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[MXNET-1410]Adding Large Tensor Support for tensor transpose#15059

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apeforest merged 1 commit into
apache:masterfrom
access2rohit:lts_transpose
Jun 2, 2019
Merged

[MXNET-1410]Adding Large Tensor Support for tensor transpose#15059
apeforest merged 1 commit into
apache:masterfrom
access2rohit:lts_transpose

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@access2rohit access2rohit commented May 24, 2019 •
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Description

Adds tests for tensor transpose
Fix operators: flip

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Essentials

Please feel free to remove inapplicable items for your PR.

  • The PR title starts with [MXNET-1410], where [MXNET-1410]Adding Large Tensor Support for tensor transpose #15059 refers to the relevant JIRA issue created (except PRs with tiny changes)
  • Changes are complete (i.e. I finished coding on this PR)
  • All changes have test coverage:
  • Unit tests are added for small changes to verify correctness (e.g. adding a new operator)
  • Nightly tests are added for complicated/long-running ones (e.g. changing distributed kvstore)
  • Build tests will be added for build configuration changes (e.g. adding a new build option with NCCL)
  • Code is well-documented:
  • For user-facing API changes, API doc string has been updated.
  • For new C++ functions in header files, their functionalities and arguments are documented.
  • For new examples, README.md is added to explain the what the example does, the source of the dataset, expected performance on test set and reference to the original paper if applicable
  • Check the API doc at http://mxnet-ci-doc.s3-accelerate.dualstack.amazonaws.com/PR-$PR_ID/$BUILD_ID/index.html
  • To the my best knowledge, examples are either not affected by this change, or have been fixed to be compatible with this change

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access2rohit commented May 24, 2019 •
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@mxnet-label-bot add [pr-work-in-progress]

@marcoabreu marcoabreu added pr-awaiting-review PR is waiting for code review pr-work-in-progress PR is still work in progress labels May 24, 2019
@access2rohit access2rohit changed the title [MXNET-1410]Adding Large Tensor Support for tensor transpose [WIP][MXNET-1410]Adding Large Tensor Support for tensor transpose May 24, 2019
@access2rohit access2rohit force-pushed the lts_transpose branch 2 times, most recently from 1976567 to cc20e34 Compare May 24, 2019 10:24
@access2rohit access2rohit changed the title [WIP][MXNET-1410]Adding Large Tensor Support for tensor transpose [MXNET-1410]Adding Large Tensor Support for tensor transpose May 24, 2019
samskalicky
samskalicky approved these changes May 24, 2019
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LGTM

apeforest
apeforest reviewed May 24, 2019
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Comment thread src/operator/tensor/matrix_op-inl.h Outdated
struct reverse {
MSHADOW_XINLINE static int ReverseIndex(index_t idx,
MSHADOW_XINLINE static index_t ReverseIndex(index_t idx,
index_t nreversedim,
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@apeforest apeforest May 24, 2019

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nit: indent

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@access2rohit access2rohit May 24, 2019

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my bad .. will fix it

apeforest
apeforest reviewed May 24, 2019
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Comment thread tests/nightly/test_large_array.py Outdated
apeforest
apeforest reviewed May 24, 2019
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Comment thread tests/nightly/test_large_array.py
t = b.T
assert t.shape == (SMALL_Y, LARGE_X)
assert np.sum(t[:,-1].asnumpy() == LARGE_X) == b.shape[1]
t = nd.swapaxes(b, dim1=0, dim2=1)
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test transpose instead?

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@access2rohit access2rohit May 24, 2019

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These are 3 different transpose operations all three are tested

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@apeforest apeforest May 24, 2019

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I thought transpose is a operator name? If you are testing swapaxes, maybe change the test name as well?

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flip(), swapaxes() and b.T are all transpose operations

apeforest
apeforest reviewed May 24, 2019
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Comment thread tests/nightly/test_large_array.py
t = nd.swapaxes(b, dim1=0, dim2=1)
assert t.shape == (SMALL_Y, LARGE_X)
assert np.sum(t[:,-1].asnumpy() == LARGE_X) == b.shape[1]
t = nd.flip(b, axis=0)
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@apeforest apeforest May 24, 2019

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test this operator in separate?

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@access2rohit access2rohit May 24, 2019

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same as above

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try test operator invidually to avoid collateral failures.

@access2rohit access2rohit force-pushed the lts_transpose branch 3 times, most recently from d5443f0 to e678461 Compare May 29, 2019 18:16
apeforest
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Comment thread tests/nightly/test_large_array.py Outdated
assert_almost_equal(r.asnumpy(), np.diag(a_np, k=k))


def create_large_tensor():
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can we make this method more generic, so user can pass in values to create tensors with different dimension? Also, if it is limited to a 2D tensor, maybe you want to rename the method too.

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this is currently generic to 2D tensor. Can be used for other tests will update that in a separate PR. Apart from this do you think its good to go ?

apeforest
apeforest reviewed May 31, 2019
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Comment thread tests/nightly/test_large_array.py
apeforest
apeforest approved these changes May 31, 2019
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LGTM

@apeforest apeforest merged commit 99e69e6 into apache:master Jun 2, 2019
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roywei commented Jun 3, 2019

@access2rohit @apeforest this is causing nightly to fail on test large tensors
http://jenkins.mxnet-ci.amazon-ml.com/blue/organizations/jenkins/NightlyTestsForBinaries/detail/master/333/changes

@roywei roywei mentioned this pull request Jun 4, 2019
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haohuanw pushed a commit to haohuanw/incubator-mxnet that referenced this pull request Jun 23, 2019
@access2rohit
[MXNET-1410]Adding Large Tensor Support for tensor transpose (apache#…
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…15059)
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@samskalicky samskalicky samskalicky approved these changes

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