Repository: kserve/kserve

Issue:
Create PyTorch GPU Image for GPU inference
/kind feature

**Describe the solution you'd like**
For PyTorch GPU inference we need to create an image with `nvidia/cuda:10.0-cudnn7-devel-ubuntu18.04` as base image  and `Apex` which is pytorch extension with NVIDIA-maintained utilities to streamline mixed precision and distributed training. 

**Anything else you would like to add:**
[Miscellaneous information that will assist in solving the issue.]



Discussion:

Resolving patch:
diff --git a/python/kfserving/kfserving/api/kf_serving_client.py b/python/kfserving/kfserving/api/kf_serving_client.py
--- a/python/kfserving/kfserving/api/kf_serving_client.py
+++ b/python/kfserving/kfserving/api/kf_serving_client.py
@@ -42,7 +42,7 @@ def __init__(self, config_file=None, context=None, # pylint: disable=too-many-ar
                 persist_config=persist_config)
         else:
             config.load_incluster_config()
-
+        self.core_api = client.CoreV1Api()
         self.api_instance = client.CustomObjectsApi()
 
     def set_credentials(self, storage_type, namespace=None, credentials_file=None,
diff --git a/python/pytorchserver/pytorchserver/model.py b/python/pytorchserver/pytorchserver/model.py
--- a/python/pytorchserver/pytorchserver/model.py
+++ b/python/pytorchserver/pytorchserver/model.py
@@ -29,7 +29,8 @@ def __init__(self, name: str, model_class_name: str, model_dir: str):
         self.model_class_name = model_class_name
         self.model_dir = model_dir
         self.ready = False
-        self._pytorch = None
+        self.model = None
+        self.device = torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')
 
     def load(self):
         model_file_dir = kfserving.Storage.download(self.model_dir)
@@ -53,20 +54,20 @@ def load(self):
         model_class = getattr(importlib.import_module(modulename), model_class_name)
 
         # Make sure the model weight is transform with the right device in this machine
-        device = torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')
-        self._pytorch = model_class().to(device)
-        self._pytorch.load_state_dict(torch.load(model_file, map_location=device))
-        self._pytorch.eval()
+        self.model = model_class().to(self.device)
+        self.model.load_state_dict(torch.load(model_file, map_location=self.device))
+        self.model.eval()
         self.ready = True
 
     def predict(self, request: Dict) -> Dict:
         inputs = []
-        try:
-            inputs = torch.tensor(request["instances"])
-        except Exception as e:
-            raise Exception(
-                "Failed to initialize Torch Tensor from inputs: %s, %s" % (e, inputs))
-        try:
-            return {"predictions":  self._pytorch(inputs).tolist()}
-        except Exception as e:
-            raise Exception("Failed to predict %s" % e)
+        with torch.no_grad():
+            try:
+                inputs = torch.tensor(request["instances"]).to(self.device)
+            except Exception as e:
+                raise TypeError(
+                    "Failed to initialize Torch Tensor from inputs: %s, %s" % (e, inputs))
+            try:
+                return {"predictions":  self.model(inputs).tolist()}
+            except Exception as e:
+                raise Exception("Failed to predict %s" % e)


Test patch:
diff --git a/config/overlays/test/configmap/inferenceservice.yaml b/config/overlays/test/configmap/inferenceservice.yaml
--- a/config/overlays/test/configmap/inferenceservice.yaml
+++ b/config/overlays/test/configmap/inferenceservice.yaml
@@ -45,8 +45,10 @@ data:
         "pytorch": {
             "image": "gcr.io/kubeflow-ci/kfserving/pytorchserver",
             "defaultImageVersion": "latest",
+            "defaultGpuImageVersion": "latest-gpu",
             "allowedImageVersions": [
-               "latest"
+               "latest",
+               "latest-gpu"
             ]
         },
         "tensorrt": {
diff --git a/pkg/apis/serving/v1alpha2/framework_pytorch_test.go b/pkg/apis/serving/v1alpha2/framework_pytorch_test.go
--- a/pkg/apis/serving/v1alpha2/framework_pytorch_test.go
+++ b/pkg/apis/serving/v1alpha2/framework_pytorch_test.go
@@ -16,6 +16,7 @@ func TestFrameworkPytorch(t *testing.T) {
 	g := gomega.NewGomegaWithT(t)
 	allowedPyTorchImageVersionsArray := []string{
 		DefaultPyTorchRuntimeVersion,
+		DefaultPyTorchRuntimeVersionGPU,
 	}
 	allowedPyTorchImageVersions := strings.Join(allowedPyTorchImageVersionsArray, ", ")
 
