Add ssl_verify_path for explainer TLS (#495)

* revert REQUESTS_CA_BUNDLE * add ssl_verify_path to mlserver explainer settings * MLServer dev7 update
SeldonIO · Oct 14, 2022 · feaf14d · feaf14d
1 parent e12f681
commit feaf14d
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Showing 23 changed files with 117 additions and 100 deletions.
diff --git a/docs/source/contents/getting-started/cli.md b/docs/source/contents/getting-started/cli.md
@@ -6,7 +6,7 @@ Seldon Core V2 can be managed via a CLI tool.
 
 Download from a recent release from https://github.com/SeldonIO/seldon-core-v2/releases.
 
-It is dynamically linked and will require and nix architetcure and glibc 2.25+.
+It is dynamically linked and will require and *nix architecture and glibc 2.25+.
 
 ```
 mv seldon-linux-amd64 seldon

diff --git a/k8s/Makefile b/k8s/Makefile
@@ -12,7 +12,7 @@ PIPELINEGATEWAY_IMG ?= ${DOCKERHUB_USERNAME}/seldon-pipelinegateway:${CUSTOM_IMA
 RCLONE_IMG ?= ${DOCKERHUB_USERNAME}/seldon-rclone:${CUSTOM_IMAGE_TAG}
 SCHEDULER_IMG ?= ${DOCKERHUB_USERNAME}/seldon-scheduler:${CUSTOM_IMAGE_TAG}
 
-MLSERVER_IMG ?= seldonio/mlserver:1.2.0.dev5
+MLSERVER_IMG ?= seldonio/mlserver:1.2.0.dev7
 TRITON_IMG ?= nvcr.io/nvidia/tritonserver:22.05-py3
 
 .PHONY: create

diff --git a/k8s/yaml/seldon-v2-components.yaml b/k8s/yaml/seldon-v2-components.yaml
@@ -1074,7 +1074,7 @@ spec:
         value: "1"
       - name: MLSERVER_LOAD_MODELS_AT_STARTUP
         value: "false"
-      image: seldonio/mlserver:1.2.0.dev5
+      image: seldonio/mlserver:1.2.0.dev7
       imagePullPolicy: IfNotPresent
       lifecycle:
         preStop:

diff --git a/operator/config/serverconfigs/kustomization.yaml b/operator/config/serverconfigs/kustomization.yaml
@@ -13,7 +13,7 @@ images:
   newTag: latest
 - name: mlserver
   newName: seldonio/mlserver
-  newTag: 1.2.0.dev5
+  newTag: 1.2.0.dev7
 - name: rclone
   newName: seldonio/seldon-rclone
   newTag: latest

diff --git a/samples/examples/income_classifier/.gitignore b/samples/examples/income_classifier/.gitignore
@@ -1,6 +1 @@
-classifier/
-preprocessor/
-drift-detector/
-outlier-detector/
-explainer/
 infer-data/
diff --git a/samples/examples/income_classifier/classifier/.gitignore b/samples/examples/income_classifier/classifier/.gitignore
@@ -0,0 +1 @@
+model.joblib
diff --git a/samples/examples/income_classifier/classifier/model-settings.json b/samples/examples/income_classifier/classifier/model-settings.json
@@ -0,0 +1,7 @@
+{
+    "name": "income",
+    "implementation": "mlserver_sklearn.SKLearnModel",
+    "parameters": {
+        "version": "v0.1.0"
+    }
+}
diff --git a/samples/examples/income_classifier/drift-detector/.gitignore b/samples/examples/income_classifier/drift-detector/.gitignore
@@ -0,0 +1,2 @@
+config.toml
+x_ref.npy
diff --git a/samples/examples/income_classifier/drift-detector/model-settings.json b/samples/examples/income_classifier/drift-detector/model-settings.json
@@ -0,0 +1,8 @@
+{
