Fix vgg16_imagenet.py

llvm/projects/keras/src/vgg16_imagenet.py

@@ -206,20 +206,14 @@ if __name__ == '__main__':
     f = open("/home/nz11/ILSVRC2012/ILSVRC2012_devkit_t12/data/ILSVRC2012_validation_ground_truth.txt","r")
     y_true = f.read().strip().split("\n")
     y_true = list(map(int, y_true))
-    y_true = np.array([convert_original_idx_to_keras_idx(idx) for idx in y_true])[idx]
-    y_true = to_categorical(y_true, num_classes=1000)
+    y_true = np.array([convert_original_idx_to_keras_idx(idx) for idx in y_true])[idx]    
+    y_true = y_true.astype(np.uint32)
     f.close()
-    
+        
     
     translate_to_approxhpvm(model_nchw, "data/vgg16_imagenet/", X_test[:val_size], y_true[:val_size], 1000)
     
-    dumpCalibrationData("data/vgg16_imagenet/test_input.bin", X_test, "data/vgg16_imagenet/test_labels.bin", y_true)
-
-
-    
-    y_pred = model_nchw.predict(X_test[:val_size])
-    print ('val accuracy', np.sum(np.argmax(y_pred, axis=1) == np.argmax(y_true[:val_size], axis=1)) / val_size)
-    
+    dumpCalibrationData("data/vgg16_imagenet/test_input.bin", X_test, "data/vgg16_imagenet/test_labels.bin", y_true)    
     
     
     
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