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| np_out = np.nonzero(x.asnumpy()) | ||
| np_out = np.transpose(np_out) | ||
| assert_almost_equal(mx_out.asnumpy(), np_out, rtol, atol) | ||
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| (1, 1), | ||
| (1, 2, 3), | ||
| (1, 0), | ||
| (2, 0, 3) |
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| for hybridize in [True, False]: | ||
| for shape in [(), | ||
| (1,), | ||
| (1, 1), |
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Get rid of this shape and the shape above.
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LGTM after rebase and resolution of conflicts
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* add cpu test and handle 0-dim * add FGradient with MakeZeroGradNodes * handle 0-dim and 0-shape and add test on gpu * add doc * fix bug in review * do not use thrust::inclusive_scan on cpu * fix format error * edit test and remove gpu test The output is same as numpy.transpose(numpy.nonzero(x)) * fix error of review * edit test
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* add cpu test and handle 0-dim * add FGradient with MakeZeroGradNodes * handle 0-dim and 0-shape and add test on gpu * add doc * fix bug in review * do not use thrust::inclusive_scan on cpu * fix format error * edit test and remove gpu test The output is same as numpy.transpose(numpy.nonzero(x)) * fix error of review * edit test
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* add cpu test and handle 0-dim * add FGradient with MakeZeroGradNodes * handle 0-dim and 0-shape and add test on gpu * add doc * fix bug in review * do not use thrust::inclusive_scan on cpu * fix format error * edit test and remove gpu test The output is same as numpy.transpose(numpy.nonzero(x)) * fix error of review * edit test
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* add cpu test and handle 0-dim * add FGradient with MakeZeroGradNodes * handle 0-dim and 0-shape and add test on gpu * add doc * fix bug in review * do not use thrust::inclusive_scan on cpu * fix format error * edit test and remove gpu test The output is same as numpy.transpose(numpy.nonzero(x)) * fix error of review * edit test
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numpy operator nonzero