added checks to cudnn Convolution for stride, dilation, kernel size and num input planes #1723

alykhantejani · 2017-06-05T11:25:26Z

Added checks for stride, dilation, kernel sizes and num input planes for cuda convolutions (issue #1406)

…nd num input planes

torch/csrc/cudnn/Conv.cpp

  }
  params.groups = groups;
+
+  for (int i = 2; i != input->nDimension; ++i) {
+    int kernel_size = params.weight_size[i];


colesbury · 2017-06-05T16:29:07Z

Adding additional checks here seems okay, but doesn't fix the issue referred to in #1406. The CHECK_ARG error message is very minimal: that's because its used for checking internal invariants, not mistakes that the user might make.

We need something like SpatialConvolutionMM_shapeCheck for cuDNN convolutions, especially the check that for a given input the output size is > 0.

alykhantejani · 2017-06-05T16:38:53Z

I think what @soumith is saying here is that the kernel_size > 0 checks here are pointless, as the weight tensor is already created so the sizes must be > 0.

However, I agree CHECK_ARG is too minimal and still doesn't give a good error message. I also don't check for the case that you mention @colesbury.

Perhaps I should create a Convolution_shapeCheck function in csrc/cudnn/Conv.cpp and call it from the constructor, in there I can mimic SpatialConvolutionMM_shapeCheck and throw runtime errors with more meaningful messages?

If you guys agree, I'll just do this on this branch then?

colesbury · 2017-06-05T16:43:54Z

Yeah, that seems like a good idea

alykhantejani · 2017-06-06T17:44:57Z

@soumith @colesbury I think this should now contain all the checks we need. Let me know if I've missed anything

soumith · 2017-06-06T19:42:18Z

thanks @alykhantejani !

…b9fdd5 Summary: Previous import was 8384c788939bc65463f9754b6a7a00b212b18ba1 Included changes: - **[7abd834](onnx/onnx@7abd834)**: Clarify some aspects of the Loop spec. (pytorch#1587) <Scott McKay> - **[5a5b15f](onnx/onnx@5a5b15f)**: Support rtol and atol at the model granularity (pytorch#1723) <Lu Fang> - **[ba76e45](onnx/onnx@ba76e45)**: print some information (pytorch#1724) <Lu Fang> - **[797390d](onnx/onnx@797390d)**: Update README.md (pytorch#1722) <Prasanth Pulavarthi> - **[40cdb5f](onnx/onnx@40cdb5f)**: repaire convtranspose shape inference (pytorch#1660) <peter yang> - **[68fdb3f](onnx/onnx@68fdb3f)**: [Minor] Fix Windows line ending in test coverage generating script (pytorch#1717) <Raymond Yang> - **[00101bf](onnx/onnx@00101bf)**: Remove ConstantLike op. Updates to ConstantOfShape op. (pytorch#1716) <Spandan Tiwari> - **[c59e90a](onnx/onnx@c59e90a)**: add a shape inference test for group conv (pytorch#1719) <Lu Fang> Reviewed By: zrphercule Differential Revision: D13629499 fbshipit-source-id: 61d4b30be2018f6b1e39a6acf9d80f8a5f26d7fc

…b9fdd5 (#15942) Summary: Pull Request resolved: #15942 Previous import was 8384c788939bc65463f9754b6a7a00b212b18ba1 Included changes: - **[7abd834](onnx/onnx@7abd834)**: Clarify some aspects of the Loop spec. (#1587) <Scott McKay> - **[5a5b15f](onnx/onnx@5a5b15f)**: Support rtol and atol at the model granularity (#1723) <Lu Fang> - **[ba76e45](onnx/onnx@ba76e45)**: print some information (#1724) <Lu Fang> - **[797390d](onnx/onnx@797390d)**: Update README.md (#1722) <Prasanth Pulavarthi> - **[40cdb5f](onnx/onnx@40cdb5f)**: repaire convtranspose shape inference (#1660) <peter yang> - **[68fdb3f](onnx/onnx@68fdb3f)**: [Minor] Fix Windows line ending in test coverage generating script (#1717) <Raymond Yang> - **[00101bf](onnx/onnx@00101bf)**: Remove ConstantLike op. Updates to ConstantOfShape op. (#1716) <Spandan Tiwari> - **[c59e90a](onnx/onnx@c59e90a)**: add a shape inference test for group conv (#1719) <Lu Fang> Reviewed By: zrphercule Differential Revision: D13629499 fbshipit-source-id: 4b3e4cb29bdb84c3777a8fb26263548efb20f317

…orch#1723)

