access2rohit commented on a change in pull request #19294:
URL: https://github.com/apache/incubator-mxnet/pull/19294#discussion_r525603178
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File path: tests/nightly/test_np_large_array.py
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@@ -542,6 +564,113 @@ def test_slice_assign():
B[-1] = 2
assert B[-1, 0] == 2 and B[-1, 1] == 2
+@use_np
+def test_flatnonzero():
+ inp = np.zeros((2, INT_OVERFLOW))
+ inp[-1, -1] = 1
+ inp.attach_grad()
+ with mx.autograd.record():
+ out = np.flatnonzero(inp)
+ out.backward()
+ assert out.shape == (1, )
+ assert out[0] == int(2 * INT_OVERFLOW - 1)
+ assert inp.grad.shape == inp.shape
+ assert inp.grad[-1, -1] == 0
+
+@use_np
+def test_ravel():
+ inp = np.zeros((2, INT_OVERFLOW))
+ inp[0, -1], inp[-1, -1] = 1, 2
+ inp.attach_grad()
+ with mx.autograd.record():
+ out = np.ravel(inp)
+ out.backward()
+ assert out.shape == (DOUBLE_INT_OVERFLOW, )
+ assert out[INT_OVERFLOW-1] == 1 and out[-1] == 2
+ assert inp.grad.shape == inp.shape
+ assert inp.grad[-1, -1] == 1
+
+@use_np
+def test_mean():
+ inp = np.arange(DOUBLE_INT_OVERFLOW).reshape((2, INT_OVERFLOW))
+ inp.attach_grad()
+ with mx.autograd.record():
+ out = np.mean(inp, axis=1)
+ out.backward()
+ assert out.shape == (2, )
+ assert_almost_equal(out[0], np.array((HALF_INT_OVERFLOW-0.5)), \
Review comment:
can you specify dtype in the input itself ?
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