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Update runner registration flow based on feedback Enhance security by unmounting and removing runner token file To prevent any potential token leakage, unmount and remove /run/runner_secret immediately after generating the token. This ensures that the token is inaccessible beyond its intended use, even within the job execution.
sandeepgupta12
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Mar 20, 2025
…pytorch#144120) (pytorch#146372) Summary: # Summary ### Sticky points Cuda-graph rng handling has changed / deviated from original implementation. We will be left with a dangling 'offset' val and confusing naming due to BC ## Dependencies - Flash PR: Dao-AILab/flash-attention#1419 ### Other Points - The BC linter is complaining about losing generate.py and its functions which is not real BC surface cc albanD imported-using-ghimport Test Plan: Imported from OSS Building in dev `buck build @//mode/dev-nosan -c fbcode.nvcc_arch=h100a //caffe2:ATen-cu --show-full-output ` I and Nming the .so I do see that the flash symbols are correctly named: ``` 0000000001c3dfb0 t pytorch_flash::run_mha_bwd(pytorch_flash::Flash_bwd_params&, CUstream_st*)::$_0::operator()() const::{lambda()#1}::operator()() const::{lambda()#1}::operator()() const::{lambda()pytorch#7}::operator()() const 0000000001c36080 t pytorch_flash::run_mha_fwd(pytorch_flash::Flash_fwd_params&, CUstream_st*, bool)::$_0::operator()() const::{lambda()#2}::operator()() const::{lambda()#1}::operator()() const::{lambda()pytorch#6}::operator()() const 0000000001c360e0 t pytorch_flash::run_mha_fwd(pytorch_flash::Flash_fwd_params&, CUstream_st*, bool)::$_0::operator()() const::{lambda()#2}::operator()() const::{lambda()#1}::operator()() const::{lambda()pytorch#7}::operator()() const 0000000001c35fc0 t pytorch_flash::run_mha_fwd(pytorch_flash::Flash_fwd_params&, CUstream_st*, bool)::$_0::operator()() const::{lambda()#1}::operator()() const::{lambda()#1}::operator()() const::{lambda()pytorch#6}::operator()() const 0000000001c36020 t pytorch_flash::run_mha_fwd(pytorch_flash::Flash_fwd_params&, CUstream_st*, bool)::$_0::operator()() const::{lambda()#1}::operator()() const::{lambda()#1}::operator()() const::{lambda()pytorch#7}::operator()() const ``` Reviewed By: vkuzo Differential Revision: D68502879 Pulled By: drisspg Pull Request resolved: pytorch#146372 Approved by: https://github.com/jbschlosser
sandeepgupta12
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Mar 27, 2025
Summary:
fix another combo kernel logging error:
File "/home/guorachel/local/fbsource/buck-out/v2/gen/fbcode/4bcbfa3ef39dbd6f/caffe2/test/inductor/__combo_kernels__/combo_kernels#link-tree/torch/_inductor/scheduler.py", line 2036, in _init
self.create_combo_kernel_nodes(num_ck_nodes=None)
File "/home/guorachel/local/fbsource/buck-out/v2/gen/fbcode/4bcbfa3ef39dbd6f/caffe2/test/inductor/__combo_kernels__/combo_kernels#link-tree/torch/_inductor/scheduler.py", line 3068, in create_combo_kernel_nodes
log.debug("ComboKernels: Generating with num_ck_nodes = %d...", num_ck_nodes)
Message: 'ComboKernels: Generating with num_ck_nodes = %d...'
Arguments: (None,)
Test Plan:
Verified in test_combo_kernel.py
the logging error went away.