+  "name": "income-drift",
+  "implementation": "mlserver_alibi_detect.AlibiDetectRuntime",
+  "parameters": {
+    "uri": "./",
+    "version": "v0.1.0"
+  }
+}
diff --git a/samples/examples/income_classifier/explainer/.gitignore b/samples/examples/income_classifier/explainer/.gitignore
@@ -0,0 +1 @@
+data
diff --git a/samples/examples/income_classifier/explainer/model-settings.json b/samples/examples/income_classifier/explainer/model-settings.json
@@ -0,0 +1,9 @@
+{
+  "name": "anchor-tabular-income",
+  "implementation": "mlserver_alibi_explain.AlibiExplainRuntime",
+  "parallel_workers": 0,
+  "parameters": {
+    "uri": "./data",
+    "version": "v0.1.0"
+  }
+}
diff --git a/samples/examples/income_classifier/infer.ipynb b/samples/examples/income_classifier/infer.ipynb
@@ -257,7 +257,7 @@
       "    {\r\n",
       "      \"pipeline\": {\r\n",
       "        \"name\": \"income-production\",\r\n",
-      "        \"uid\": \"ccss58q4u1vus3q1e1ig\",\r\n",
+      "        \"uid\": \"cd4lg2qivs0nm83cjb60\",\r\n",
       "        \"version\": 1,\r\n",
       "        \"steps\": [\r\n",
       "          {\r\n",
@@ -291,7 +291,7 @@
       "        \"pipelineVersion\": 1,\r\n",
       "        \"status\": \"PipelineReady\",\r\n",
       "        \"reason\": \"created pipeline\",\r\n",
-      "        \"lastChangeTimestamp\": \"2022-10-02T16:56:03.396751091Z\"\r\n",
+      "        \"lastChangeTimestamp\": \"2022-10-14T12:37:32.526902569Z\"\r\n",
       "      }\r\n",
       "    }\r\n",
       "  ]\r\n",
@@ -343,7 +343,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "seldon.default.model.income-drift.outputs\tccss59patu79k6fs0pjg\t{\"name\":\"is_drift\",\"datatype\":\"INT64\",\"shape\":[\"1\"],\"contents\":{\"int64Contents\":[\"0\"]}}\r\n"
+      "seldon.default.model.income-drift.outputs\tcd4lg40n3m56u1qgegr0\t{\"name\":\"is_drift\",\"datatype\":\"INT64\",\"shape\":[\"1\"],\"contents\":{\"int64Contents\":[\"0\"]}}\r\n"
      ]
     }
    ],
@@ -391,7 +391,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "seldon.default.model.income-drift.outputs\tccss5dpatu79k6fs0pk0\t{\"name\":\"is_drift\",\"datatype\":\"INT64\",\"shape\":[\"1\"],\"contents\":{\"int64Contents\":[\"1\"]}}\r\n"
+      "seldon.default.model.income-drift.outputs\tcd4lg6on3m56u1qgegrg\t{\"name\":\"is_drift\",\"datatype\":\"INT64\",\"shape\":[\"1\"],\"contents\":{\"int64Contents\":[\"1\"]}}\r\n"
      ]
     }
    ],
@@ -419,7 +419,7 @@
      "text": [
       "[0 0 1 1 0 1 0 0 1 0 0 0 0 0 1 1 0 0 0 1]\n",
       "<Response [200]>\n",
-      "{'model_name': '', 'outputs': [{'data': [0, 0, 1, 1, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 1, 1, 0, 0, 0, 1], 'name': 'predict', 'shape': [20], 'datatype': 'INT64'}, {'data': [1, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 1, 1, 0, 1, 1], 'name': 'is_outlier', 'shape': [1, 20], 'datatype': 'INT64'}]}\n"
