# 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.""" from __future__ import absolute_import from __future__ import division from __future__ import print_function import numpy as np import tensorflow as tf class GatherTest(tf.test.TestCase): use_gpu = False def testScalar1D(self): with self.test_session(use_gpu=self.use_gpu): params = tf.constant([0, 1, 2, 3, 7, 5]) indices = tf.constant(4) gather_t = tf.gather(params, indices) gather_val = gather_t.eval() self.assertAllEqual(7, gather_val) self.assertEqual([], gather_t.get_shape()) def testScalar2D(self): with self.test_session(use_gpu=self.use_gpu): params = tf.constant([[0, 1, 2], [3, 4, 5], [6, 7, 8], [9, 10, 11], [12, 13, 14]]) indices = tf.constant(2) gather_t = tf.gather(params, indices) gather_val = gather_t.eval() self.assertAllEqual([6, 7, 8], gather_val) self.assertEqual([3], gather_t.get_shape()) def testSimpleTwoD32(self): with self.test_session(use_gpu=self.use_gpu): params = tf.constant([[0, 1, 2], [3, 4, 5], [6, 7, 8], [9, 10, 11], [12, 13, 14]]) indices = tf.constant([0, 4, 0, 2]) gather_t = tf.gather(params, indices) gather_val = gather_t.eval() self.assertAllEqual([[0, 1, 2], [12, 13, 14], [0, 1, 2], [6, 7, 8]], gather_val) self.assertEqual([4, 3], gather_t.get_shape()) def testHigherRank(self): np.random.seed(1) # We check that scalar and empty shapes work as well for shape in (7, 0), (4, 3, 2): for indices_shape in (), (0,), (3, 0), (3, 5): params = np.random.randn(*shape) indices = np.random.randint(shape[0], size=indices_shape) with self.test_session(use_gpu=self.use_gpu): tf_params = tf.constant(params) tf_indices = tf.constant(indices) gather = tf.gather(tf_params, tf_indices) self.assertAllEqual(params[indices], gather.eval()) self.assertEqual(indices.shape + params.shape[1:], gather.get_shape()) # Test gradients gather_grad = np.random.randn(*gather.get_shape().as_list()) params_grad, indices_grad = tf.gradients( gather, [tf_params, tf_indices], gather_grad) self.assertEqual(indices_grad, None) self.assertEqual(type(params_grad), tf.IndexedSlices) params_grad = tf.convert_to_tensor(params_grad) correct_params_grad = np.zeros(shape) for i, g in zip(indices.flat, gather_grad.reshape((indices.size,) + shape[1:])): correct_params_grad[i] += g self.assertAllClose(correct_params_grad, params_grad.eval()) def testUnknownIndices(self): params = tf.constant([[0, 1, 2]]) indices = tf.placeholder(tf.int32) gather_t = tf.gather(params, indices) self.assertEqual(None, gather_t.get_shape()) def testBadIndices(self): with self.test_session(use_gpu=False): params = [0, 1, 2] indices = [[7]] gather = tf.gather(params, indices) with self.assertRaisesOpError(r"indices\[0,0\] = 7 is not in \[0, 3\)"): gather.eval() def testEmptySlices(self): with self.test_session(use_gpu=self.use_gpu): for dtype in np.float32, np.float64: for itype in np.int32, np.int64: params = np.zeros((7, 0), dtype=dtype) indices = np.array([3, 4], dtype=itype) gather = tf.gather(params, indices) self.assertAllEqual(gather.eval(), np.zeros((2, 0))) class GatherGpuTest(GatherTest): use_gpu = True if __name__ == "__main__": tf.test.main()