added azure

examples/models/azure_aks_deep_mnist/.s2i/environment

@@ -0,0 +1,4 @@
+MODEL_NAME=DeepMnist
+API_TYPE=REST
+SERVICE_TYPE=MODEL
+PERSISTENCE=0

examples/models/azure_aks_deep_mnist/DeepMnist.py

@@ -0,0 +1,19 @@
+import tensorflow as tf
+import numpy as np
+
+class DeepMnist(object):
+    def __init__(self):
+        self.class_names = ["class:{}".format(str(i)) for i in range(10)]
+        self.sess = tf.Session()
+        saver = tf.train.import_meta_graph("model/deep_mnist_model.meta")
+        saver.restore(self.sess,tf.train.latest_checkpoint("./model/"))
+
+        graph = tf.get_default_graph()
+        self.x = graph.get_tensor_by_name("x:0")
+        self.y = graph.get_tensor_by_name("y:0")
+
+    def predict(self,X,feature_names):
+        predictions = self.sess.run(self.y,feed_dict={self.x:X})
+        return predictions.astype(np.float64)
+
+

examples/models/azure_aks_deep_mnist/create_model.py

@@ -0,0 +1,36 @@
+from tensorflow.examples.tutorials.mnist import input_data
+mnist = input_data.read_data_sets("MNIST_data/", one_hot = True)
+import tensorflow as tf
+
+if __name__ == '__main__':
+
+    x = tf.placeholder(tf.float32, [None,784], name="x")
+
+    W = tf.Variable(tf.zeros([784,10]))
+    b = tf.Variable(tf.zeros([10]))
+
+    y = tf.nn.softmax(tf.matmul(x,W) + b, name="y")
+
+    y_ = tf.placeholder(tf.float32, [None, 10])
+
+
+    cross_entropy = tf.reduce_mean(-tf.reduce_sum(y_ * tf.log(y), reduction_indices=[1]))
+
+    train_step = tf.train.GradientDescentOptimizer(0.5).minimize(cross_entropy)
+
+    init = tf.initialize_all_variables()
+
+    sess = tf.Session()
+    sess.run(init)
+
+    for i in range(1000):
+        batch_xs, batch_ys = mnist.train.next_batch(100)
+        sess.run(train_step, feed_dict={x: batch_xs, y_: batch_ys})
+
+    correct_prediction = tf.equal(tf.argmax(y,1), tf.argmax(y_,1))
+    accuracy = tf.reduce_mean(tf.cast(correct_prediction, tf.float32))
+    print(sess.run(accuracy, feed_dict = {x: mnist.test.images, y_:mnist.test.labels}))
+
+    saver = tf.train.Saver()
+
+    saver.save(sess, "model/deep_mnist_model")

examples/models/azure_aks_deep_mnist/deep_mnist.json

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+{
+    "apiVersion": "machinelearning.seldon.io/v1alpha2",
+    "kind": "SeldonDeployment",
+    "metadata": {
+        "labels": {
+            "app": "seldon"
+        },
+        "name": "deep-mnist"
+    },
+    "spec": {
+        "annotations": {
+            "project_name": "Tensorflow MNIST",
+            "deployment_version": "v1"
+        },
+        "name": "deep-mnist",
+        "oauth_key": "oauth-key",
+        "oauth_secret": "oauth-secret",
+        "predictors": [
+            {
+                "componentSpecs": [{
+                    "spec": {
+                        "containers": [
+                            {
+                                "image": "REPLACE_FOR_IMAGE_AND_TAG",
+                                "imagePullPolicy": "IfNotPresent",
+                                "name": "classifier",
+                                "resources": {
+                                    "requests": {
+                                        "memory": "1Mi"
+                                    }
+                                }
+                            }
+                        ],
+                        "terminationGracePeriodSeconds": 20
+                    }
+                }],
+                "graph": {
+                    "children": [],
+                    "name": "classifier",
+                    "endpoint": {
+			"type" : "REST"
+		    },
+                    "type": "MODEL"
+                },
+                "name": "single-model",
+                "replicas": 1,
+		"annotations": {
+		    "predictor_version" : "v1"
+		}
+            }
+        ]
+    }
+}

examples/models/azure_aks_deep_mnist/model/checkpoint

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+model_checkpoint_path: "deep_mnist_model"
+all_model_checkpoint_paths: "deep_mnist_model"

examples/models/azure_aks_deep_mnist/requirements.txt

@@ -0,0 +1 @@
+tensorflow>=1.12.0

examples/models/azure_aks_deep_mnist/tiller-role-binding.yaml

@@ -0,0 +1,12 @@
+kind: ClusterRoleBinding
+apiVersion: rbac.authorization.k8s.io/v1
+metadata:
+  name: tiller-role-binding
+roleRef:
+  kind: ClusterRole
+  name: cluster-admin
+  apiGroup: rbac.authorization.k8s.io
+subjects:
+- kind: ServiceAccount
+  name: tiller
+  namespace: kube-system