+      "{'model_name': '', 'outputs': [{'data': [0, 0, 1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 1], 'name': 'predict', 'shape': [20], 'datatype': 'INT64'}, {'data': [1, 1, 0, 0, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 1, 1, 0, 1, 0, 1], 'name': 'is_outlier', 'shape': [1, 20], 'datatype': 'INT64'}]}\n"
      ]
     }
    ],
@@ -439,7 +439,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "seldon.default.model.income-drift.outputs\tccss5ghatu79k6fs0pkg\t{\"name\":\"is_drift\",\"datatype\":\"INT64\",\"shape\":[\"1\"],\"contents\":{\"int64Contents\":[\"0\"]}}\r\n"
+      "seldon.default.model.income-drift.outputs\tcd4lg88n3m56u1qgegs0\t{\"name\":\"is_drift\",\"datatype\":\"INT64\",\"shape\":[\"1\"],\"contents\":{\"int64Contents\":[\"0\"]}}\r\n"
      ]
     }
    ],
@@ -529,7 +529,7 @@
      "text": [
       "[0]\n",
       "<Response [200]>\n",
-      "{'model_name': 'income-explainer_1', 'model_version': '1', 'id': '4e5362b0-e2c7-41e0-82d5-f1a240f60834', 'parameters': {'content_type': None, 'headers': None}, 'outputs': [{'name': 'explanation', 'shape': [1], 'datatype': 'BYTES', 'parameters': {'content_type': 'str', 'headers': None}, 'data': ['{\"meta\": {\"name\": \"AnchorTabular\", \"type\": [\"blackbox\"], \"explanations\": [\"local\"], \"params\": {\"seed\": 1, \"disc_perc\": [25, 50, 75], \"threshold\": 0.95, \"delta\": 0.1, \"tau\": 0.15, \"batch_size\": 100, \"coverage_samples\": 10000, \"beam_size\": 1, \"stop_on_first\": false, \"max_anchor_size\": null, \"min_samples_start\": 100, \"n_covered_ex\": 10, \"binary_cache_size\": 10000, \"cache_margin\": 1000, \"verbose\": false, \"verbose_every\": 1, \"kwargs\": {}}, \"version\": \"0.7.0\"}, \"data\": {\"anchor\": [\"Marital Status = Never-Married\", \"Relationship = Own-child\"], \"precision\": 1.0, \"coverage\": 0.07165109034267912, \"raw\": {\"feature\": [3, 5], \"mean\": [0.8044052863436123, 1.0], \"precision\": [0.8044052863436123, 1.0], \"coverage\": [0.3037383177570093, 0.07165109034267912], \"examples\": [{\"covered_true\": [[24, 4, 1, 1, 6, 3, 4, 1, 0, 0, 40, 9], [31, 4, 1, 1, 8, 1, 4, 1, 0, 0, 40, 9], [28, 4, 1, 1, 8, 1, 4, 0, 0, 0, 50, 9], [49, 4, 5, 1, 5, 1, 4, 1, 0, 0, 60, 9], [24, 0, 1, 1, 0, 1, 1, 1, 0, 0, 25, 2], [41, 4, 5, 1, 1, 1, 4, 0, 0, 0, 40, 9], [34, 1, 1, 1, 8, 4, 1, 1, 1471, 0, 40, 7], [61, 4, 1, 1, 1, 1, 4, 1, 0, 0, 40, 9], [55, 5, 1, 1, 6, 0, 4, 1, 0, 0, 60, 9], [26, 4, 5, 1, 5, 0, 4, 1, 0, 0, 20, 9]], \"covered_false\": [[47, 2, 5, 1, 5, 1, 4, 1, 0, 0, 35, 9], [30, 4, 1, 1, 8, 4, 4, 0, 0, 0, 45, 9], [49, 7, 2, 1, 8, 1, 4, 0, 0, 2258, 50, 9], [59, 1, 5, 1, 5, 1, 4, 0, 0, 0, 40, 0], [42, 4, 1, 1, 8, 0, 4, 1, 5178, 0, 40, 9], [36, 4, 5, 1, 6, 0, 4, 1, 15024, 0, 45, 9], [33, 4, 1, 1, 5, 0, 4, 1, 15024, 0, 75, 9], [40, 4, 1, 1, 6, 1, 3, 0, 0, 0, 55, 9], [32, 4, 1, 1, 6, 0, 4, 1, 99999, 0, 50, 9], [30, 4, 1, 1, 4, 1, 4, 0, 0, 0, 40, 9]], \"uncovered_true\": [], \"uncovered_false\": []}, {\"covered_true\": [[37, 4, 5, 1, 5, 3, 4, 1, 0, 0, 48, 9], [28, 4, 1, 1, 4, 3, 4, 0, 0, 0, 40, 9], [64, 0, 