
-      modelUri: gs://seldon-models/sklearn/iris
+      modelUri: gs://seldon-models/v1.10.0-dev/sklearn/iris
       name: classifier
     name: default
     replicas: 1
@@ -156,9 +156,9 @@ In this case we are also exporting the model binaries/artifacts, but we will be
 
 ```python
 >> my_sklearn_model.train(...)
->> pickle.dumps(my_sklearn_model, "model.pickle")
+>> joblib.dump(my_sklearn_model, "model.joblib")
 
-[Created file at /mypath/model.pickle]
+[Created file at /mypath/model.joblib]
 ```
 
 **2. Create a wrapper class Model.py**
@@ -170,7 +170,7 @@ The python SDK also allows for other functions such as `load` for loading logic,
 ```python
 class Model:
     def __init__(self):
-        self._model = pickle.loads("model.pickle")
+        self._model = joblib.load("model.joblib")
 
     def predict(self, X):
         output = self._model(X)

examples/batch/argo-workflows-batch/helm-charts/seldon-batch-workflow/values.yaml

@@ -19,7 +19,7 @@ seldonDeployment:
   # Prepackaged model server to use [see https://docs.seldon.io/projects/seldon-core/en/latest/servers/overview.html]
   server: SKLEARN_SERVER
   # The URL for the model that is to be used
-  modelUri: gs://seldon-models/sklearn/iris
+  modelUri: gs://seldon-models/v1.10.0-dev/sklearn/iris
   # The number of seldon deployment replicas to launch
   replicas: 2
   # Waiting time before checks for deployment to ensure kubernetes cluster registers create

examples/batch/hdfs-argo-workflows/deployment.yaml

@@ -9,7 +9,7 @@ spec:
   - graph:
       children: []
       implementation: SKLEARN_SERVER
-      modelUri: gs://seldon-models/sklearn/iris
+      modelUri: gs://seldon-models/v1.10.0-dev/sklearn/iris
       name: classifier
       logger:
         mode: all

examples/batch/hdfs-argo-workflows/hdfs-batch.ipynb

@@ -237,7 +237,7 @@
     "  - graph:\n",
     "      children: []\n",
     "      implementation: SKLEARN_SERVER\n",
-    "      modelUri: gs://seldon-models/sklearn/iris\n",
+    "      modelUri: gs://seldon-models/v1.10.0-dev/sklearn/iris\n",
     "      name: classifier\n",
     "      logger:\n",
     "        mode: all\n",

examples/batch/kubeflow-pipelines-batch/README.ipynb

@@ -222,7 +222,7 @@
     "def nlp_pipeline(\n",
     "        namespace=\"kubeflow\",\n",
     "        seldon_server=\"SKLEARN_SERVER\",\n",
-    "        model_path=\"gs://seldon-models/sklearn/iris\",\n",
+    "        model_path=\"gs://seldon-models/v1.10.0-dev/sklearn/iris\",\n",
     "        gateway_endpoint=\"istio-ingressgateway.istio-system.svc.cluster.local\",\n",
     "        retries=3,\n",
     "        replicas=10,\n",

examples/batch/kubeflow-pipelines-batch/README.md

@@ -126,7 +126,7 @@ from kubernetes import client as k8s
 def nlp_pipeline(
         namespace="kubeflow",
         seldon_server="SKLEARN_SERVER",
-        model_path="gs://seldon-models/sklearn/iris",
+        model_path="gs://seldon-models/v1.10.0-dev/sklearn/iris",
         gateway_endpoint="istio-ingressgateway.istio-system.svc.cluster.local",
         retries=3,
         replicas=10,

examples/batch/kubeflow-pipelines-batch/assets/seldon-batch-pipeline.py

@@ -9,7 +9,7 @@
 def nlp_pipeline(
     namespace="kubeflow",
     seldon_server="SKLEARN_SERVER",
-    model_path="gs://seldon-models/sklearn/iris",
+    model_path="gs://seldon-models/v1.10.0-dev/sklearn/iris",
     gateway_endpoint="istio-ingressgateway.istio-system.svc.cluster.local",
     retries=3,
     replicas=10,

examples/feedback/feedback-metrics-server/README.ipynb