Syncing nvfuser devel branch to upstream master. https://github.com/csarofeen/pytorch/ A few bigger updates: 1. Initial support of cp.async and cp.async.wait: csarofeen#1619 2. Emulate ampere's mma 16816 with Turing's mma 1688, for a unified interface: csarofeen#1643 3. Extending the infrastructure to support mma operators on turing and ampere arch: csarofeen#1440 Commits that's actually in this PR from the csarofeen branch ``` * dd23252 (csarofeen/devel) Fusion Segmenter: Unify single kernel and multi-kernel runtime path (#1710) * b3d1c3f Fix missing cooperative launch (#1726) * dc670a2 Async gmem copy support on sm80+ (#1619) * 5e6a8da Add turing mma support and test (#1643) * d6d6b7d Fix rFactor when there are indirect root domain(s), and refactor (#1723) * 7093e39 Mma op integration on ampere (#1440) * fade8da patch python test for bfloat16 (#1724) * 8fbd0b1 Fine-grained kernel profiling (#1720) * 77c1b4f Adding dry run mode to skip arch dependent checks (#1702) * 151d95b More precise concretization analysis (#1719) * f4d3630 Enable complex python tests (#1667) * 4ceeee5 Minor bugfix in transform_rfactor.cpp (#1715) * 3675c70 Separate root domain and rfactor domain in TransformPrinter (#1716) * f68b830 Fix scheduling with polymorphic broadcast (#1714) * 4ab5ef7 updating_ci_machine (#1718) * 56585c5 Merge pull request #1711 from csarofeen/upstream_master_bump_0517 * 174d453 Allow using nvFuser on CUDA extension (#1701) * 18bee67 Validate LOOP concrete IDs have complete IterDomains (#1676) ``` Pull Request resolved: #78244 Approved by: https://github.com/csarofeen, https://github.com/malfet

Summary: Syncing nvfuser devel branch to upstream master. https://github.com/csarofeen/pytorch/ A few bigger updates: 1. Initial support of cp.async and cp.async.wait: csarofeen#1619 2. Emulate ampere's mma 16816 with Turing's mma 1688, for a unified interface: csarofeen#1643 3. Extending the infrastructure to support mma operators on turing and ampere arch: csarofeen#1440 Commits that's actually in this PR from the csarofeen branch ``` * dd23252 (csarofeen/devel) Fusion Segmenter: Unify single kernel and multi-kernel runtime path (#1710) * b3d1c3f Fix missing cooperative launch (#1726) * dc670a2 Async gmem copy support on sm80+ (#1619) * 5e6a8da Add turing mma support and test (#1643) * d6d6b7d Fix rFactor when there are indirect root domain(s), and refactor (#1723) * 7093e39 Mma op integration on ampere (#1440) * fade8da patch python test for bfloat16 (#1724) * 8fbd0b1 Fine-grained kernel profiling (#1720) * 77c1b4f Adding dry run mode to skip arch dependent checks (#1702) * 151d95b More precise concretization analysis (#1719) * f4d3630 Enable complex python tests (#1667) * 4ceeee5 Minor bugfix in transform_rfactor.cpp (#1715) * 3675c70 Separate root domain and rfactor domain in TransformPrinter (#1716) * f68b830 Fix scheduling with polymorphic broadcast (#1714) * 4ab5ef7 updating_ci_machine (#1718) * 56585c5 Merge pull request #1711 from csarofeen/upstream_master_bump_0517 * 174d453 Allow using nvFuser on CUDA extension (#1701) * 18bee67 Validate LOOP concrete IDs have complete IterDomains (#1676) ``` Pull Request resolved: #78244 Reviewed By: ejguan Differential Revision: D36678948 Pulled By: davidberard98 fbshipit-source-id: 0ccde965acbd31da67d99c6adb2eaaa888948105

added checks to cudnn Convolution for stride, dilation, kernel size a…

7efd8d7

…nd num input planes

soumith reviewed Jun 5, 2017

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torch/csrc/cudnn/Conv.cpp Outdated

}

params.groups = groups;

for (int i = 2; i != input->nDimension; ++i) {

int kernel_size = params.weight_size[i];

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add convolution_shape_checks for cudnn convs

8abca10

soumith merged commit c6a6391 into pytorch:master Jun 6, 2017

houseroad mentioned this pull request Jan 10, 2019

Automatic update of fbcode/onnx to 7abd834091f1024c11749dcfd25126802db9fdd5 #15942

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ezyang added the open source label Jun 24, 2019

jjsjann123 pushed a commit to jjsjann123/pytorch that referenced this pull request May 24, 2022

Fix rFactor when there are indirect root domain(s), and refactor (pyt…

d6d6b7d

…orch#1723)

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added checks to cudnn Convolution for stride, dilation, kernel size and num input planes #1723

added checks to cudnn Convolution for stride, dilation, kernel size and num input planes #1723

alykhantejani commented Jun 5, 2017

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colesbury commented Jun 5, 2017

alykhantejani commented Jun 5, 2017

colesbury commented Jun 5, 2017

alykhantejani commented Jun 6, 2017

soumith commented Jun 6, 2017

added checks to cudnn Convolution for stride, dilation, kernel size and num input planes #1723

added checks to cudnn Convolution for stride, dilation, kernel size and num input planes #1723

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alykhantejani commented Jun 5, 2017

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colesbury commented Jun 5, 2017

alykhantejani commented Jun 5, 2017

colesbury commented Jun 5, 2017

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soumith commented Jun 6, 2017