Minor fix in COCO dataset #1
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thanks! |
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just fyi, i am working on CIFAR10/CIFAR100 as we speak. If you are working on any dataset, open an issue before-hand, so that we dont overlap |
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* adding base files * setup modification to actually build the thing * video api constructor registration * FAIL metadata * FAIL update for QS * revert * debugging with Victor * adding base files * setup modification to actually build the thing * video api constructor registration * FAIL metadata * FAIL update for QS * revert * debugging with Victor * metadata registration works * API build next * test * Merge change * formatting parameters to avoid the segfault * next now works on a video * make size of the output tensor format dependent * Make next work on audio stream only as well * refactoring the _setCurrentStream param * Fixing the last frame return and sensor * todo docs * Formatting * cleanup and comments * introducing new tests for the API * cleanup * Comment out unnecesary format (will add following FFMPEG fix) * Reformat parsing function * removing the seek bug `get_decoder_params` * Removing unnecessary code/variables * enforce RGB24 as a reading format (will crash before ffmpeg fix) * permute the dimensions to return (RGB x H x W) * Changing the return type to std::tuple<torch::Tensor, double> as opposed to tensor list * Adjusting tests for the new return type * remove unnecessary jitter * clangangangang * Metadata return changes (#1) * remove implicit calls to set a current stream (#2) * Adding new tests to check the accuracy of the seek * cleanup debugging statements * adding base files * setup modification to actually build the thing * video api constructor registration * FAIL metadata * FAIL update for QS * revert * debugging with Victor * adding base files * video api constructor registration * FAIL metadata * FAIL update for QS * revert * debugging with Victor * metadata registration works * API build next * test * Merge change * formatting parameters to avoid the segfault * next now works on a video * make size of the output tensor format dependent * Make next work on audio stream only as well * refactoring the _setCurrentStream param * Fixing the last frame return and sensor * todo docs * Formatting * cleanup and comments * introducing new tests for the API * cleanup * Comment out unnecesary format (will add following FFMPEG fix) * Reformat parsing function * removing the seek bug `get_decoder_params` * Removing unnecessary code/variables * enforce RGB24 as a reading format (will crash before ffmpeg fix) * permute the dimensions to return (RGB x H x W) * Changing the return type to std::tuple<torch::Tensor, double> as opposed to tensor list * Adjusting tests for the new return type * remove unnecessary jitter * clangangangang * Metadata return changes (#1) * remove implicit calls to set a current stream (#2) * Adding new tests to check the accuracy of the seek * cleanup debugging statements * Addressing PR comments * addressing Francisco's comments * CLANG build formatting * Updated testing to test against pyav for the video tensor reads * Formatting * remove pyav from pip deps and add it to conda build * add pyav and ffmeped to conda builds * Formatting? * Setting up linter once and for all hopefully * Testing pyav * Fix to 8.0.0 * Try 6.2.0 * See what happens with av from pip * Remove FFMPEG blocker * What is going on? * More tests * Forgot something * unblocker * Check if cache is messing up with things * Now try with different ffmpeg * Now try with different ffmpeg * Testing pyav * Fix to 8.0.0 * Try 6.2.0 * See what happens with av from pip * What is going on? * More tests * Forgot something * Check if cache is messing up with things * Now try with different ffmpeg * Now try with different ffmpeg * Do not install av * Test with ffmpeg 4.2 * clean up video tests * cleaning up the tests a bit to better test partial reading * arrgh linter * Forgot the av test * forgot av test * checkout build files from master * revert circleci * addressing Franciscos comments * addressing Franciscos comments * Ignore ffmpeg in travis Co-authored-by: Francisco Massa <[email protected]> Co-authored-by: Edgar Andrés Margffoy Tuay <[email protected]>