1, 1, 0, 3, 2, 0, 0, 0, 8, 9], [69, 4, 2, 1, 5, 3, 4, 1, 0, 0, 40, 2], [48, 7, 5, 1, 5, 3, 4, 1, 0, 0, 40, 9], [45, 4, 1, 1, 5, 3, 4, 0, 0, 0, 50, 9], [59, 0, 1, 1, 0, 3, 4, 1, 0, 0, 40, 9], [55, 5, 5, 1, 8, 3, 4, 1, 0, 0, 60, 9], [43, 4, 1, 1, 6, 3, 4, 1, 0, 0, 44, 9], [36, 4, 1, 1, 8, 3, 4, 1, 0, 0, 55, 9]], \"covered_false\": [[26, 4, 1, 1, 5, 3, 4, 1, 10520, 0, 64, 9], [49, 7, 5, 1, 5, 3, 2, 0, 7430, 0, 40, 9], [62, 4, 2, 1, 5, 3, 4, 1, 15024, 0, 50, 9], [63, 6, 1, 1, 6, 3, 4, 1, 10605, 0, 40, 9], [41, 4, 1, 1, 6, 3, 4, 1, 15024, 0, 45, 9], [39, 4, 1, 1, 8, 3, 4, 1, 15024, 0, 60, 9], [44, 4, 5, 1, 5, 3, 4, 1, 7688, 0, 55, 9], [46, 4, 5, 1, 5, 3, 4, 0, 7688, 0, 35, 9], [32, 4, 1, 1, 8, 3, 4, 1, 7298, 0, 45, 9], [51, 5, 5, 1, 8, 3, 4, 1, 15024, 0, 50, 9]], \"uncovered_true\": [], \"uncovered_false\": []}], \"all_precision\": 0, \"num_preds\": 1000000, \"success\": true, \"names\": [\"Marital Status = Never-Married\", \"Relationship = Own-child\"], \"prediction\": [0], \"instance\": [47.0, 4.0, 1.0, 1.0, 1.0, 3.0, 4.0, 1.0, 0.0, 0.0, 40.0, 9.0], \"instances\": [[47.0, 4.0, 1.0, 1.0, 1.0, 3.0, 4.0, 1.0, 0.0, 0.0, 40.0, 9.0]]}}}']}]}\n"
+      "{'model_name': 'income-explainer_1', 'model_version': '1', 'id': 'a1e804a6-8716-4aa6-bd36-51917b259a60', 'parameters': {'content_type': None, 'headers': None}, 'outputs': [{'name': 'explanation', 'shape': [1], 'datatype': 'BYTES', 'parameters': {'content_type': 'str', 'headers': None}, 'data': ['{\"meta\": {\"name\": \"AnchorTabular\", \"type\": [\"blackbox\"], \"explanations\": [\"local\"], \"params\": {\"seed\": 1, \"disc_perc\": [25, 50, 75], \"threshold\": 0.95, \"delta\": 0.1, \"tau\": 0.15, \"batch_size\": 100, \"coverage_samples\": 10000, \"beam_size\": 1, \"stop_on_first\": false, \"max_anchor_size\": null, \"min_samples_start\": 100, \"n_covered_ex\": 10, \"binary_cache_size\": 10000, \"cache_margin\": 1000, \"verbose\": false, \"verbose_every\": 1, \"kwargs\": {}}, \"version\": \"0.8.0\"}, \"data\": {\"anchor\": [\"Marital Status = Never-Married\", \"Relationship = Own-child\"], \"precision\": 1.0, \"coverage\": 0.07165109034267912, \"raw\": {\"feature\": [3, 5], \"mean\": [0.8040345821325648, 1.0], \"precision\": [0.8040345821325648, 1.0], \"coverage\": [0.3037383177570093, 0.07165109034267912], \"examples\": [{\"covered_true\": [[42, 0, 5, 1, 0, 0, 4, 1, 0, 0, 50, 9], [35, 4, 1, 1, 7, 1, 4, 1, 0, 0, 37, 9], [46, 7, 5, 1, 4, 4, 4, 1, 0, 0, 40, 9], [27, 4, 1, 1, 2, 1, 2, 1, 0, 0, 40, 9], [45, 2, 5, 1, 5, 1, 4, 0, 0, 0, 30, 9], [67, 4, 1, 1, 4, 0, 4, 1, 6514, 0, 7, 9], [43, 4, 1, 1, 2, 0, 4, 1, 0, 0, 48, 9], [35, 4, 1, 1, 6, 5, 4, 0, 0, 0, 30, 9], [46, 4, 1, 1, 5, 0, 4, 1, 0, 1848, 45, 9], [27, 0, 1, 1, 0, 4, 1, 1, 0, 0, 25, 7]], \"covered_false\": [[39, 5, 1, 1, 8, 0, 4, 1, 0, 0, 60, 9], [47, 4, 1, 1, 6, 1, 4, 1, 0, 0, 45, 9], [46, 2, 1, 1, 1, 1, 4, 0, 99999, 0, 40, 9], [36, 5, 1, 1, 6, 0, 4, 1, 15024, 0, 45, 9], [39, 4, 5, 1, 8, 0, 4, 1, 0, 0, 50, 9], [49, 4, 1, 