access2rohit commented on a change in pull request #19059:
URL: https://github.com/apache/incubator-mxnet/pull/19059#discussion_r485261190
##########
File path: tests/nightly/test_np_large_array.py
##########
@@ -176,11 +178,10 @@ def test_amin():
@use_np
def test_amax():
A = np.zeros((INT_OVERFLOW, 2))
- A[100][1] = 1
+ A[-1, -1] = 1
A.attach_grad()
with mx.autograd.record():
B = np.amax(A)
- print(B)
assert B == 1.0
B.backward()
Review comment:
can you move it inside `autograd.record()`
##########
File path: tests/nightly/test_np_large_array.py
##########
@@ -453,13 +455,14 @@ def batch_check(x1, x2, axises, shapes):
# backward not working https://github.com/apache/incubator-mxnet/issues/18952
def test_copysign():
A = np.ones((INT_OVERFLOW, 2))
- #A.attach_grad()
- #with mx.autograd.record():
- B = np.copysign(A, -1)
- assert B.shape == (INT_OVERFLOW, 2)
- assert B[0][0] == -1
- #B.backward()
- #assert A.grad.shape == (INT_OVERFLOW, 2)
+ A.attach_grad()
+ B = np.array([-1])
+ with mx.autograd.record():
+ C = np.copysign(A, B)
+ assert C.shape == (INT_OVERFLOW, 2)
+ assert C[0][0] == -1
+ C.backward()
Review comment:
can you move it inside `autograd.record()`
##########
File path: tests/nightly/test_np_large_array.py
##########
@@ -568,7 +571,686 @@ def test_slice_assign():
B[-1] = 2
assert B[-1, 0] == 2 and B[-1, 1] == 2
+@use_np
[email protected](reason='This test will pass; will fail if the dim along \
+ the axis is large. Need to add dim check')
+def test_cumsum():
+ A = np.ones((INT_OVERFLOW, 3))
+ A.attach_grad()
+ with mx.autograd.record():
+ B = np.cumsum(A, axis=1, dtype='float64')
+ assert B.shape == A.shape
+ assert B[-1, -1] == 3
+ B.backward()
Review comment:
same
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