Bumping version for 0.11.1 (kserve#3141)

* Bumping version for 0.11.1 Signed-off-by: Rachit Chauhan <[email protected]> * add back kustomize * Update VERSION --------- Signed-off-by: Rachit Chauhan <[email protected]> Co-authored-by: Dan Sun <[email protected]>
Jooho · Sep 22, 2023 · 52b8804 · 52b8804
1 parent a6af401
commit 52b8804
Show file tree

Hide file tree

Showing 32 changed files with 43,489 additions and 49 deletions.
diff --git a/charts/kserve-crd/Chart.yaml b/charts/kserve-crd/Chart.yaml
@@ -1,6 +1,6 @@
 apiVersion: v1
 name: kserve-crd
-version: v0.11.0
+version: v0.11.1
 description: Helm chart for deploying kserve crds 
 keywords:
   - kserve

diff --git a/charts/kserve-crd/templates/serving.kserve.io_inferencegraphs.yaml b/charts/kserve-crd/templates/serving.kserve.io_inferencegraphs.yaml
@@ -420,6 +420,11 @@ spec:
                             type: string
                           data:
                             type: string
+                          dependency:
+                            enum:
+                            - Soft
+                            - Hard
+                            type: string
                           name:
                             type: string
                           nodeName:

diff --git a/charts/kserve-resources/Chart.yaml b/charts/kserve-resources/Chart.yaml
@@ -1,6 +1,6 @@
 apiVersion: v1
 name: kserve 
-version: v0.11.0
+version: v0.11.1
 description: Helm chart for deploying kserve resources
 keywords:
   - kserve

diff --git a/charts/kserve-resources/values.yaml b/charts/kserve-resources/values.yaml
@@ -1,5 +1,5 @@
 kserve:
-  version: &defaultVersion v0.11.0
+  version: &defaultVersion v0.11.1
   modelmeshVersion: &defaultModelMeshVersion v0.11.0
   agent:
     image: kserve/agent

diff --git a/hack/generate-install.sh b/hack/generate-install.sh
@@ -49,6 +49,7 @@ RELEASES=(
     "v0.11.0-rc0"
     "v0.11.0-rc1"
     "v0.11.0"
+    "v0.11.1"
 )
 
 TAG=$1

diff --git a/hack/quick_install.sh b/hack/quick_install.sh
@@ -33,7 +33,7 @@ done
 export ISTIO_VERSION=1.17.2
 export KNATIVE_SERVING_VERSION=knative-v1.10.1
 export KNATIVE_ISTIO_VERSION=knative-v1.10.0
-export KSERVE_VERSION=v0.11.0
+export KSERVE_VERSION=v0.11.1
 export CERT_MANAGER_VERSION=v1.3.0
 export SCRIPT_DIR="$( dirname -- "${BASH_SOURCE[0]}" )"
 