Differential Revision: D71655949
Pull Request resolved: pytorch#149772
Approved by: https://github.com/ColinPeppler, https://github.com/Skylion007
sandeepgupta12
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Jun 4, 2025
Use uint64_t index types to avoid
```
torch_np/numpy_tests/core/test_einsum.py::TestEinsum::test_einsum_broadcast /var/lib/jenkins/workspace/aten/src/ATen/native/cpu/BlasKernel.cpp:132:24: runtime error: signed integer overflow: 9223365439786057728 + 13194139533312 cannot be represented in type 'long'
#0 0x7f30d26166ba in std::enable_if<std::is_same_v<long, long>, void>::type at::native::cpublas::(anonymous namespace)::gemm_notrans_<long, long, long>(long, long, long, long, long const*, long, long const*, long, long, long*, long) /var/lib/jenkins/workspace/aten/src/ATen/native/cpu/BlasKernel.cpp:132:24
#1 0x7f30d26166ba in void at::native::cpublas::(anonymous namespace)::gemm_core_<long, long, long>(at::native::TransposeType, at::native::TransposeType, long, long, long, long, long const*, long, long const*, long, long, long*, long) /var/lib/jenkins/workspace/aten/src/ATen/native/cpu/BlasKernel.cpp:451:12
#2 0x7f30d25fba1b in at::native::cpublas::(anonymous namespace)::cpublas_gemm_impl(c10::ScalarType, at::native::TransposeType, at::native::TransposeType, long, long, long, c10::Scalar const&, void const*, long, void const*, long, c10::Scalar const&, void*, long)::$_2::operator()() const::'lambda2'()::operator()() const /var/lib/jenkins/workspace/aten/src/ATen/native/cpu/BlasKernel.cpp:485:3
#3 0x7f30d25fba1b in at::native::cpublas::(anonymous namespace)::cpublas_gemm_impl(c10::ScalarType, at::native::TransposeType, at::native::TransposeType, long, long, long, c10::Scalar const&, void const*, long, void const*, long, c10::Scalar const&, void*, long)::$_2::operator()() const /var/lib/jenkins/workspace/aten/src/ATen/native/cpu/BlasKernel.cpp:485:3
```
Pull Request resolved: pytorch#154809
Approved by: https://github.com/soulitzer
sandeepgupta12
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Jun 9, 2025
Vibe-coded with Codex, after collecting a backtrace, see https://chatgpt.com/s/cd_68438be8a1248191adbfa0a5f000e60b Even though, check for empty tensor list exists in `at::cat` crash might happens while resolving named dimension to position, by calling `dimname_to_position(tensors[0], dim)`, see backtrace below ``` (lldb) up frame #1: 0x00000001101146dc libtorch_cpu.dylib`at::TensorBase::has_names(this=0x0000000000000000) const at TensorBase.h:559:10 556 bool has_names() const { 557 // If a user is using unnamed tensors, then we can short-circuit right here. 558 // Otherwise, impl::has_names attempts to retrieve names. -> 559 if (!impl_->has_named_tensor_meta()) { 560 return false; 561 } 562 return impl::has_names(unsafeGetTensorImpl()); (lldb) up frame #2: 0x00000001101144c4 libtorch_cpu.dylib`at::dimname_to_position(tensor=0x0000000000000000, dim=Dimname @ 0x000000016fdfe348) at NamedTensorUtils.cpp:23:3 20 int64_t dimname_to_position(const Tensor& tensor, Dimname dim) { 21 TORCH_CHECK(dim.type() != NameType::WILDCARD, 22 "Please look up dimensions by name, got: name = None."); -> 23 TORCH_CHECK(tensor.has_names(), 24 "Name ", dim, " not found in ", toDimnameRepr(tensor), "."); 25 const auto names = tensor.names(); 26 ``` TODOs: - May be move test from `test_tensor_creation.py` to OpInfo (not sure which one is more readable) - Replace `TORCH_CHECK` with `TORCH_CHECK_VALUE` and adjust unit tests Fixes pytorch#155306 Pull Request resolved: pytorch#155383 Approved by: https://github.com/cyyever, https://github.com/ezyang ghstack dependencies: pytorch#155382
sandeepgupta12
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Jul 28, 2025
