[Docs] Fix docs for torch.chunk #61097
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Add an explanation covering pytorch#9382 and pytorch#36403, refer to torch.tensor_split
Also, modify the warning
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💊 CI failures summary and remediationsAs of commit cebe4b4 (more details on the Dr. CI page and at hud.pytorch.org/pr/61097):
🕵️ 2 new failures recognized by patternsThe following CI failures do not appear to be due to upstream breakages:
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| Job | Step | Action |
|---|---|---|
 Test tools / test |
Install dependencies | 🔁 rerun |
❄️ 1 failure tentatively classified as flaky
but reruns have not yet been triggered to confirm:
pytorch_linux_xenial_cuda11_1_cudnn8_py3_gcc7_test2 (1/1)
Step: "Run tests" (full log | diagnosis details | 🔁 rerun) ❄️
Jul 15 06:03:12 unknown file: Failure
Jul 15 06:03:12 frame #7: build/bin/test_api() [0xc0b8c5]
Jul 15 06:03:12 frame #8: build/bin/test_api() [0xc0bb65]
Jul 15 06:03:12 frame #9: testing::internal::UnitTestImpl::RunAllTests() + 0xbf9 (0xc0cba9 in build/bin/test_api)
Jul 15 06:03:12 frame #10: testing::UnitTest::Run() + 0x8f (0xc0ce4f in build/bin/test_api)
Jul 15 06:03:12 frame #11: main + 0xc8 (0x5833a8 in build/bin/test_api)
Jul 15 06:03:12 frame #12: __libc_start_main + 0xf0 (0x7f474b9e3840 in /lib/x86_64-linux-gnu/libc.so.6)
Jul 15 06:03:12 frame #13: _start + 0x29 (0x5b9a19 in build/bin/test_api)
Jul 15 06:03:12 " thrown in the test body.
Jul 15 06:03:12 [ FAILED ] IntegrationTest.MNIST_CUDA (3 ms)
Jul 15 06:03:12 [ RUN ] IntegrationTest.MNISTBatchNorm_CUDA
Jul 15 06:03:12 unknown file: Failure
Jul 15 06:03:12 C++ exception with description "Error opening images file at test/cpp/api/mnist/train-images-idx3-ubyte
Jul 15 06:03:12 Exception raised from read_images at /var/lib/jenkins/workspace/torch/csrc/api/src/data/datasets/mnist.cpp:67 (most recent call first):
Jul 15 06:03:12 frame #0: c10::Error::Error(c10::SourceLocation, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >) + 0x6b (0x7f4765454c6b in /var/lib/jenkins/workspace/build/lib/libc10.so)
Jul 15 06:03:12 frame #1: c10::detail::torchCheckFail(char const*, char const*, unsigned int, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&) + 0xce (0x7f476545047e in /var/lib/jenkins/workspace/build/lib/libc10.so)
Jul 15 06:03:12 frame #2: <unknown function> + 0x42015f2 (0x7f4769aa15f2 in /var/lib/jenkins/workspace/build/lib/libtorch_cpu.so)
Jul 15 06:03:12 frame #3: torch::data::datasets::MNIST::MNIST(std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, torch::data::datasets::MNIST::Mode) + 0x46 (0x7f4769aa2696 in /var/lib/jenkins/workspace/build/lib/libtorch_cpu.so)
Jul 15 06:03:12 frame #4: IntegrationTest_MNISTBatchNorm_CUDA_Test::TestBody() + 0x9d6 (0x7843b6 in build/bin/test_api)
Jul 15 06:03:12 frame #5: void testing::internal::HandleExceptionsInMethodIfSupported<testing::Test, void>(testing::Test*, void (testing::Test::*)(), char const*) + 0x4a (0xc1489a in build/bin/test_api)
Jul 15 06:03:12 frame #6: build/bin/test_api() [0xc0b2d6]
Jul 15 06:03:12 frame #7: build/bin/test_api() [0xc0b8c5]
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@ezyang has imported this pull request. If you are a Facebook employee, you can view this diff on Phabricator. |
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could I trouble you to fix lint |
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Thank you for adding the "see also" for |
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Fixed the errors shown by lint |
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@ezyang has imported this pull request. If you are a Facebook employee, you can view this diff on Phabricator. |
5 participants
torch.chunk may return less than the requested number of chunks silently if some undocumented division constraints are not met. The functionality that users expect is provided by another function: torch.tensor_split
This has led to confusion countless times and who knows how many systems out there are fragile because of this.
My changes describe the discrepancy, show an example and direct users to the usually preferred function.
Issues mentioning this problem:
#9382
torch/torch7#617
I considered documenting the constraint for when an unexpected number of chunks may be returned (it is chunks*chunks>input.size[dim] ), so that users could quickly tell if their code may be affected. Please let me know if you think this should be in the docs or not.