bryant1410
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Nov 22, 2020
* adding base files * setup modification to actually build the thing * video api constructor registration * FAIL metadata * FAIL update for QS * revert * debugging with Victor * adding base files * setup modification to actually build the thing * video api constructor registration * FAIL metadata * FAIL update for QS * revert * debugging with Victor * metadata registration works * API build next * test * Merge change * formatting parameters to avoid the segfault * next now works on a video * make size of the output tensor format dependent * Make next work on audio stream only as well * refactoring the _setCurrentStream param * Fixing the last frame return and sensor * todo docs * Formatting * cleanup and comments * introducing new tests for the API * cleanup * Comment out unnecesary format (will add following FFMPEG fix) * Reformat parsing function * removing the seek bug `get_decoder_params` * Removing unnecessary code/variables * enforce RGB24 as a reading format (will crash before ffmpeg fix) * permute the dimensions to return (RGB x H x W) * Changing the return type to std::tuple<torch::Tensor, double> as opposed to tensor list * Adjusting tests for the new return type * remove unnecessary jitter * clangangangang * Metadata return changes (pytorch#1) * remove implicit calls to set a current stream (pytorch#2) * Adding new tests to check the accuracy of the seek * cleanup debugging statements * adding base files * setup modification to actually build the thing * video api constructor registration * FAIL metadata * FAIL update for QS * revert * debugging with Victor * adding base files * video api constructor registration * FAIL metadata * FAIL update for QS * revert * debugging with Victor * metadata registration works * API build next * test * Merge change * formatting parameters to avoid the segfault * next now works on a video * make size of the output tensor format dependent * Make next work on audio stream only as well * refactoring the _setCurrentStream param * Fixing the last frame return and sensor * todo docs * Formatting * cleanup and comments * introducing new tests for the API * cleanup * Comment out unnecesary format (will add following FFMPEG fix) * Reformat parsing function * removing the seek bug `get_decoder_params` * Removing unnecessary code/variables * enforce RGB24 as a reading format (will crash before ffmpeg fix) * permute the dimensions to return (RGB x H x W) * Changing the return type to std::tuple<torch::Tensor, double> as opposed to tensor list * Adjusting tests for the new return type * remove unnecessary jitter * clangangangang * Metadata return changes (pytorch#1) * remove implicit calls to set a current stream (pytorch#2) * Adding new tests to check the accuracy of the seek * cleanup debugging statements * Addressing PR comments * addressing Francisco's comments * CLANG build formatting * Updated testing to test against pyav for the video tensor reads * Formatting * remove pyav from pip deps and add it to conda build * add pyav and ffmeped to conda builds * Formatting? * Setting up linter once and for all hopefully * Testing pyav * Fix to 8.0.0 * Try 6.2.0 * See what happens with av from pip * Remove FFMPEG blocker * What is going on? * More tests * Forgot something * unblocker * Check if cache is messing up with things * Now try with different ffmpeg * Now try with different ffmpeg * Testing pyav * Fix to 8.0.0 * Try 6.2.0 * See what happens with av from pip * What is going on? * More tests * Forgot something * Check if cache is messing up with things * Now try with different ffmpeg * Now try with different ffmpeg * Do not install av * Test with ffmpeg 4.2 * clean up video tests * cleaning up the tests a bit to better test partial reading * arrgh linter * Forgot the av test * forgot av test * checkout build files from master * revert circleci * addressing Franciscos comments * addressing Franciscos comments * Ignore ffmpeg in travis Co-authored-by: Francisco Massa <[email protected]> Co-authored-by: Edgar Andrés Margffoy Tuay <[email protected]>
