access2rohit 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_r289496932
########## File path: tests/nightly/test_large_array.py ########## @@ -274,11 +265,26 @@ def test_diag(): assert_almost_equal(r.asnumpy(), np.diag(a_np, k=k)) # random k - k = np.random.randint(-min(LARGE_X, 64) + 1, min(h, w)) + k = np.random.randint(-min(LARGE_X, SMALL_Y) + 1, min(LARGE_X, SMALL_Y)) r = mx.nd.diag(a, k=k) assert_almost_equal(r.asnumpy(), np.diag(a_np, k=k)) +def test_ravel_multi_index(): + indices_2d = [[LARGE_X-1, LARGE_X-100, 6], [SMALL_Y-1, SMALL_Y-10, 1]] + idx = mx.nd.ravel_multi_index(mx.nd.array(indices_2d, dtype=np.int64), shape=(LARGE_X, SMALL_Y)) + idx_numpy = np.ravel_multi_index(indices_2d, (LARGE_X, SMALL_Y)) + assert np.sum(1 for i in range(idx.size) if idx[i] == idx_numpy[i]) == 3 + + +def test_unravel_index(): + original_2d_indices = [[LARGE_X-1, LARGE_X-100, 6], [SMALL_Y-1, SMALL_Y-10, 1]] Review comment: The input is not 2d_array, we pass indices as input. I can do following: `low_large_value = 2**32` `high_large_value = 2**34` `a = nd.random.randint(low_large_value, high_large_value, dtype=np.int64)` for random Large indices Good Point ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services