@@ -35,18 +36,33 @@ func TestFrameworkPytorch(t *testing.T) {
 			},
 			matcher: gomega.MatchError(fmt.Sprintf(InvalidPyTorchRuntimeVersionError, allowedPyTorchImageVersions)),
 		},
+		"RejectGPUResourcesExcluded": {
+			spec: PyTorchSpec{
+				RuntimeVersion: DefaultPyTorchRuntimeVersionGPU,
+			},
+			matcher: gomega.MatchError(fmt.Sprintf(InvalidPyTorchRuntimeExcludesGPU, allowedPyTorchImageVersions)),
+		},
+		"RejectGPUResourcesIncluded": {
+			spec: PyTorchSpec{
+				RuntimeVersion: DefaultPyTorchRuntimeVersion,
+				Resources: v1.ResourceRequirements{
+					Limits: v1.ResourceList{constants.NvidiaGPUResourceType: resource.MustParse("1")},
+				},
+			},
+			matcher: gomega.MatchError(fmt.Sprintf(InvalidPyTorchRuntimeIncludesGPU, allowedPyTorchImageVersions)),
+		},
 	}
 
-	for name, scenario := range scenarios {
-		config := &InferenceServicesConfig{
-			Predictors: &PredictorsConfig{
-				PyTorch: PredictorConfig{
-					ContainerImage:       "kfserving/pytorchserver",
-					DefaultImageVersion:  "latest",
-					AllowedImageVersions: allowedPyTorchImageVersionsArray,
-				},
+	config := &InferenceServicesConfig{
+		Predictors: &PredictorsConfig{
+			PyTorch: PredictorConfig{
+				ContainerImage:       "kfserving/pytorchserver",
+				DefaultImageVersion:  "0.1.0",
+				AllowedImageVersions: allowedPyTorchImageVersionsArray,
 			},
-		}
+		},
+	}
+	for name, scenario := range scenarios {
 		g.Expect(scenario.spec.Validate(config)).Should(scenario.matcher, fmt.Sprintf("Testing %s", name))
 	}
 }
diff --git a/pkg/apis/serving/v1alpha2/v1alpha2_suite_test.go b/pkg/apis/serving/v1alpha2/v1alpha2_suite_test.go
--- a/pkg/apis/serving/v1alpha2/v1alpha2_suite_test.go
+++ b/pkg/apis/serving/v1alpha2/v1alpha2_suite_test.go
@@ -40,6 +40,7 @@ const (
 	DefaultTensorflowRuntimeVersionGPU  = "latest-gpu"
 	DefaultSKLearnRuntimeVersion        = "0.1.0"
 	DefaultPyTorchRuntimeVersion        = "0.1.0"
+	DefaultPyTorchRuntimeVersionGPU     = "0.1.0-gpu"
 	DefaultXGBoostRuntimeVersion        = "0.1.0"
 	DefaultTensorRTRuntimeVersion       = "19.05-py3"
 	DefaultONNXRuntimeVersion           = "v0.5.0"
@@ -96,9 +97,11 @@ func TestMain(m *testing.M) {
 			"pytorch" : {
 				"image" : "kfserving/pytorchserver",
 				"defaultImageVersion": "0.1.0",
+                "defaultGPUImageVersion": "0.1.0-gpu",
 				"allowedImageVersions": [
 				   "latest",
-				   "0.1.0"
+				   "0.1.0",
+                   "0.1.0-gpu"
 				]
 			},
 			"onnx" : {
diff --git a/test/e2e/data/cifar_input.json b/test/e2e/data/cifar_input.json
new file mode 100644
--- /dev/null
+++ b/test/e2e/data/cifar_input.json
@@ -0,0 +1,3276 @@
+{
+   "instances":[
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+}
diff --git a/test/e2e/predictor/test_pytorch.py b/test/e2e/predictor/test_pytorch.py
new file mode 100644
--- /dev/null
+++ b/test/e2e/predictor/test_pytorch.py
@@ -0,0 +1,69 @@
+# Copyright 2019 kubeflow.org.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import numpy as np
+from kubernetes import client
+
+from kfserving import KFServingClient
+from kfserving import constants
+from kfserving import V1alpha2EndpointSpec
+from kfserving import V1alpha2PredictorSpec
+from kfserving import V1alpha2TransformerSpec
+from kfserving import V1alpha2PyTorchSpec
+from kfserving import V1alpha2CustomSpec
+from kfserving import V1alpha2InferenceServiceSpec
+from kfserving import V1alpha2InferenceService
+from kubernetes.client import V1ResourceRequirements
+from kubernetes.client import V1Container
+from ..common.utils import predict
+from ..common.utils import KFSERVING_TEST_NAMESPACE
+
+api_version = constants.KFSERVING_GROUP + '/' + constants.KFSERVING_VERSION
+KFServing = KFServingClient(config_file="~/.kube/config")
+
+
+def test_pytorch():
+    service_name = 'isvc-pytorch'
+    default_endpoint_spec = V1alpha2EndpointSpec(
+        predictor=V1alpha2PredictorSpec(
+            min_replicas=1,
+            pytorch=V1alpha2PyTorchSpec(
+                storage_uri='gs://kfserving-samples/models/pytorch/cifar10',
+                model_class_name="Net",
+                resources=V1ResourceRequirements(
+                    requests={'cpu': '100m', 'memory': '2Gi', 'nvidia.com/gpu': '1'},
+                    limits={'cpu': '100m', 'memory': '2Gi', 'nvidia.com/gpu': '1'}))))
+
+    isvc = V1alpha2InferenceService(api_version=api_version,
+                                    kind=constants.KFSERVING_KIND,
+                                    metadata=client.V1ObjectMeta(
+                                        name=service_name, namespace=KFSERVING_TEST_NAMESPACE,
+                                        annotations={'serving.kubeflow.org/gke-accelerator': 'nvidia-tesla-k80'}),
+                                    spec=V1alpha2InferenceServiceSpec(default=default_endpoint_spec))
+
+    KFServing.create(isvc)
+    try:
+        KFServing.wait_isvc_ready(service_name, namespace=KFSERVING_TEST_NAMESPACE)
+    except RuntimeError as e:
+        print(KFServing.api_instance.get_namespaced_custom_object("serving.knative.dev", "v1", KFSERVING_TEST_NAMESPACE,
+                                                                  "services", service_name + "-predictor-default"))
+        pods = KFServing.core_api.list_namespaced_pod(KFSERVING_TEST_NAMESPACE,
+                                                      label_selector='serving.kubeflow.org/inferenceservice={}'.
+                                                      format(service_name))
+        for pod in pods.items:
+            print(pod)
+        raise e
+    probs = predict(service_name, './data/cifar_input.json')
+    assert(np.argmax(probs) == 3)
+    KFServing.delete(service_name, KFSERVING_TEST_NAMESPACE)
diff --git a/test/scripts/build-python-image.sh b/test/scripts/build-python-image.sh
--- a/test/scripts/build-python-image.sh
+++ b/test/scripts/build-python-image.sh
@@ -20,19 +20,19 @@ set -o errexit
 set -o nounset
 set -o pipefail
 
