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new 6f6a1dc [MXNET-291] Fix an ndarray indexing bug with index -1 (#10440)
6f6a1dc is described below
commit 6f6a1dc4d350dcec3058abbe4ca5123b5fce536e
Author: Deokjae Lee <36436141+asitsta...@users.noreply.github.com>
AuthorDate: Sat Apr 7 08:14:35 2018 +0900
[MXNET-291] Fix an ndarray indexing bug with index -1 (#10440)
* Fix an ndarray indexing bug with index -1
* Add tests for ndarray slicing with negative index
* Test revise
---
python/mxnet/ndarray/ndarray.py | 2 +-
tests/python/unittest/test_ndarray.py | 10 +++++++++-
2 files changed, 10 insertions(+), 2 deletions(-)
diff --git a/python/mxnet/ndarray/ndarray.py b/python/mxnet/ndarray/ndarray.py
index cbb1dd5..4677189 100644
--- a/python/mxnet/ndarray/ndarray.py
+++ b/python/mxnet/ndarray/ndarray.py
@@ -797,7 +797,7 @@ fixed-size items.
for i, slice_i in enumerate(key):
if isinstance(slice_i, integer_types):
begin.append(slice_i)
- end.append(slice_i+1)
+ end.append(slice_i+1 if slice_i != -1 else self.shape[i])
step.append(1)
elif isinstance(slice_i, py_slice):
if slice_i.step == 0:
diff --git a/tests/python/unittest/test_ndarray.py
b/tests/python/unittest/test_ndarray.py
index 89b037b..4265bf8 100644
--- a/tests/python/unittest/test_ndarray.py
+++ b/tests/python/unittest/test_ndarray.py
@@ -349,7 +349,7 @@ def test_ndarray_slice():
A = mx.nd.array(np.random.uniform(-10, 10, shape))
A2 = A.asnumpy()
assert same(A[3:8].asnumpy(), A2[3:8])
- A2[3:8] *= 10;
+ A2[3:8] *= 10
A[3:8] = A2[3:8]
assert same(A[3:8].asnumpy(), A2[3:8])
@@ -360,11 +360,19 @@ def test_ndarray_slice():
assert same(A[1,3:4,:,1:5].asnumpy(), A2[1,3:4,:,1:5])
assert A[1,2,3,4,5].asscalar() == A2[1,2,3,4,5]
+ assert A[-1,-2,-3,-4,-5].asscalar() == A2[-1,-2,-3,-4,-5]
a = mx.nd.array([[0, 1], [2, 3]])
assert (a[[1, 1, 0], [0, 1, 0]].asnumpy() == [2, 3, 0]).all()
assert (a[mx.nd.array([1, 1, 0]), mx.nd.array([0, 1, 0])].asnumpy() == [2,
3, 0]).all()
+ shape = (4, 4)
+ A = mx.nd.random.uniform(shape=shape)
+ A2 = A.asnumpy()
+ for i in range(-4, 0):
+ assert A[i, i].asscalar() == A2[i, i]
+ assert same(A[:, i].asnumpy(), A2[:, i])
+ assert same(A[i, :].asnumpy(), A2[i, :])
@with_seed()
def test_ndarray_crop():
--
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