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facebook-github-bot
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… to conform with non-quantized countertpart filenames (#77037) Summary: X-link: pytorch/pytorch#77037 Names of analogous files in quantized directory (previously snake case) were inconsistent with their non-quantized filename counterparts (pascal case). This is the first of a series of PRs that changes all files in quantized (and sub-directories) dir to have pascal case. `aten/src/ATen/native/quantized/qconv_unpack.cpp` has not been renamed yet because (for reasons currently unknown) after making the name change, `import torch` produces the below error (`qlinear_unpack.cpp` renaming also seems to fail some phabricator CI tests for similar reasons). We suspect that these may be undefined errors and will revisit naming these files in a future PR. ``` terminate called after throwing an instance of 'c10::Error' what(): Type c10::intrusive_ptr<ConvPackedParamsBase<2> > could not be converted to any of the known types. Exception raised from operator() at ../aten/src/ATen/core/jit_type.h:1735 (most recent call first): frame #0: c10::Error::Error(c10::SourceLocation, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >) + 0x55 (0x7f26745c0c65 in /data/users/dzdang/pytorch/torch/lib/libc10.so) frame #1: c10::detail::torchCheckFail(char const*, char const*, unsigned int, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&) + 0xb1 (0x7f26745bdcd1 in /data/users/dzdang/pytorch/torch/lib/libc10.so) frame #2: <unknown function> + 0x1494e24 (0x7f2663b14e24 in /data/users/dzdang/pytorch/torch/lib/libtorch_cpu.so) frame #3: <unknown function> + 0xfed0bc (0x7f266366d0bc in /data/users/dzdang/pytorch/torch/lib/libtorch_cpu.so) frame #4: c10::detail::infer_schema::make_function_schema(std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >&&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >&&, c10::ArrayRef<c10::detail::infer_schema::ArgumentDef>, c10::ArrayRef<c10::detail::infer_schema::ArgumentDef>) + 0x5a (0x7f266366d71a in /data/users/dzdang/pytorch/torch/lib/libtorch_cpu.so) frame #5: c10::detail::infer_schema::make_function_schema(c10::ArrayRef<c10::detail::infer_schema::ArgumentDef>, c10::ArrayRef<c10::detail::infer_schema::ArgumentDef>) + 0x7b (0x7f266366e06b in /data/users/dzdang/pytorch/torch/lib/libtorch_cpu.so) frame #6: <unknown function> + 0x1493f32 (0x7f2663b13f32 in /data/users/dzdang/pytorch/torch/lib/libtorch_cpu.so) frame #7: <unknown function> + 0xe227dd (0x7f26634a27dd in /data/users/dzdang/pytorch/torch/lib/libtorch_cpu.so) frame #8: <unknown function> + 0x14e0a (0x7f268c934e0a in /lib64/ld-linux-x86-64.so.2) ..........................truncated............. ``` Reviewed By: malfet Differential Revision: D36862332 Pulled By: dzdang fbshipit-source-id: 598c36656b4e71f906d940e7ff19ecf82d43031d
datumbox
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…zed directory… (#6133) * [quant][core][better-engineering] Rename files in quantized directory to conform with non-quantized countertpart filenames (#77037) Summary: X-link: pytorch/pytorch#77037 Names of analogous files in quantized directory (previously snake case) were inconsistent with their non-quantized filename counterparts (pascal case). This is the first of a series of PRs that changes all files in quantized (and sub-directories) dir to have pascal case. `aten/src/ATen/native/quantized/qconv_unpack.cpp` has not been renamed yet because (for reasons currently unknown) after making the name change, `import torch` produces the below error (`qlinear_unpack.cpp` renaming also seems to fail some phabricator CI tests for similar reasons). We suspect that these may be undefined errors and will revisit naming these files in a future PR. ``` terminate called after throwing an instance of 'c10::Error' what(): Type c10::intrusive_ptr<ConvPackedParamsBase<2> > could not be converted to any