diff --git a/install/v0.11.1/kserve-runtimes.yaml b/install/v0.11.1/kserve-runtimes.yaml
@@ -0,0 +1,338 @@
+apiVersion: serving.kserve.io/v1alpha1
+kind: ClusterServingRuntime
+metadata:
+  name: kserve-lgbserver
+spec:
+  annotations:
+    prometheus.kserve.io/path: /metrics
+    prometheus.kserve.io/port: "8080"
+  containers:
+  - args:
+    - --model_name={{.Name}}
+    - --model_dir=/mnt/models
+    - --http_port=8080
+    - --nthread=1
+    image: kserve/lgbserver:v0.11.1
+    name: kserve-container
+    resources:
+      limits:
+        cpu: "1"
+        memory: 2Gi
+      requests:
+        cpu: "1"
+        memory: 2Gi
+  protocolVersions:
+  - v1
+  - v2
+  supportedModelFormats:
+  - autoSelect: true
+    name: lightgbm
+    priority: 1
+    version: "3"
+---
+apiVersion: serving.kserve.io/v1alpha1
+kind: ClusterServingRuntime
+metadata:
+  name: kserve-mlserver
+spec:
+  annotations:
+    prometheus.kserve.io/path: /metrics
+    prometheus.kserve.io/port: "8080"
+  containers:
+  - env:
+    - name: MLSERVER_MODEL_IMPLEMENTATION
+      value: '{{.Labels.modelClass}}'
+    - name: MLSERVER_HTTP_PORT
+      value: "8080"
+    - name: MLSERVER_GRPC_PORT
+      value: "9000"
+    - name: MODELS_DIR
+      value: /mnt/models
+    image: docker.io/seldonio/mlserver:1.3.2
+    name: kserve-container
+    resources:
+      limits:
+        cpu: "1"
+        memory: 2Gi
+      requests:
+        cpu: "1"
+        memory: 2Gi
+  protocolVersions:
+  - v2
+  supportedModelFormats:
+  - autoSelect: true
+    name: sklearn
+    priority: 1
+    version: "0"
+  - autoSelect: true
+    name: sklearn
+    priority: 2
+    version: "1"
+  - autoSelect: true
+    name: xgboost
+    priority: 2
+    version: "1"
+  - autoSelect: true
+    name: lightgbm
+    priority: 2
+    version: "3"
+  - autoSelect: true
+    name: mlflow
+    priority: 1
+    version: "1"
+---
+apiVersion: serving.kserve.io/v1alpha1
+kind: ClusterServingRuntime
+metadata:
+  name: kserve-paddleserver
+spec:
+  annotations:
+    prometheus.kserve.io/path: /metrics
+    prometheus.kserve.io/port: "8080"
+  containers:
+  - args:
+    - --model_name={{.Name}}
+    - --model_dir=/mnt/models
+    - --http_port=8080
+    image: kserve/paddleserver:v0.11.1
+    name: kserve-container
+    resources:
+      limits:
+        cpu: "1"
+        memory: 2Gi
+      requests:
+        cpu: "1"
+        memory: 2Gi
+  protocolVersions:
+  - v1
+  - v2
+  supportedModelFormats:
+  - autoSelect: true
+    name: paddle
+    priority: 1
+    version: "2"
+---
+apiVersion: serving.kserve.io/v1alpha1
+kind: ClusterServingRuntime
+metadata:
+  name: kserve-pmmlserver
+spec:
+  annotations:
+    prometheus.kserve.io/path: /metrics
+    prometheus.kserve.io/port: "8080"
+  containers:
+  - args:
+    - --model_name={{.Name}}
+    - --model_dir=/mnt/models
+    - --http_port=8080
+    image: kserve/pmmlserver:v0.11.1
+    name: kserve-container
+    resources:
+      limits:
+        cpu: "1"
+        memory: 2Gi
+      requests:
+        cpu: "1"
+        memory: 2Gi
+  protocolVersions:
+  - v1
+  - v2
+  supportedModelFormats:
+  - autoSelect: true
+    name: pmml
+    priority: 1
+    version: "3"
+  - autoSelect: true
+    name: pmml
+    priority: 1
+    version: "4"
+---
+apiVersion: serving.kserve.io/v1alpha1
+kind: ClusterServingRuntime
+metadata:
+  name: kserve-sklearnserver
+spec:
+  annotations:
+    prometheus.kserve.io/path: /metrics
+    prometheus.kserve.io/port: "8080"
+  containers:
+  - args:
+    - --model_name={{.Name}}
+    - --model_dir=/mnt/models
+    - --http_port=8080
+    image: kserve/sklearnserver:v0.11.1
+    name: kserve-container
+    resources:
