apeforest commented on a change in pull request #15048: [MXNET-1408] Adding
test to verify Large Tensor Support for ravel and unravel
URL: https://github.com/apache/incubator-mxnet/pull/15048#discussion_r288201463
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File path: tests/nightly/test_large_array.py
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@@ -279,6 +279,19 @@ def test_diag():
assert_almost_equal(r.asnumpy(), np.diag(a_np, k=k))
+def test_ravel_and_unravel():
+ idxs_2d = [[LARGE_X-1,LARGE_X-100,6],[SMALL_Y-1,SMALL_Y-10,1]]
Review comment:
Hi @marcoabreu, thanks a lot for your suggestion and it's a very good
learning for me too. The large tensor support is crucial to DGL (Deep Graph
Library) that is using MXNet and planning to release with support of large
tensors. Without this test, we cannot make this feature production ready.
While I appreciate the direction of testing you suggested and definitely
would like to explore it further, I am also afraid that not adding tests before
we implement the approach you suggested will block the release of DGL and other
MXNet projects that depend on large tensors as well.
Can we have a seperate project to address the test efficiency (we may need
some expertise from CI team for this project) while moving on with the large
tensor project? Please let me know if you have other concerns or advice. Thank
you
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