-if [ ! $# -eq 2 ]; then
-  echo "build-python-image.sh dockerFile imageName"
-  exit -1
+if [ ! $# -eq 3 ]; then
+  echo "build-python-image.sh dockerFile imageName imageTag"
+  exit 1
 fi
 
 # Avoid conflicts due to multipe components parallel executing in same folder.
-mkdir -p build_for_$2
-cp -rf python/* build_for_$2
-cd build_for_$2
+mkdir -p build_for_$2_$3
+cp -rf python/* build_for_$2_$3
+cd build_for_$2_$3
 
 if [ ! -f $1 ]; then
   echo "dockerFile $1 doesn't exist"
-  exit -1
+  exit 1
 fi
 
 REGISTRY="${GCP_REGISTRY}"
@@ -44,4 +44,4 @@ gcloud auth activate-service-account --key-file=${GOOGLE_APPLICATION_CREDENTIALS
 
 cp $1 Dockerfile
 gcloud builds submit . --tag=${REGISTRY}/${REPO_NAME}/$2:${VERSION} --project=${PROJECT} --timeout=20m
-gcloud container images add-tag --quiet ${REGISTRY}/${REPO_NAME}/$2:${VERSION} ${REGISTRY}/${REPO_NAME}/$2:latest --verbosity=info
+gcloud container images add-tag --quiet ${REGISTRY}/${REPO_NAME}/$2:${VERSION} ${REGISTRY}/${REPO_NAME}/$2:$3 --verbosity=info
diff --git a/test/scripts/create-cluster.sh b/test/scripts/create-cluster.sh
--- a/test/scripts/create-cluster.sh
+++ b/test/scripts/create-cluster.sh
@@ -33,6 +33,7 @@ gcloud --project ${PROJECT} beta container clusters create ${CLUSTER_NAME} \
     --addons=HorizontalPodAutoscaling,HttpLoadBalancing \
     --machine-type=n1-standard-4 \
     --cluster-version 1.14 --zone ${ZONE} \
+    --accelerator type=nvidia-tesla-k80,count=1 \
     --enable-stackdriver-kubernetes --enable-ip-alias \
     --enable-autoscaling --min-nodes=3 --max-nodes=10 \
     --enable-autorepair \
@@ -43,3 +44,6 @@ gcloud --project ${PROJECT} container clusters get-credentials ${CLUSTER_NAME} -
 
