[GitHub] [incubator-mxnet] access2rohit commented on a change in pull request #19294: Numpy large tensor test batch 4

[GitBox <gi...@apache.org>]

access2rohit commented on a change in pull request #19294:
URL: https://github.com/apache/incubator-mxnet/pull/19294#discussion_r535768801



##########
File path: tests/nightly/test_np_large_array.py
##########
@@ -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:
       I think you have improved the test now. Looks good 




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