Improve compatibility with Torch7 #738
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Can you please revert the changes to Linear and Padding? We don't support non-batched mode anymore, so |
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Then we need something in load_lua that converts networks to batched mode, but I am not sure that it can be always done automatically. Or should we leave people on their own to patch their networks? |
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What kind of conversions are needed? I don't think there's anything special to do, is there? |
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Without all my modifications here, several Eugenio's networks won't work. They have Padding.nInputDim=3 and Padding.index=1 (1-based Torch indexes), so Padding.index has to become 2, because the input is 4D instead of 3D. Then they have a View to 1D, followed by a Linear. |
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All our nets were trained in batch mode, and even just having a small converter code will be enough, as long as it works |
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@pytorchbot add to whitelist |
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…9c90c8 Previous import was a4dcc47791eb127652f5aaddd51d8896d446a067 Included changes: - **[985af3f](onnx/onnx@985af3f)**: Update PythonAPIOverview.md (pytorch#738) <Dmytro Dzhulgakov> - **[b69be33](onnx/onnx@b69be33)**: Add backend test for upsample (pytorch#729) <Sebastian Meßmer> - **[0d9496e](onnx/onnx@0d9496e)**: Input test data of concat op should be float (pytorch#711) <Changming Sun> - **[20bcb8b](onnx/onnx@20bcb8b)**: Fix the spec for batchnorm and instancenorm (pytorch#733) <Lu Fang> - **[c9f825f](onnx/onnx@c9f825f)**: Refine a little bit about op spec. (pytorch#666) <Ke Zhang> - **[a484eb2](onnx/onnx@a484eb2)**: Fix an error in Conv doc (pytorch#731) <Lu Fang> - **[7410cc4](onnx/onnx@7410cc4)**: Fix incorrect package output paths (pytorch#730) <bddppq> - **[be546e2](onnx/onnx@be546e2)**: Improve optimizer's API and docs (pytorch#713) <Lu Fang> - **[c61506f](onnx/onnx@c61506f)**: Fix the shape inference python API (pytorch#716) <Lu Fang> - **[e9d4134](onnx/onnx@e9d4134)**: Fix cmake on windows when not building python extension (pytorch#728) <bddppq> - **[72187aa](onnx/onnx@72187aa)**: Add value_info support in make_graph (pytorch#726) <Lu Fang> - **[67b7d89](onnx/onnx@67b7d89)**: Fix gen_proto in cmake (pytorch#719) <bddppq> - **[fcb4ae3](onnx/onnx@fcb4ae3)**: docs rewording: Important Python Functions -> Python API Overview (pytorch#721) <anderspapitto> - **[24275d6](onnx/onnx@24275d6)**: Ignore .eggs directory when doing lint (pytorch#722) <bddppq> - **[54be8fa](onnx/onnx@54be8fa)**: Use cmake3 if it's available (pytorch#718) <bddppq> - **[b8c4238](onnx/onnx@b8c4238)**: Add python function docs (pytorch#714) <Lu Fang> - **[e177493](onnx/onnx@e177493)**: Remove unused cmake utils (pytorch#712) <bddppq> - **[72d6ad6](onnx/onnx@72d6ad6)**: Remove pycmd from CMake (pytorch#710) <bddppq> - **[93f0d40](onnx/onnx@93f0d40)**: Fix windows local build (pytorch#709) <Raymond Yang> - **[6734224](onnx/onnx@6734224)**: CMake fixes and setup.py cleanup (pytorch#706) <bddppq> - **[7f6a4fd](onnx/onnx@7f6a4fd)**: Add docs to explain important functions in ONNX Infra (pytorch#682) <Lu Fang> - **[f0f6b3d](onnx/onnx@f0f6b3d)**: fix hardmax test cases make output dtype same as input (pytorch#705) <Wenhao