1, 8, 0, 4, 1, 0, 0, 45, 9], [49, 4, 1, 1, 8, 1, 4, 1, 0, 0, 40, 9], [58, 4, 1, 1, 8, 0, 4, 1, 7688, 0, 50, 9], [52, 5, 2, 1, 5, 0, 4, 1, 99999, 0, 65, 9], [62, 4, 1, 1, 8, 1, 4, 1, 10520, 0, 50, 9]], \"uncovered_true\": [], \"uncovered_false\": []}, {\"covered_true\": [[31, 4, 1, 1, 5, 3, 4, 1, 0, 0, 40, 9], [28, 4, 1, 1, 1, 3, 4, 1, 0, 0, 45, 9], [27, 7, 5, 1, 5, 3, 4, 1, 0, 0, 40, 9], [37, 4, 5, 1, 8, 3, 4, 1, 0, 0, 40, 9], [45, 4, 2, 1, 5, 3, 1, 1, 0, 0, 45, 2], [46, 4, 1, 1, 7, 3, 4, 1, 0, 0, 40, 9], [62, 7, 1, 1, 1, 3, 4, 1, 0, 0, 38, 9], [34, 4, 5, 1, 5, 3, 1, 1, 0, 0, 43, 1], [37, 5, 5, 1, 8, 3, 4, 1, 0, 0, 70, 9], [56, 4, 1, 1, 5, 3, 4, 1, 0, 0, 40, 9]], \"covered_false\": [[33, 4, 5, 1, 5, 3, 4, 1, 15024, 0, 44, 9], [40, 1, 1, 1, 5, 3, 4, 1, 7688, 0, 66, 9], [36, 4, 1, 1, 8, 3, 4, 1, 27828, 0, 40, 9], [55, 5, 1, 1, 8, 3, 4, 1, 0, 2415, 50, 9], [54, 5, 1, 1, 8, 3, 4, 1, 7688, 0, 40, 0], [27, 4, 1, 1, 5, 3, 1, 1, 13550, 0, 40, 9], [48, 4, 1, 1, 4, 3, 4, 0, 99999, 0, 40, 9], [55, 4, 5, 1, 5, 3, 4, 1, 15024, 0, 50, 0], [66, 4, 1, 1, 6, 3, 4, 1, 20051, 0, 40, 9], [35, 4, 1, 1, 2, 3, 4, 1, 7298, 0, 35, 9]], \"uncovered_true\": [], \"uncovered_false\": []}], \"all_precision\": 0, \"num_preds\": 1000000, \"success\": true, \"names\": [\"Marital Status = Never-Married\", \"Relationship = Own-child\"], \"prediction\": [0], \"instance\": [47.0, 4.0, 1.0, 1.0, 1.0, 3.0, 4.0, 1.0, 0.0, 0.0, 40.0, 9.0], \"instances\": [[47.0, 4.0, 1.0, 1.0, 1.0, 3.0, 4.0, 1.0, 0.0, 0.0, 40.0, 9.0]]}}}']}]}\n"
      ]
     }
    ],
@@ -549,7 +549,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 53,
+   "execution_count": 21,
    "id": "a2d69d25",
    "metadata": {},
    "outputs": [

diff --git a/samples/examples/income_classifier/outlier-detector/.gitignore b/samples/examples/income_classifier/outlier-detector/.gitignore
@@ -0,0 +1,3 @@
+meta.dill
+model
+OutlierVAE.dill
diff --git a/samples/examples/income_classifier/outlier-detector/model-settings.json b/samples/examples/income_classifier/outlier-detector/model-settings.json
@@ -0,0 +1,8 @@
+{
+  "name": "income-drift",
+  "implementation": "mlserver_alibi_detect.AlibiDetectRuntime",
+  "parameters": {
+    "uri": "./",
+    "version": "v0.1.0"
+  }
+}
diff --git a/samples/examples/income_classifier/preprocessor/.gitignore b/samples/examples/income_classifier/preprocessor/.gitignore
@@ -0,0 +1 @@
+model.joblib
diff --git a/samples/examples/income_classifier/preprocessor/model-settings.json b/samples/examples/income_classifier/preprocessor/model-settings.json
@@ -0,0 +1,10 @@
+{
+    "name": "income-preprocess",
+    "implementation": "mlserver_sklearn.SKLearnModel",
+    "parameters": {
+        "version": "v0.1.0",
+	"extra": {
+	    "predict_fn": "transform"
+	}
+    }
+}
diff --git a/samples/examples/income_classifier/requirements.txt b/samples/examples/income_classifier/requirements.txt
@@ -1,3 +1,3 @@
-alibi==0.7.0
+alibi==0.8.0
 alibi-detect==0.10.0
 scikit-learn==1.1.2