+      limits:
+        cpu: "1"
+        memory: 2Gi
+      requests:
+        cpu: "1"
+        memory: 2Gi
+  protocolVersions:
+  - v1
+  - v2
+  supportedModelFormats:
+  - autoSelect: true
+    name: sklearn
+    priority: 1
+    version: "1"
+---
+apiVersion: serving.kserve.io/v1alpha1
+kind: ClusterServingRuntime
+metadata:
+  name: kserve-tensorflow-serving
+spec:
+  annotations:
+    prometheus.kserve.io/path: /metrics
+    prometheus.kserve.io/port: "8080"
+  containers:
+  - args:
+    - --model_name={{.Name}}
+    - --port=9000
+    - --rest_api_port=8080
+    - --model_base_path=/mnt/models
+    - --rest_api_timeout_in_ms=60000
+    command:
+    - /usr/bin/tensorflow_model_server
+    image: tensorflow/serving:2.6.2
+    name: kserve-container
+    resources:
+      limits:
+        cpu: "1"
+        memory: 2Gi
+      requests:
+        cpu: "1"
+        memory: 2Gi
+  protocolVersions:
+  - v1
+  - grpc-v1
+  supportedModelFormats:
+  - autoSelect: true
+    name: tensorflow
+    priority: 2
+    version: "1"
+  - autoSelect: true
+    name: tensorflow
+    priority: 2
+    version: "2"
+---
+apiVersion: serving.kserve.io/v1alpha1
+kind: ClusterServingRuntime
+metadata:
+  name: kserve-torchserve
+spec:
+  annotations:
+    prometheus.kserve.io/path: /metrics
+    prometheus.kserve.io/port: "8082"
+  containers:
+  - args:
+    - torchserve
+    - --start
+    - --model-store=/mnt/models/model-store
+    - --ts-config=/mnt/models/config/config.properties
+    env:
+    - name: TS_SERVICE_ENVELOPE
+      value: '{{.Labels.serviceEnvelope}}'
+    image: pytorch/torchserve-kfs:0.8.2
+    name: kserve-container
+    resources:
+      limits:
+        cpu: "1"
+        memory: 2Gi
+      requests:
+        cpu: "1"
+        memory: 2Gi
+  protocolVersions:
+  - v1
+  - v2
+  - grpc-v1
+  supportedModelFormats:
+  - autoSelect: true
+    name: pytorch
+    priority: 2
+    version: "1"
+---
+apiVersion: serving.kserve.io/v1alpha1
+kind: ClusterServingRuntime
+metadata:
+  name: kserve-tritonserver
+spec:
+  annotations:
+    prometheus.kserve.io/path: /metrics
+    prometheus.kserve.io/port: "8002"
+  containers:
+  - args:
+    - tritonserver
+    - --model-store=/mnt/models
+    - --grpc-port=9000
+    - --http-port=8080
+    - --allow-grpc=true
+    - --allow-http=true
+    image: nvcr.io/nvidia/tritonserver:23.05-py3
+    name: kserve-container
+    resources:
+      limits:
+        cpu: "1"
+        memory: 2Gi
+      requests:
+        cpu: "1"
+        memory: 2Gi
+  protocolVersions:
+  - v2
+  - grpc-v2
+  supportedModelFormats:
+  - autoSelect: true
+    name: tensorrt
+    priority: 1
+    version: "8"
+  - autoSelect: true
+    name: tensorflow
+    priority: 1
+    version: "1"
+  - autoSelect: true
+    name: tensorflow
+    priority: 1
+    version: "2"
+  - autoSelect: true
+    name: onnx
+    priority: 1
+    version: "1"
+  - name: pytorch
+    version: "1"
+  - autoSelect: true
+    name: triton
+    priority: 1
+    version: "2"
+---
+apiVersion: serving.kserve.io/v1alpha1
+kind: ClusterServingRuntime
+metadata:
+  name: kserve-xgbserver
+spec:
+  annotations:
+    prometheus.kserve.io/path: /metrics
+    prometheus.kserve.io/port: "8080"
+  containers:
+  - args:
+    - --model_name={{.Name}}
+    - --model_dir=/mnt/models
+    - --http_port=8080
+    - --nthread=1
+    image: kserve/xgbserver:v0.11.1
+    name: kserve-container
+    resources:
+      limits:
+        cpu: "1"
+        memory: 2Gi
+      requests:
+        cpu: "1"
+        memory: 2Gi
+  protocolVersions:
+  - v1
+  - v2
+  supportedModelFormats:
+  - autoSelect: true
+    name: xgboost
+    priority: 1
+    version: "1"