of the known types. Exception raised from operator() at ../aten/src/ATen/core/jit_type.h:1735 (most recent call first): frame #0: c10::Error::Error(c10::SourceLocation, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >) + 0x55 (0x7f26745c0c65 in /data/users/dzdang/pytorch/torch/lib/libc10.so) frame #1: c10::detail::torchCheckFail(char const*, char const*, unsigned int, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&) + 0xb1 (0x7f26745bdcd1 in /data/users/dzdang/pytorch/torch/lib/libc10.so) frame #2: <unknown function> + 0x1494e24 (0x7f2663b14e24 in /data/users/dzdang/pytorch/torch/lib/libtorch_cpu.so) frame #3: <unknown function> + 0xfed0bc (0x7f266366d0bc in /data/users/dzdang/pytorch/torch/lib/libtorch_cpu.so) frame #4: c10::detail::infer_schema::make_function_schema(std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >&&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >&&, c10::ArrayRef<c10::detail::infer_schema::ArgumentDef>, c10::ArrayRef<c10::detail::infer_schema::ArgumentDef>) + 0x5a (0x7f266366d71a in /data/users/dzdang/pytorch/torch/lib/libtorch_cpu.so) frame #5: c10::detail::infer_schema::make_function_schema(c10::ArrayRef<c10::detail::infer_schema::ArgumentDef>, c10::ArrayRef<c10::detail::infer_schema::ArgumentDef>) + 0x7b (0x7f266366e06b in /data/users/dzdang/pytorch/torch/lib/libtorch_cpu.so) frame #6: <unknown function> + 0x1493f32 (0x7f2663b13f32 in /data/users/dzdang/pytorch/torch/lib/libtorch_cpu.so) frame #7: <unknown function> + 0xe227dd (0x7f26634a27dd in /data/users/dzdang/pytorch/torch/lib/libtorch_cpu.so) frame #8: <unknown function> + 0x14e0a (0x7f268c934e0a in /lib64/ld-linux-x86-64.so.2) ..........................truncated............. ``` Reviewed By: malfet Differential Revision: D36862332 Pulled By: dzdang fbshipit-source-id: 598c36656b4e71f906d940e7ff19ecf82d43031d * empty commit * empty commit * empty commit Co-authored-by: dzdang <[email protected]> Co-authored-by: Vasilis Vryniotis <[email protected]>
rajveerb
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* [BERT] fixing input pipeline and layer norm namescope * [BERT] input preprocessing for tf2 model, seperating training and eval sets * [BERT] small corrections to README.md * Shell script to download and extract, V0.7 README * Minor fix to README * [BERT] small fixes to tpu library imports * [BERT] Gradient accumulation for TF1 * Fixing git SHA and nltk versions * [BERT] redirect seperated dataset changes to TF1 * [BERT] revert back run commands * [BERT] uncommand process_wiki.sh * [BERT] remove 3M starting eval requirement and update target accuracy to 0.720 * [BERT] delete unused files * [BERT] add MLPerf logging * [BERT] small corrections * [BERT] update eval frequency * [BERT] provides dataset after preprocessing, and move the related details to dataset.md * [BERT] small corrections * [BERT] update HPs for BS24 on V100x8, and add BS8k running steps on TPUs * [BERT] update README to give more details about how to use eval * [BERT] Readme update for eval * Revert "Merge pull request pytorch#1 from aarti-cerebras/v0.7_readme" This reverts commit 9974ac9d6d6bf0b3ceaf22d4d86c1f5f25ba26e4, reversing changes made to 563be596bd7f5c38db696e9c34ef29bd477462f7. * Revert "Revert "Merge pull request pytorch#1 from aarti-cerebras/v0.7_readme"" This reverts commit f38ef1626517ae74a3be2895861ee17ee0d699c9. * [BERT] add clip_by_global_norm_after_gradient_allreduce option * [BERT] sample script to run offline eval Co-authored-by: Aarti Ghatkesar <[email protected]>
rajveerb
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Nov 30, 2023
* Update readme * Unet3d update (pytorch#1) * enable multi-gpu training * enable multi-gpu training * enable multi-gpu training * enable multi-gpu training * enable multi-gpu training * test grad acc * test grad acc * test grad acc * fix number of samples logging * test * Add divergence detection * Add divergence detection * Remove debug prints * Remove debug prints * Remove debug prints * Remove debug prints * Remove debug prints * Remove debug prints
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transformswas missing forCOCODetection.