Add example of inferencing with keras using plaidml.

GestureRecognition/keras_ex.py

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+import time
+import os
+
+import numpy as np
+
+os.environ["KERAS_BACKEND"] = "plaidml.keras.backend"
+
+import keras
+import keras.applications as kapp
+from keras.datasets import cifar10
+
+(x_train, y_train_cats), (x_test, y_test_cats) = cifar10.load_data()
+batch_size = 8
+x_train = x_train[:batch_size]
+x_train = np.repeat(np.repeat(x_train, 7, axis=1), 7, axis=2)
+model = kapp.VGG19()
+model.compile(optimizer='sgd', loss='categorical_crossentropy',
+              metrics=['accuracy'])
+
+print("Running initial batch (compiling tile program)")
+y = model.predict(x=x_train, batch_size=batch_size)
+
+# Now start the clock and run 10 batches
+print("Timing inference...")
+start = time.time()
+for i in range(10):
+    y = model.predict(x=x_train, batch_size=batch_size)
+print("Ran in {} seconds".format(time.time() - start))