experiments/STT-tensorflow
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Support negative values in the reduction_indices argument of reduce_*

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functions.

Fixes #2426
Change: 122735328
This commit is contained in:
Manjunath Kudlur 2016-05-19 07:45:10 -08:00 committed by TensorFlower Gardener
parent 144855b385
commit cce41d3fa3
3 changed files with 41 additions and 26 deletions
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5
tensorflow/core/kernels/reduction_ops_common.cc
View File

@ -61,12 +61,13 @@ Status ReductionHelper::Simplify(const Tensor& data, const Tensor& axis,
gtl::InlinedVector<bool, 4> bitmap(data.dims(), false);
auto axis_vec = axis.flat<int32>();
for (int64 i = 0; i < axis.NumElements(); ++i) {
const int32 index = axis_vec(i);
if (index < 0 || index >= data.dims()) {
int32 index = axis_vec(i);
if (index < -data.dims() || index >= data.dims()) {
return errors::InvalidArgument("Invalid reduction dimension (", index,
" for input with ", data.dims(),
" dimension(s)");
}
index = (index + data.dims()) % data.dims();
bitmap[index] = true;
}

55
tensorflow/python/kernel_tests/reduction_ops_test.py
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@ -27,34 +27,40 @@ from tensorflow.python.ops import math_ops
class ReducedShapeTest(tf.test.TestCase):
def _check(self, shape, axes, result):
output = math_ops.reduced_shape(shape, axes=axes)
self.assertAllEqual(output.eval(), result)
def testSimple(self):
with self.test_session():
def check(shape, axes, result):
output = math_ops.reduced_shape(shape, axes=axes)
self.assertAllEqual(output.eval(), result)
check([3], [], [3])
check([3], [0], [1])
check([5, 3], [], [5, 3])
check([5, 3], [0], [1, 3])
check([5, 3], [1], [5, 1])
check([5, 3], [0, 1], [1, 1])
self._check([3], [], [3])
self._check([3], [0], [1])
self._check([5, 3], [], [5, 3])
self._check([5, 3], [0], [1, 3])
self._check([5, 3], [1], [5, 1])
self._check([5, 3], [0, 1], [1, 1])
def testZeros(self):
"""Check that reduced_shape does the right thing with zero dimensions."""
with self.test_session():
def check(shape, axes, result):
output = math_ops.reduced_shape(shape, axes=axes)
self.assertAllEqual(output.eval(), result)
check([0], [], [0])
check([0], [0], [1])
check([0, 3], [], [0, 3])
check([0, 3], [0], [1, 3])
check([0, 3], [1], [0, 1])
check([0, 3], [0, 1], [1, 1])
check([3, 0], [], [3, 0])
check([3, 0], [0], [1, 0])
check([3, 0], [1], [3, 1])
check([3, 0], [0, 1], [1, 1])
self._check([0], [], [0])
self._check([0], [0], [1])
self._check([0, 3], [], [0, 3])
self._check([0, 3], [0], [1, 3])
self._check([0, 3], [1], [0, 1])
self._check([0, 3], [0, 1], [1, 1])
self._check([3, 0], [], [3, 0])
self._check([3, 0], [0], [1, 0])
self._check([3, 0], [1], [3, 1])
self._check([3, 0], [0, 1], [1, 1])
def testNegAxes(self):
with self.test_session():
self._check([10, 10, 10], [-1], [10, 10, 1])
self._check([10, 10, 10], [-1, 2], [10, 10, 1])
self._check([10, 10, 10], [-1, -1], [10, 10, 1])
self._check([10, 10, 10], [-1, 0], [1, 10, 1])
self._check([10, 10, 10], [-3], [1, 10, 10])
class SumReductionTest(tf.test.TestCase):
@ -110,6 +116,9 @@ class SumReductionTest(tf.test.TestCase):
self._compareAll(np_arr, [1, 2])
self._compareAll(np_arr, [0, 2])
self._compareAll(np_arr, [0, 1, 2])
self._compareAll(np_arr, [-1])
self._compareAll(np_arr, [-1, -3])
self._compareAll(np_arr, [-1, 1])
def testFloatReduce4D(self):
# Create a 4D array of floats and reduce across some
@ -167,7 +176,7 @@ class SumReductionTest(tf.test.TestCase):
input_tensor = tf.convert_to_tensor(np_arr)
with self.assertRaisesWithPredicateMatch(
ValueError, lambda e: "Invalid reduction dimension" in str(e)):
tf.reduce_sum(input_tensor, [-1])
tf.reduce_sum(input_tensor, [-3])
with self.assertRaisesWithPredicateMatch(
ValueError, lambda e: "Invalid reduction dimension" in str(e)):
tf.reduce_sum(input_tensor, [2])

7
tensorflow/python/ops/math_ops.py
View File

@ -1527,10 +1527,14 @@ def _ReductionShape(op):
reduction_indices = np.ravel(reduction_indices)
for reduction_index in reduction_indices:
if reduction_index < 0 or reduction_index >= input_shape.ndims:
if (reduction_index < -input_shape.ndims or
reduction_index >= input_shape.ndims):
raise ValueError("Invalid reduction dimension %d for input with %d "
"dimensions" % (reduction_index, input_shape.ndims))
reduction_indices = set([(x + input_shape.ndims) % input_shape.ndims
for x in reduction_indices])
returned_dims = []
if keep_dims:
for i, dim in enumerate(input_shape.dims):
@ -1624,6 +1628,7 @@ def reduced_shape(input_shape, axes):
axes = to_int32(axes) # [1, 2]
input_rank = array_ops.size(input_shape) # 4
axes = (axes + input_rank) % input_rank
axes_shape = array_ops.shape(axes) # [2]
return gen_data_flow_ops.dynamic_stitch( # [2, 1, 1, 7]
[range(input_rank), # [0, 1, 2, 3]