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# Copyright 2015 The TensorFlow Authors. 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.
# ==============================================================================
"""Tests for tensorflow.ops.tf.gather_nd."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import time
import numpy as np
import tensorflow as tf
class GatherNdTest(tf.test.TestCase):
use_gpu = False
def _testSimpleDtype(self, dtype):
with self.test_session(use_gpu=self.use_gpu):
params = tf.constant(np.array([8, 1, 2, 3, 7, 5], dtype=dtype))
indices = tf.constant([[4], [4], [0]])
gather_nd_t = tf.gather_nd(params, indices)
gather_nd_val = gather_nd_t.eval()
self.assertAllEqual(np.array([7, 7, 8], dtype=dtype), gather_nd_val)
self.assertEqual([3], gather_nd_t.get_shape())
def testSimpleDtype(self):
self._testSimpleDtype(np.float32)
self._testSimpleDtype(np.float64)
self._testSimpleDtype(np.int32)
self._testSimpleDtype(np.int64)
self._testSimpleDtype(np.complex64)
self._testSimpleDtype("|S") # byte strings in python2 + 3
def testHigherRankParams(self):
with self.test_session(use_gpu=self.use_gpu):
shape = (10, 20, 5, 1, 17)
params = np.random.rand(*shape)
indices = np.vstack([
np.random.randint(0, s, size=2000) for s in shape]).T
gather_nd_t = tf.gather_nd(params, indices)
gather_nd_val = gather_nd_t.eval()
expected = params[tuple(indices.T)]
self.assertAllEqual(expected, gather_nd_val)
self.assertEqual([2000], gather_nd_t.get_shape())
def testHigherRankParamsAndIndices(self):
with self.test_session(use_gpu=self.use_gpu):
shape = (10, 20, 5, 1, 17)
params = np.random.rand(*shape)
indices = np.vstack([
np.random.randint(0, s, size=2000) for s in shape]).T
indices_reshaped = indices.reshape([10, 10, 20, 5])
gather_nd_t = tf.gather_nd(params, indices_reshaped)
gather_nd_val = gather_nd_t.eval()
expected = params[tuple(indices.T)]
self.assertAllEqual(expected.reshape([10, 10, 20]), gather_nd_val)
self.assertEqual([10, 10, 20], gather_nd_t.get_shape())
def testUnknownIndices(self):
params = tf.constant([[0, 1, 2]])
indices = tf.placeholder(tf.int32)
gather_nd_t = tf.gather_nd(params, indices)
shape = gather_nd_t.get_shape()
self.assertEqual(shape.ndims, None)
self.assertEqual(shape[0].value, None)
def testBadIndices(self):
with self.test_session(use_gpu=False):
params = [0, 1, 2]
indices = [[[0], [7]]] # Make this one higher rank
gather_nd = tf.gather_nd(params, indices)
with self.assertRaisesOpError(
r"flat indices\[1, :\] = \[7\] does not index into param "
r"\(shape: \[3\]\)"):
gather_nd.eval()
class GatherNdGpuTest(GatherNdTest):
use_gpu = True
class GatherNdOpBenchmark(tf.test.Benchmark):
def benchmark_gather_nd_op(self):
shape = (100, 47, 18, 170, 13)
np.random.seed(127)
params = np.random.rand(*shape)
indices = np.vstack([
np.random.randint(0, s, size=10000) for s in shape]).T
with tf.Session():
t_params = tf.Variable(params)
t_indices = tf.Variable(indices)
gather_op = tf.gather_nd(t_params, t_indices)
tf.initialize_all_variables().run()
for _ in range(10):
gather_op.eval()
t1 = time.time()
for _ in range(1000):
gather_op.eval()
t2 = time.time()
self.report_benchmark(iters=1000, wall_time=(t2-t1)/1000.0)
if __name__ == "__main__":
tf.test.main()
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