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jblitzar
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github-python

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for k in xrange(len(adjacency[i][j])):
adjacency_pad[i][j][k] = adjacency[i][j][k]
dist_pad[i][j][k] = dist[i][j][k]
with tf.Session() as sess:
sess.run(tf.global_variables_initializer())
output = sess.run(
pred_op, feed_dict=build_feed_dict(ph, h, adjacency, dist, m))
output_pad = sess.run(
pred_op,
feed_dict=build_feed_dict(ph, h_pad, adjacency_pad, dist_pad, m_pad))
print "output no pad:"
print output
print "\noutput pad:"
print output_pad
return output, output_pad
class MPNNTest(tf.test.TestCase):
"""Tests for MPNNs."""
def test_build_two_graphs(self):
"""Test constructing the MPNN graph."""
batch_size = 5
num_nodes = 3
input_dim = 4
output_dim = 6
adjacency = np.random.randint(2, size=(batch_size, num_nodes, num_nodes))
h = np.random.rand(batch_size, num_nodes, input_dim)
dist = np.random.rand(batch_size, num_nodes, num_nodes)
m = np.full((batch_size, num_nodes), 1)
with tf.Graph().as_default():
hparams = mpnn.MPNN.default_hparams()
model = mpnn.MPNN(hparams, input_dim, output_dim, num_edge_class=5)
ph, _ = model.get_fprop_placeholders()
ph2, _ = model.get_fprop_placeholders()
print ph[0], ph2[0]
pred = model.fprop(*ph, train=True)
pred2 = model.fprop(*ph2)
with tf.Session() as sess:
sess.run(tf.global_variables_initializer())
pred1 = sess.run(
pred, feed_dict=build_feed_dict(ph, h, adjacency, dist, m))
pred2 = sess.run(
pred2, feed_dict=build_feed_dict(ph2, h, adjacency, dist, m))
self.assertListEqual(list(pred1.shape), [batch_size, output_dim])
self.assertListEqual(list(pred2.shape), [batch_size, output_dim])
self.assertAllClose(pred1, pred2)
print "Successfully constructed MPNN graph."
def test_permutation_and_pad_invariance(self):
# test GG-NN msg pass + graph level output
hparams = mpnn.MPNN.default_hparams()
output, output_perm = get_permutation_test_outputs(hparams)
self.assertAllClose(output, output_perm)
output, output_pad = get_pad_test_outputs(hparams)
self.assertAllClose(output, output_pad)
# test edge_network message function
hparams.message_function = "edge_network"
output, output_perm = get_permutation_test_outputs(hparams)
self.assertAllClose(output, output_perm)
output, output_pad = get_pad_test_outputs(hparams)
self.assertAllClose(output, output_pad)
# test edge_network + set2vec output
hparams.output_function = "set2vec"
output, output_perm = get_permutation_test_outputs(hparams)
self.assertAllClose(output, output_perm)
output, output_pad = get_pad_test_outputs(hparams)
self.assertAllClose(output, output_pad)
if __name__ == "__main__":
tf.test.main()
# <FILESEP>
"""
Copyright 2022 Google LLC
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
ERROR: type should be string, got " https://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.