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Add zero grad for npi_unique #18080

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@haojin2 haojin2 commented Apr 16, 2020

Description

Fix for #18074

Checklist

Essentials

Please feel free to remove inapplicable items for your PR.

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

Changes

  • add FGradient registeration

Comments

The script in the issue could pass after this change.

@haojin2 haojin2 added the Numpy label Apr 16, 2020
@haojin2 haojin2 requested a review from sxjscience April 16, 2020 05:10
@haojin2 haojin2 self-assigned this Apr 16, 2020
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leezu commented Apr 16, 2020

@mxnet-bot run ci [unix-gpu]

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Jenkins CI successfully triggered : [unix-gpu]

@haojin2 haojin2 merged commit 5155095 into apache:master Apr 17, 2020
sxjscience pushed a commit to sxjscience/mxnet that referenced this pull request Jun 30, 2020
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ciyongch commented Jul 1, 2020

Hi @haojin2 @sxjscience , could you please help to backport this PR to v1.7.x? thanks!

sxjscience pushed a commit to sxjscience/mxnet that referenced this pull request Jul 1, 2020
TaoLv pushed a commit that referenced this pull request Jul 2, 2020
* add zero grad for npi_unique (#18080)

* fix np.clip scalar input case (#17788)

* fix true_divide (#18393)

Co-authored-by: Hao Jin <hjjn.amzn@gmail.com>
Co-authored-by: Xi Wang <xidulu@gmail.com>
AntiZpvoh pushed a commit to AntiZpvoh/incubator-mxnet that referenced this pull request Jul 6, 2020
leezu pushed a commit to leezu/mxnet that referenced this pull request Oct 1, 2020
* add zero grad for npi_unique (apache#18080)

* fix np.clip scalar input case (apache#17788)

* fix true_divide (apache#18393)

Co-authored-by: Hao Jin <hjjn.amzn@gmail.com>
Co-authored-by: Xi Wang <xidulu@gmail.com>
samskalicky pushed a commit that referenced this pull request Oct 2, 2020
* * Fix einsum gradient (#18482)

* [v1.7.x] Backport PRs of numpy features (#18653)

* add zero grad for npi_unique (#18080)

* fix np.clip scalar input case (#17788)

* fix true_divide (#18393)

Co-authored-by: Hao Jin <hjjn.amzn@gmail.com>
Co-authored-by: Xi Wang <xidulu@gmail.com>

* [v1.7.x] backport mixed type binary ops to v1.7.x (#18649)

* Fix Windows GPU CI (#17962)

Update Windows CI to use VS 2019 and enable x64 bit toolchain. Previously we are using an older 32 bit toolchain causing OOM errors during linking. Switching to x64 bit toolchain on the older VS version previously used by the CI was attempted in #17912 and did not work. Update to Cuda 10.2 as it is required by VS 2019. Switch to ninja-build on Windows to speed up build as ninja-build is now preinstalled. Remove logic to install cmake 3.16 on every PR as cmake 3.17 is now preinstalled. Add build retrials due to cuda thrust + VS2019 flakyness.

Co-authored-by: vexilligera <vexilligera@gmail.com>

* backport mixed type

Co-authored-by: Leonard Lausen <lausen@amazon.com>
Co-authored-by: vexilligera <vexilligera@gmail.com>

* revise activations (#18700)

* [v1.6] Fix the monitor_callback invalid issue during calibration with variable input shapes (#18632) (#18703)

* Fix the monitor_callback invalid issue during calibration with variable input shapes

* retrigger CI

* Add UT for monitor check and disable codecov

Co-authored-by: Tao Lv <tao.a.lv@intel.com>

* Fail build_windows.py if all retries failed (#18177)

* Update to thrust 1.9.8 on Windows (#18218)

* Update to thrust 1.9.8 on Windows

* Remove debug logic

* Re-enable build retries on MSVC (#18230)

Updating thrust alone did not help. Similar issues (though less often) still
occur with updated thrust, and also with nvidia cub. Tracked upstream at
NVIDIA/thrust#1090

Co-authored-by: Ke Han <38852697+hanke580@users.noreply.github.com>
Co-authored-by: Xingjian Shi <xshiab@connect.ust.hk>
Co-authored-by: Hao Jin <hjjn.amzn@gmail.com>
Co-authored-by: Xi Wang <xidulu@gmail.com>
Co-authored-by: Yijun Chen <chenyijun0902@gmail.com>
Co-authored-by: vexilligera <vexilligera@gmail.com>
Co-authored-by: ciyong <ciyong.chen@intel.com>
Co-authored-by: Tao Lv <tao.a.lv@intel.com>
samskalicky pushed a commit to samskalicky/incubator-mxnet that referenced this pull request Oct 2, 2020
* * Fix einsum gradient (apache#18482)

* [v1.7.x] Backport PRs of numpy features (apache#18653)

* add zero grad for npi_unique (apache#18080)

* fix np.clip scalar input case (apache#17788)

* fix true_divide (apache#18393)

Co-authored-by: Hao Jin <hjjn.amzn@gmail.com>
Co-authored-by: Xi Wang <xidulu@gmail.com>

* [v1.7.x] backport mixed type binary ops to v1.7.x (apache#18649)

* Fix Windows GPU CI (apache#17962)

Update Windows CI to use VS 2019 and enable x64 bit toolchain. Previously we are using an older 32 bit toolchain causing OOM errors during linking. Switching to x64 bit toolchain on the older VS version previously used by the CI was attempted in apache#17912 and did not work. Update to Cuda 10.2 as it is required by VS 2019. Switch to ninja-build on Windows to speed up build as ninja-build is now preinstalled. Remove logic to install cmake 3.16 on every PR as cmake 3.17 is now preinstalled. Add build retrials due to cuda thrust + VS2019 flakyness.

