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…torch#156600) Don't call `sum()` on a tensor that is default constructed. Previously we could call `sum()` on a tensor that was default-contructed. That would lead to an error like this: ``` Traceback (most recent call last): File "/home/ahmads/.conda/envs/pt3/lib/python3.12/unittest/case.py", line 58, in testPartExecutor yield File "/home/ahmads/.conda/envs/pt3/lib/python3.12/unittest/case.py", line 634, in run self._callTestMethod(testMethod) File "/home/ahmads/.conda/envs/pt3/lib/python3.12/unittest/case.py", line 589, in _callTestMethod if method() is not None: ^^^^^^^^ File "/home/ahmads/personal/pytorch/torch/testing/_internal/common_utils.py", line 3191, in wrapper method(*args, **kwargs) File "/home/ahmads/personal/pytorch/test/test_nn.py", line 7235, in test_layer_norm_backwards_eps ln_out_cuda.backward(grad_output_cuda) File "/home/ahmads/personal/pytorch/torch/_tensor.py", line 647, in backward torch.autograd.backward( File "/home/ahmads/personal/pytorch/torch/autograd/__init__.py", line 354, in backward _engine_run_backward( File "/home/ahmads/personal/pytorch/torch/autograd/graph.py", line 829, in _engine_run_backward return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ RuntimeError: tensor does not have a device Exception raised from device_default at /home/ahmads/personal/pytorch/c10/core/TensorImpl.h:1265 (most recent call first): C++ CapturedTraceback: #4 std::_Function_handler<std::shared_ptr<c10::LazyValue<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > > const> (), c10::SetStackTraceFetcher(std::function<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > ()>)::{lambda()#1}>::_M_invoke(std::_Any_data const&) from Logging.cpp:0 #5 c10::Error::Error(c10::SourceLocation, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >) from ??:0 #6 c10::detail::torchCheckFail(char const*, char const*, unsigned int, char const*) from ??:0 #7 at::TensorBase::options() const from :0 #8 at::meta::resize_reduction(at::impl::MetaBase&, at::Tensor const&, c10::OptionalArrayRef<long>, bool, c10::ScalarType, bool) from :0 #9 at::meta::structured_sum_dim_IntList::meta(at::Tensor const&, c10::OptionalArrayRef<long>, bool, std::optional<c10::ScalarType>) from ??:0 #10 at::(anonymous namespace)::wrapper_CompositeExplicitAutogradNonFunctional_sum_dim_IntList(at::Tensor const&, c10::OptionalArrayRef<long>, bool, std::optional<c10::ScalarType>) from RegisterCompositeExplicitAutogradNonFunctional_0.cpp:0 #11 c10::impl::wrap_kernel_functor_unboxed_<c10::impl::detail::WrapFunctionIntoFunctor_<c10::CompileTimeFunctionPointer<at::Tensor (at::Tensor const&, c10::OptionalArrayRef<long>, bool, std::optional<c10::ScalarType>), &at::(anonymous namespace)::wrapper_CompositeExplicitAutogradNonFunctional_sum_dim_IntList>, at::Tensor, c10::guts::typelist::typelist<at::Tensor const&, c10::OptionalArrayRef<long>, bool, std::optional<c10::ScalarType> > >, at::Tensor (at::Tensor const&, c10::OptionalArrayRef<long>, bool, std::optional<c10::ScalarType>)>::call(c10::OperatorKernel*, c10::DispatchKeySet, at::Tensor const&, c10::OptionalArrayRef<long>, bool, std::optional<c10::ScalarType>) from RegisterCompositeExplicitAutogradNonFunctional_0.cpp:0 #12 at::_ops::sum_dim_IntList::call(at::Tensor const&, c10::OptionalArrayRef<long>, bool, std::optional<c10::ScalarType>) from ??:0 #13 void at::native::(anonymous namespace)::LaunchGammaBetaBackwardCUDAKernel<float, float>(float const*, float const*, float const*, float const*, long, long, at::Tensor*, at::Tensor*, CUstream_st*) from ??:0 #14 void at::native::(anonymous namespace)::LayerNormBackwardKernelImplInternal<float>(at::Tensor const&, at::Tensor const&, at::Tensor const&, at::Tensor const&, at::Tensor const&, long, long, at::Tensor*, at::Tensor*, at::Tensor*) from ??:0 #15 at::native::(anonymous namespace)::LayerNormBackwardKernelImpl(at::Tensor const&, at::Tensor const&, at::Tensor const&, at::Tensor const&, at::Tensor const&, long, long, at::Tensor*, at::Tensor*, at::Tensor*) from ??:0 #16 at::native::layer_norm_backward_cuda(at::Tensor const&, at::Tensor const&, c10::ArrayRef<long>, at::Tensor const&, at::Tensor const&, std::optional<at::Tensor> const&, std::optional<at::Tensor> const&, std::array<bool, 3ul>) from ??:0 #17 at::(anonymous namespace)::(anonymous namespace)::wrapper_CUDA__native_layer_norm_backward(at::Tensor const&, at::Tensor const&, c10::ArrayRef<c10::SymInt>, at::Tensor const&, at::Tensor const&, std::optional<at::Tensor> const&, std::optional<at::Tensor> const&, std::array<bool, 3ul>) from RegisterCUDA_0.cpp:0 ``` Now we only call `sum(0)` on tensors that are defined and properly guard the `sum(0)` and assignment. Pull Request resolved: pytorch#156600 Approved by: https://github.com/eqy, https://github.com/ngimel
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When another process group name is registered as the backend for XPU, it immediately replaces XCCL. However, our intention is to designate XCCL as the default distributed backend for XPU.
A simple case is:
Now this case will raise
RuntimeError: No backend type associated with device type xpuTest case added in other repo intel/torch-xpu-ops#1721