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[v1.x][LT] Add forward & backward linalg.gemm test for large size #18825
[v1.x][LT] Add forward & backward linalg.gemm test for large size #18825
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Hey @ChaiBapchya , Thanks for submitting the PR
CI supported jobs: [website, windows-cpu, sanity, centos-cpu, edge, miscellaneous, unix-cpu, clang, centos-gpu, windows-gpu, unix-gpu] Note: |
left nitpicky comments. Rest LGTM ! |
out = mx.nd.linalg.gemm(inp1, inp2, inp3, transpose_b=True) | ||
return inp1.grad, inp2.grad, inp3.grad, out | ||
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inp1 = mx.nd.ones(shape=(MEDIUM_X, SMALL_Y, MEDIUM_X)) |
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It's incorrect according to PEP8 style guide Python
https://www.python.org/dev/peps/pep-0008/
inp1 = mx.nd.ones(shape=(MEDIUM_X, SMALL_Y, MEDIUM_X)) | ||
perturbation = 0.2 | ||
inp1[0][0][0] = perturbation | ||
inp2 = mx.nd.ones(shape=(MEDIUM_X, SMALL_Y, MEDIUM_X)) |
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spaces around =
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It's incorrect according to PEP8 style guide Python
https://www.python.org/dev/peps/pep-0008/
perturbation = 0.2 | ||
inp1[0][0][0] = perturbation | ||
inp2 = mx.nd.ones(shape=(MEDIUM_X, SMALL_Y, MEDIUM_X)) | ||
inp3 = mx.nd.ones(shape=(MEDIUM_X, SMALL_Y, SMALL_Y)) |
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same
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It's incorrect according to PEP8 style guide Python
https://www.python.org/dev/peps/pep-0008/
@mxnet-bot run ci [centos-cpu] |
Jenkins CI successfully triggered : [centos-cpu] |
Description
Tests mx.nd.linalg.gemm operator for large size tensor [not large dimension]
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