Co-authored-by: vexilligera <vexilligera@gmail.com>

* backport mixed type

Co-authored-by: Leonard Lausen <lausen@amazon.com>
Co-authored-by: vexilligera <vexilligera@gmail.com>

* revise activations (apache#18700)

* [v1.6] Fix the monitor_callback invalid issue during calibration with variable input shapes (apache#18632) (apache#18703)

* Fix the monitor_callback invalid issue during calibration with variable input shapes

* retrigger CI

* Add UT for monitor check and disable codecov

Co-authored-by: Tao Lv <tao.a.lv@intel.com>

* Fail build_windows.py if all retries failed (apache#18177)

* Update to thrust 1.9.8 on Windows (apache#18218)

* Update to thrust 1.9.8 on Windows

* Remove debug logic

* Re-enable build retries on MSVC (apache#18230)

Updating thrust alone did not help. Similar issues (though less often) still
occur with updated thrust, and also with nvidia cub. Tracked upstream at
NVIDIA/thrust#1090

Co-authored-by: Ke Han <38852697+hanke580@users.noreply.github.com>
Co-authored-by: Xingjian Shi <xshiab@connect.ust.hk>
Co-authored-by: Hao Jin <hjjn.amzn@gmail.com>
Co-authored-by: Xi Wang <xidulu@gmail.com>
Co-authored-by: Yijun Chen <chenyijun0902@gmail.com>
Co-authored-by: vexilligera <vexilligera@gmail.com>
Co-authored-by: ciyong <ciyong.chen@intel.com>
Co-authored-by: Tao Lv <tao.a.lv@intel.com>
samskalicky added a commit that referenced this pull request Oct 3, 2020
* * Fix einsum gradient (#18482)

* [v1.7.x] Backport PRs of numpy features (#18653)

* add zero grad for npi_unique (#18080)

* fix np.clip scalar input case (#17788)

* fix true_divide (#18393)

Co-authored-by: Hao Jin <hjjn.amzn@gmail.com>
Co-authored-by: Xi Wang <xidulu@gmail.com>

* [v1.7.x] backport mixed type binary ops to v1.7.x (#18649)

* Fix Windows GPU CI (#17962)

Update Windows CI to use VS 2019 and enable x64 bit toolchain. Previously we are using an older 32 bit toolchain causing OOM errors during linking. Switching to x64 bit toolchain on the older VS version previously used by the CI was attempted in #17912 and did not work. Update to Cuda 10.2 as it is required by VS 2019. Switch to ninja-build on Windows to speed up build as ninja-build is now preinstalled. Remove logic to install cmake 3.16 on every PR as cmake 3.17 is now preinstalled. Add build retrials due to cuda thrust + VS2019 flakyness.

Co-authored-by: vexilligera <vexilligera@gmail.com>

* backport mixed type

Co-authored-by: Leonard Lausen <lausen@amazon.com>
Co-authored-by: vexilligera <vexilligera@gmail.com>

* revise activations (#18700)

* [v1.6] Fix the monitor_callback invalid issue during calibration with variable input shapes (#18632) (#18703)

* Fix the monitor_callback invalid issue during calibration with variable input shapes

* retrigger CI

* Add UT for monitor check and disable codecov

Co-authored-by: Tao Lv <tao.a.lv@intel.com>

* Fail build_windows.py if all retries failed (#18177)

* Update to thrust 1.9.8 on Windows (#18218)

* Update to thrust 1.9.8 on Windows

* Remove debug logic

* Re-enable build retries on MSVC (#18230)

Updating thrust alone did not help. Similar issues (though less often) still
occur with updated thrust, and also with nvidia cub. Tracked upstream at
NVIDIA/thrust#1090

Co-authored-by: Ke Han <38852697+hanke580@users.noreply.github.com>
Co-authored-by: Xingjian Shi <xshiab@connect.ust.hk>
Co-authored-by: Hao Jin <hjjn.amzn@gmail.com>
Co-authored-by: Xi Wang <xidulu@gmail.com>
Co-authored-by: Yijun Chen <chenyijun0902@gmail.com>
Co-authored-by: vexilligera <vexilligera@gmail.com>
Co-authored-by: ciyong <ciyong.chen@intel.com>
Co-authored-by: Tao Lv <tao.a.lv@intel.com>

Co-authored-by: Leonard Lausen <lausen@amazon.com>
Co-authored-by: Ke Han <38852697+hanke580@users.noreply.github.com>
Co-authored-by: Xingjian Shi <xshiab@connect.ust.hk>
Co-authored-by: Hao Jin <hjjn.amzn@gmail.com>
Co-authored-by: Xi Wang <xidulu@gmail.com>
Co-authored-by: Yijun Chen <chenyijun0902@gmail.com>
Co-authored-by: vexilligera <vexilligera@gmail.com>
Co-authored-by: ciyong <ciyong.chen@intel.com>
Co-authored-by: Tao Lv <tao.a.lv@intel.com>
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5 participants