 echo "Creating namespace ${NAMESPACE} ..."
 kubectl create namespace ${NAMESPACE}
+
+echo "Intalling GPU Drivers"
+kubectl apply -f https://raw.githubusercontent.com/GoogleCloudPlatform/container-engine-accelerators/master/nvidia-driver-installer/cos/daemonset-preloaded.yaml
diff --git a/test/scripts/run-e2e-tests.sh b/test/scripts/run-e2e-tests.sh
--- a/test/scripts/run-e2e-tests.sh
+++ b/test/scripts/run-e2e-tests.sh
@@ -176,5 +176,5 @@ popd
 
 echo "Starting E2E functional tests ..."
 pushd test/e2e >/dev/null
-  pytest -n 1 
+  pytest -n 4
 popd
diff --git a/test/scripts/unit-test.sh b/test/scripts/unit-test.sh
--- a/test/scripts/unit-test.sh
+++ b/test/scripts/unit-test.sh
@@ -29,4 +29,11 @@ GO_DIR=${GOPATH}/src/github.com/${REPO_OWNER}/${REPO_NAME}
 mkdir -p ${GO_DIR}
 cp -r ./* ${GO_DIR}
 cd ${GO_DIR}
-make test
+# Run unit and integration tests
+n=0
+until [ $n -ge 3 ]
+do
+  make test && break
+  n=$[$n+1]
+  sleep 5
+done
diff --git a/test/workflows/components/workflows.libsonnet b/test/workflows/components/workflows.libsonnet
--- a/test/workflows/components/workflows.libsonnet
+++ b/test/workflows/components/workflows.libsonnet
@@ -242,6 +242,10 @@
                     name: "build-pytorchserver",
                     template: "build-pytorchserver",
                   },
+                  {
+                    name: "build-pytorchserver-gpu",
+                    template: "build-pytorchserver-gpu",
+                  },
                   {
                     name: "build-sklearnserver",
                     template: "build-sklearnserver",
@@ -302,13 +306,13 @@
               "test/scripts/build-kfserving.sh",
             ]),  // build-kfserving
             $.parts(namespace, name, overrides).e2e(prow_env, bucket).buildTemplate("build-alibi-explainer", testWorkerImage, [
-              "test/scripts/build-python-image.sh", "alibiexplainer.Dockerfile", "alibi-explainer",
+              "test/scripts/build-python-image.sh", "alibiexplainer.Dockerfile", "alibi-explainer", "latest"
             ]),  // build-alibi-explainer
             $.parts(namespace, name, overrides).e2e(prow_env, bucket).buildTemplate("build-storage-initializer", testWorkerImage, [
-              "test/scripts/build-python-image.sh", "storage-initializer.Dockerfile", "storage-initializer",
+              "test/scripts/build-python-image.sh", "storage-initializer.Dockerfile", "storage-initializer", "latest"
             ]),  // build-storage-initializer
             $.parts(namespace, name, overrides).e2e(prow_env, bucket).buildTemplate("build-xgbserver", testWorkerImage, [
-              "test/scripts/build-python-image.sh", "xgb.Dockerfile", "xgbserver",
+              "test/scripts/build-python-image.sh", "xgb.Dockerfile", "xgbserver", "latest"
             ]),  // build-xgbserver
             $.parts(namespace, name, overrides).e2e(prow_env, bucket).buildTemplate("build-logger", testWorkerImage, [
               "test/scripts/build-logger.sh",
@@ -317,10 +321,13 @@
               "test/scripts/build-custom-image-transformer.sh",
             ]),  // build-custom-image-transformer
             $.parts(namespace, name, overrides).e2e(prow_env, bucket).buildTemplate("build-pytorchserver", testWorkerImage, [
-              "test/scripts/build-python-image.sh", "pytorch.Dockerfile", "pytorchserver",
+              "test/scripts/build-python-image.sh", "pytorch.Dockerfile", "pytorchserver", "latest"
             ]),  // build-pytorchserver
+            $.parts(namespace, name, overrides).e2e(prow_env, bucket).buildTemplate("build-pytorchserver-gpu", testWorkerImage, [
+              "test/scripts/build-python-image.sh", "pytorch-gpu.Dockerfile", "pytorchserver", "latest-gpu"
+            ]),  // build-pytorchserver-gpu
             $.parts(namespace, name, overrides).e2e(prow_env, bucket).buildTemplate("build-sklearnserver", testWorkerImage, [
-              "test/scripts/build-python-image.sh", "sklearn.Dockerfile", "sklearnserver",
+              "test/scripts/build-python-image.sh", "sklearn.Dockerfile", "sklearnserver", "latest"
             ]),  // build-sklearnserver
             $.parts(namespace, name, overrides).e2e(prow_env, bucket).buildTemplate("unit-test", testWorkerImage, [
               "test/scripts/unit-test.sh",