@@ -290,7 +290,7 @@
     "  - graph:\n",
     "      children: []\n",
     "      implementation: SKLEARN_SERVER\n",
-    "      modelUri: gs://seldon-models/sklearn/iris\n",
+    "      modelUri: gs://seldon-models/v1.10.0-dev/sklearn/iris\n",
     "      name: classifier\n",
     "      logger:\n",
     "        url: http://broker-ingress.knative-eventing.svc.cluster.local/seldon-logs/default\n",

examples/feedback/feedback-metrics-server/README.md

@@ -173,7 +173,7 @@ spec:
   - graph:
       children: []
       implementation: SKLEARN_SERVER
-      modelUri: gs://seldon-models/sklearn/iris
+      modelUri: gs://seldon-models/v1.10.0-dev/sklearn/iris
       name: classifier
       logger:
         url: http://broker-ingress.knative-eventing.svc.cluster.local/seldon-logs/default

examples/feedback/metrics-server/README.ipynb

@@ -111,7 +111,7 @@
     "  - graph:\n",
     "      children: []\n",
     "      implementation: SKLEARN_SERVER\n",
-    "      modelUri: gs://seldon-models/sklearn/iris\n",
+    "      modelUri: gs://seldon-models/v1.10.0-dev/sklearn/iris\n",
     "      name: classifier\n",
     "      logger:\n",
     "        url: http://seldon-multiclass-model-metrics.seldon.svc.cluster.local:80/\n",

examples/feedback/metrics-server/README.md

@@ -65,7 +65,7 @@ spec:
   - graph:
       children: []
       implementation: SKLEARN_SERVER
-      modelUri: gs://seldon-models/sklearn/iris
+      modelUri: gs://seldon-models/v1.10.0-dev/sklearn/iris
       name: classifier
       logger:
         url: http://seldon-multiclass-model-metrics.seldon.svc.cluster.local:80/

examples/init_containers/custom_init_container.ipynb

@@ -101,7 +101,7 @@
     "  predictors:\n",
     "  - graph:\n",
     "      implementation: SKLEARN_SERVER\n",
-    "      modelUri: gs://seldon-models/sklearn/iris\n",
+    "      modelUri: gs://seldon-models/v1.10.0-dev/sklearn/iris\n",
     "      envSecretRefName: seldon-init-container-secret      \n",
     "      name: classifier\n",
     "    name: default\n",
@@ -142,7 +142,7 @@
     "          image: gcr.io/kfserving/storage-initializer:v0.4.0\n",
     "          imagePullPolicy: IfNotPresent\n",
     "          args:\n",
-    "          - gs://seldon-models/sklearn/iris\n",
+    "          - gs://seldon-models/v1.10.0-dev/sklearn/iris\n",
     "          - /mnt/models\n",
     "\n",
     "          envFrom:\n",
@@ -163,7 +163,7 @@
     "    graph:\n",
     "      children: []\n",
     "      implementation: SKLEARN_SERVER\n",
-    "      modelUri: gs://seldon-models/sklearn/iris\n",
+    "      modelUri: gs://seldon-models/v1.10.0-dev/sklearn/iris\n",
     "      name: classifier\n",
     "    name: default\n",
     "    replicas: 1\n",

examples/iter8/progressive_rollout/separate_sdeps/abtest.ipynb

@@ -66,7 +66,7 @@
       "  - name: default\r\n",
       "    graph:\r\n",
       "      name: classifier\r\n",
-      "      modelUri: gs://seldon-models/sklearn/iris\r\n",
+      "      modelUri: gs://seldon-models/v1.10.0-dev/sklearn/iris\n",
       "      implementation: SKLEARN_SERVER\r\n"
      ]
     }

examples/iter8/progressive_rollout/separate_sdeps/baseline.yaml

@@ -13,5 +13,5 @@ spec:
   - name: default
     graph:
       name: classifier
-      modelUri: gs://seldon-models/sklearn/iris
+      modelUri: gs://seldon-models/v1.10.0-dev/sklearn/iris
       implementation: SKLEARN_SERVER

examples/iter8/progressive_rollout/single_sdep/abtest.ipynb

@@ -68,7 +68,7 @@
       "    traffic: 100    \r\n",