Hu> - **[c970f0c](onnx/onnx@c970f0c)**: Fix the Dummy backend (pytorch#701) <Lu Fang> - **[2af45df](onnx/onnx@2af45df)**: setup.py uses cmake build system (pytorch#606) <anderspapitto> - **[dfcaade](onnx/onnx@dfcaade)**: clean up unused variable left by removing consumed_input (pytorch#697) <bddppq> - **[accfc74](onnx/onnx@accfc74)**: Remove incorrect backend test (pytorch#700) <Lu Fang> - **[e558732](onnx/onnx@e558732)**: add max inclusive version to defs.get_schema function (pytorch#695) <Wenhao Hu> - **[16f02eb](onnx/onnx@16f02eb)**: add API to add domain to min/max version for extension. (pytorch#694) <Ke Zhang> - **[3e560dd](onnx/onnx@3e560dd)**: Fix doc for initializer (pytorch#690) <bddppq> - **[6cc4f53](onnx/onnx@6cc4f53)**: Add model save function (pytorch#692) <Lu Fang> - **[21eaf9b](onnx/onnx@21eaf9b)**: Changing the string discussing versions in operator specifications. (pytorch#691) <Niklas Gustafsson> - **[3b0cdf4](onnx/onnx@3b0cdf4)**: Minor code quality improvements in optimizer/ (pytorch#612) <Sebastian Meßmer> - **[641f126](onnx/onnx@641f126)**: Fix Gemm doc wording (pytorch#689) <bddppq> - **[4a0ec75](onnx/onnx@4a0ec75)**: Clarifies installation error message when external protobuf dependencies are missing (pytorch#684) <Daniel J. H> - **[960a2c3](onnx/onnx@960a2c3)**: Check outputs dtype in backend tests (pytorch#567) <bddppq> - **[1d7dee4](onnx/onnx@1d7dee4)**: Fix Average pool test cases converted from PyTorch (pytorch#677) <Lu Fang> - **[36d7fff](onnx/onnx@36d7fff)**: Fix Attribute default value pybind11 binding (pytorch#671) <bddppq> - **[0536866](onnx/onnx@0536866)**: git ignore .pytest_cache (pytorch#674) <bddppq> - **[afc84ac](onnx/onnx@afc84ac)**: Update README.md (pytorch#672) <Dmytro Dzhulgakov> - **[9d2b530](onnx/onnx@9d2b530)**: Revert "[Typing 1/3] Setup mypy type checker (pytorch#607)" (pytorch#667) <bddppq> - **[086727e](onnx/onnx@086727e)**: [Typing 1/3] Setup mypy type checker (pytorch#607) <Sebastian Meßmer> - **[5716e20](onnx/onnx@5716e20)**: Convert all Node tests to Model tests (pytorch#651) <bddppq> - **[6fe932a](onnx/onnx@6fe932a)**: Replace unittest.skip with custom exception (pytorch#659) <Dmytro Dzhulgakov> - **[ecac1c1](onnx/onnx@ecac1c1)**: Merge Rel 1.1.0 branch into master (pytorch#657) <Anirudh> - **[5cb999d](onnx/onnx@5cb999d)**: Minor cleanups to shape inference (pytorch#653) <anderspapitto> - **[f4acf28](onnx/onnx@f4acf28)**: Remove allowconsumed enforceconsumed from op schema. (pytorch#617) <Ke Zhang> - **[a8e4648](onnx/onnx@a8e4648)**: Adjust link flags when built in Windows Debug mode (pytorch#647) <Yinghai Lu> - **[7c009fe](onnx/onnx@7c009fe)**: Fix lint error in optimizer test (pytorch#656) <bddppq> - **[063d12f](onnx/onnx@063d12f)**: Fix optimizer split pass for models with constant output (pytorch#652) <bddppq>
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…ane() (pytorch#738) * Fix wrong pointer type * Rename type trait get_unsigned_int<> to get_carrier<> * Add 3-bytes carrier type * Add missing __device__ specifier * Rename template non-type parameter * Leave the rest byte uninitialized * Avoid invoking (host) STL algorithms * Remove unnecessary 'inline' specifier * Extract common logic out as helper method * Hide dummy member function * Add missing __device__ specifier
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Some torch7 networks did not run. These are some fixes as described here:
https://discuss.pytorch.org/t/convert-import-torch-model-to-pytorch/37/7