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author | A. Unique TensorFlower <gardener@tensorflow.org> | 2018-09-12 01:49:11 -0700 |
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committer | TensorFlower Gardener <gardener@tensorflow.org> | 2018-09-12 01:53:01 -0700 |
commit | 6bb429b7772bead4e386cb22b6ab2aefa520442e (patch) | |
tree | 3e8850d0ee4db999a281d15418431efdc6aba942 /tensorflow/compiler/tests | |
parent | 4c936f1b220676d0d427f5f38b4111cfb9011b5a (diff) |
Automated rollback of commit 4c936f1b220676d0d427f5f38b4111cfb9011b5a
PiperOrigin-RevId: 212600364
Diffstat (limited to 'tensorflow/compiler/tests')
-rw-r--r-- | tensorflow/compiler/tests/concat_ops_test.py | 35 |
1 files changed, 0 insertions, 35 deletions
diff --git a/tensorflow/compiler/tests/concat_ops_test.py b/tensorflow/compiler/tests/concat_ops_test.py index 2d225ad226..37e5318bb5 100644 --- a/tensorflow/compiler/tests/concat_ops_test.py +++ b/tensorflow/compiler/tests/concat_ops_test.py @@ -291,41 +291,6 @@ class ConcatTest(xla_test.XLATestCase): ValueError, r"Can't concatenate scalars \(use tf\.stack instead\)"): array_ops.concat([scalar, scalar, scalar], dim) - # The purpose of this is to ensure that XLA on GPU will not run out of memory - # with too many arguments. - def testConcatLargeNumberOfTensors(self): - with self.cached_session(): - with self.test_scope(): - for concat_dim in range(2): - params = {} - p = [] - shape = np.array([7, 13]) - num_tensors = 1001 - for i in np.arange(num_tensors): - input_shape = shape - placeholder = array_ops.placeholder( - dtypes.float32, shape=input_shape) - p.append(placeholder) - params[placeholder] = np.random.rand(*input_shape).astype( - np.float32) - - concat_inputs = p - c = array_ops.concat(concat_inputs, concat_dim) - result = c.eval(feed_dict=params) - - self.assertEqual(result.shape, c.get_shape()) - cur_offset = 0 - - for i in np.arange(num_tensors): - # The index into the result is the ':' along all dimensions - # except the concat_dim. slice(0, size) is used for ':', and - # a list of slices is used to index into result. - index = [slice(0, params[p[i]].shape[j]) for j in np.arange(2)] - index[concat_dim] = slice( - cur_offset, cur_offset + params[p[i]].shape[concat_dim]) - cur_offset += params[p[i]].shape[concat_dim] - self.assertAllEqual(result[index], params[p[i]]) - class ConcatOffsetTest(xla_test.XLATestCase): |