       "    graph:\r\n",
       "      name: classifier\r\n",
-      "      modelUri: gs://seldon-models/sklearn/iris\r\n",
+      "      modelUri: gs://seldon-models/v1.10.0-dev/sklearn/iris\n",
       "      implementation: SKLEARN_SERVER\r\n",
       "  - name: candidate\r\n",
       "    traffic: 0\r\n",

examples/iter8/progressive_rollout/single_sdep/abtest.yaml

@@ -14,7 +14,7 @@ spec:
     traffic: 100    
     graph:
       name: classifier
-      modelUri: gs://seldon-models/sklearn/iris
+      modelUri: gs://seldon-models/v1.10.0-dev/sklearn/iris
       implementation: SKLEARN_SERVER
   - name: candidate
     traffic: 0

examples/iter8/progressive_rollout/single_sdep/promote-v1.yaml

@@ -8,5 +8,5 @@ spec:
   - name: default
     graph:
       name: classifier
-      modelUri: gs://seldon-models/sklearn/iris
+      modelUri: gs://seldon-models/v1.10.0-dev/sklearn/iris
       implementation: SKLEARN_SERVER

examples/security/ssl_requests/README.ipynb

@@ -235,7 +235,7 @@
     "  - graph:\n",
     "      children: []\n",
     "      implementation: SKLEARN_SERVER\n",
-    "      modelUri: gs://seldon-models/sklearn/iris\n",
+    "      modelUri: gs://seldon-models/v1.10.0-dev/sklearn/iris\n",
     "      name: classifier\n",
     "    name: default\n",
     "    replicas: 1\n",
@@ -274,7 +274,7 @@
     "  - graph:\n",
     "      children: []\n",
     "      implementation: SKLEARN_SERVER\n",
-    "      modelUri: gs://seldon-models/sklearn/iris\n",
+    "      modelUri: gs://seldon-models/v1.10.0-dev/sklearn/iris\n",
     "      name: classifier\n",
     "    name: default\n",
     "    replicas: 1\n",
@@ -731,7 +731,7 @@
     "  - graph:\n",
     "      children: []\n",
     "      implementation: SKLEARN_SERVER\n",
-    "      modelUri: gs://seldon-models/sklearn/iris\n",
+    "      modelUri: gs://seldon-models/v1.10.0-dev/sklearn/iris\n",
     "      name: classifier\n",
     "    name: default\n",
     "    replicas: 1\n",

examples/security/ssl_requests/README.md

@@ -139,7 +139,7 @@ spec:
   - graph:
       children: []
       implementation: SKLEARN_SERVER
-      modelUri: gs://seldon-models/sklearn/iris
+      modelUri: gs://seldon-models/v1.10.0-dev/sklearn/iris
       name: classifier
     name: default
     replicas: 1
@@ -164,7 +164,7 @@ spec:
   - graph:
       children: []
       implementation: SKLEARN_SERVER
-      modelUri: gs://seldon-models/sklearn/iris
+      modelUri: gs://seldon-models/v1.10.0-dev/sklearn/iris
       name: classifier
     name: default
     replicas: 1
@@ -388,7 +388,7 @@ spec:
   - graph:
       children: []
       implementation: SKLEARN_SERVER
-      modelUri: gs://seldon-models/sklearn/iris
+      modelUri: gs://seldon-models/v1.10.0-dev/sklearn/iris
       name: classifier
     name: default
     replicas: 1

examples/streaming/knative-eventing/README.ipynb

@@ -58,7 +58,7 @@
     "  predictors:\n",
     "  - graph:\n",
     "      implementation: SKLEARN_SERVER\n",
-    "      modelUri: gs://seldon-models/sklearn/iris\n",
+    "      modelUri: gs://seldon-models/v1.10.0-dev/sklearn/iris\n",
     "      name: simple-iris-model\n",
     "      children: []\n",
     "    name: default\n",

examples/streaming/knative-eventing/README.md

@@ -29,7 +29,7 @@ spec:
   predictors:
   - graph:
       implementation: SKLEARN_SERVER
-      modelUri: gs://seldon-models/sklearn/iris
+      modelUri: gs://seldon-models/v1.10.0-dev/sklearn/iris
       name: simple-iris-model
       children: []
     name: default