cherry pick files for public release

example.py

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+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+
+# Copyright 2017 ComputerGraphics Tuebingen. All Rights Reserved.
+#
+# 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.
+# ==============================================================================
+# Authors: Fabian Groh, Patrick Wieschollek, Hendrik P.A. Lensch
+
+
+"""
+Demonstration of using FlexConvolution Layer.
+"""
+
+import numpy as np
+import tensorflow as tf
+from layers import flex_convolution
+
+B, Din, Dout, Dp, N, K = 1, 2, 4, 3, 10, 5
+
+features = np.random.randn(B, Din, N).astype(np.float32)
+positions = np.random.randn(B, Dp, N).astype(np.float32)
+neighbors = np.random.randint(0, N, [B, K, N]).astype(np.int32)
+
+features = tf.convert_to_tensor(features)
+positions = tf.convert_to_tensor(positions)
+neighbors = tf.convert_to_tensor(neighbors)
+
+features2 = flex_convolution(features, positions, neighbors, Dout)
+features3 = flex_convolution(features2, positions, neighbors, Dout, trainable=False)
+
+with tf.Session() as sess:
+  sess.run(tf.global_variables_initializer())
+  sess.run(features2)
+  sess.run(features3)
+
+  print(tf.trainable_variables())