anirudh2290 opened a new issue #10431: Elementwise multiplication of two ndarrays returns wrong results URL: https://github.com/apache/incubator-mxnet/issues/10431 Note: Providing complete information in the most concise form is the best way to get help. This issue template serves as the checklist for essential information to most of the technical issues and bug reports. For non-technical issues and feature requests, feel free to present the information in what you believe is the best form. For Q & A and discussion, please start a discussion thread at https://discuss.mxnet.io ## Description Elementwise multiplication of two ndarrays returns wrong results ## Environment info (Required) python, built from source, USE_CUDA=OFF, USE_CUDNN=OFF MXNet commit hash: (Paste the output of `git rev-parse HEAD` here.) f60094053e5f2c233bb39b63bdd16503875a4551 ## Error Message: ``` AssertionError: Items are not equal: Error 100000.000000 exceeds tolerance rtol=0.000010, atol=0.000000. Location of maximum error:(0, 2), a=0.098160, b=-375054495907840.000000 a: array([[ 0.88395894, 0.0185979 , 0.09815959, 0.24501987]], dtype=float32) b: array([[ 8.83958936e-01, 1.85978990e-02, -3.75054496e+14, 2.45019868e-01]], dtype=float32) ``` ## Minimum reproducible example export MXNET_ENGINE_TYPE=NaiveEngine ``` import mxnet as mx from mxnet.test_utils import * x = mx.nd.array(np.random.uniform(-1, 1, size=(1, 4))) x = x.tostype('csr') #x.attach_grad() print(x.asnumpy()) z2 = x * x z1 = mx.nd.sparse.square(x) assert_almost_equal(z1.asnumpy(), z2.asnumpy()) ``` ## What have you tried to solve it? Substituting with mx.nd.square works fine
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