For tensor with non-zero offset, it must be multiplied by element size Add regression test by creating Tensor in array of 6 elements with offset 3, which before the fix crashed with ``` C++ exception with description "setStorage: sizes [3, 3], strides [0, 1], storage offset 3, and itemsize 4 requiring a storage size of 24 are out of bounds for storage of size 15 Exception raised from checkInBoundsForStorage at /Users/nshulga/git/pytorch/pytorch/aten/src/ATen/native/Resize.h:123 (most recent call first): frame #0: c10::Error::Error(c10::SourceLocation, std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>) + 56 (0x104a9cd44 in libc10.dylib) frame #1: c10::detail::torchCheckFail(char const*, char const*, unsigned int, std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>> const&) + 120 (0x104a9a05c in libc10.dylib) frame #2: void at::native::checkInBoundsForStorage<long long>(c10::ArrayRef<long long>, c10::ArrayRef<long long>, long long, caffe2::TypeMeta const&, c10::Storage const&) + 656 (0x111dbd314 in libtorch_cpu.dylib) frame #3: void at::native::setStrided<long long>(at::Tensor const&, c10::ArrayRef<long long>, c10::ArrayRef<long long>, long long) + 152 (0x111dcd22c in libtorch_cpu.dylib) frame #4: at::native::as_strided_tensorimpl(at::Tensor const&, c10::ArrayRef<long long>, c10::ArrayRef<long long>, std::__1::optional<long long>) + 312 (0x111dccf98 in libtorch_cpu.dylib) frame pytorch#5: c10::impl::wrap_kernel_functor_unboxed_<c10::impl::detail::WrapFunctionIntoFunctor_<c10::CompileTimeFunctionPointer<at::Tensor (at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, std::__1::optional<c10::SymInt>), &at::(anonymous namespace)::(anonymous namespace)::wrapper_CPU__as_strided(at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, std::__1::optional<c10::SymInt>)>, at::Tensor, c10::guts::typelist::typelist<at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, std::__1::optional<c10::SymInt>>>, at::Tensor (at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, std::__1::optional<c10::SymInt>)>::call(c10::OperatorKernel*, c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, std::__1::optional<c10::SymInt>) + 104 (0x1129a1e94 in libtorch_cpu.dylib) frame pytorch#6: at::_ops::as_strided::call(at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, std::__1::optional<c10::SymInt>) + 476 (0x112200ad0 in libtorch_cpu.dylib) frame pytorch#7: at::Tensor::as_strided(c10::ArrayRef<long long>, c10::ArrayRef<long long>, std::__1::optional<long long>) const + 236 (0x1115db098 in libtorch_cpu.dylib) frame pytorch#8: at::native::expand(at::Tensor const&, c10::ArrayRef<long long>, bool) + 348 (0x111dcc0d4 in libtorch_cpu.dylib) frame pytorch#9: c10::impl::wrap_kernel_functor_unboxed_<c10::impl::detail::WrapFunctionIntoFunctor_<c10::CompileTimeFunctionPointer<at::Tensor (c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, bool), &torch::ADInplaceOrView::(anonymous namespace)::expand(c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, bool)>, at::Tensor, c10::guts::typelist::typelist<c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, bool>>, at::Tensor (c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, bool)>::call(c10::OperatorKernel*, c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, bool) + 116 (0x1157ac410 in libtorch_cpu.dylib) frame pytorch#10: c10::impl::wrap_kernel_functor_unboxed_<c10::impl::detail::WrapFunctionIntoFunctor_<c10::CompileTimeFunctionPointer<at::Tensor (c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, bool), &torch::autograd::VariableType::(anonymous namespace)::expand(c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, bool)>, at::Tensor, c10::guts::typelist::typelist<c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, bool>>, at::Tensor (c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, bool)>::call(c10::OperatorKernel*, c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<c10::SymInt>, bool) + 992 (0x114e8b010 in libtorch_cpu.dylib) frame pytorch#11: at::_ops::expand::call(at::Tensor const&, c10::ArrayRef<c10::SymInt>, bool) + 316 (0x112743c90 in libtorch_cpu.dylib) frame pytorch#12: at::expand_size(at::Tensor const&, c10::ArrayRef<long long>) + 164 (0x1047d82b4 in basic) frame pytorch#13: BasicTest_TestForBlobResizeCPU_Test::TestBody() + 284 (0x1047d8048 in basic) ``` Pull Request resolved: pytorch#158690 Approved by: https://github.com/angelayi
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Fixes #ISSUE_NUMBER