Fix undefined behavior detected by clang-12

[malfet]

Stack from ghstack (oldest at bottom):

• Move ASAN to clang12 and Ubuntu-22.04 (Jammy) #106355
• -> Fix undefined behavior detected by clang-12 #106354

Compiler behavior when non-zero offset is added to a null pointer is undefined and is a bad habit.

• When lapackEig is called with to estimate a workspace size, do not add matrix size to the W pointer.
• When unpack_pivots_cpu_kernel with zero dim_size exit early.
• When topk_impl_loop is called with k is zero, exit right away as output tensors are empty anyway.
• Ignore adding non-zero storage-offset in TensorImpl::data_ptr_impl_impl, which can be the case if tensor is created as torch.empty(3)[4:].
• In s_addmm_out_sparse_dense_worker do not call axpy over an empty vector.
• In _sparse_binary_op_intersection_kernel_impl do skip computing ptr_indices_dim when sparse_dim is empty.
• Exit grid_sample forward/backward kernels earlier if either input or grid are empty tensors.

Found by asan in clang-12

Before the change UBSan report looks as follows:

 ASAN_SYMBOLIZER_PATH=/usr/lib/llvm-12/bin/llvm-symbolizer UBSAN_OPTIONS=print_stacktrace=1 LD_PRELOAD=/usr/lib/llvm-12/lib/clang/12.0.1/lib/linux/libclang_rt.asan-x86_64.so python test_fx_experimental.py -v -k test_normalize_operator_exhaustive_linalg_eig_cpu_float32
Test results will be stored in test-reports/python-unittest/test_fx_experimental

Running tests...
----------------------------------------------------------------------
  test_normalize_operator_exhaustive_linalg_eig_cpu_float32 (__main__.TestNormalizeOperatorsCPU) ... /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/overrides.py:111: UserWarning: 'has_cuda' is deprecated, please use 'torch.backends.cuda.is_built()'
  torch.has_cuda,
/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/overrides.py:112: UserWarning: 'has_cudnn' is deprecated, please use 'torch.backends.cudnn.is_available()'
  torch.has_cudnn,
/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/overrides.py:118: UserWarning: 'has_mps' is deprecated, please use 'torch.backends.mps.is_built()'
  torch.has_mps,
/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/overrides.py:119: UserWarning: 'has_mkldnn' is deprecated, please use 'torch.backends.mkldnn.is_available()'
  torch.has_mkldnn,
/var/lib/jenkins/workspace/aten/src/ATen/native/BatchLinearAlgebra.cpp:937:17: runtime error: applying non-zero offset 20 to null pointer
    #0 0x7f2025794888 in void at::native::lapackEig<float, float>(char, char, int, float*, int, float*, float*, int, float*, int, float*, int, float*, int*) (/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/lib/libtorch_cpu.so+0x9945888)
    #1 0x7f20257da256 in void at::native::(anonymous namespace)::apply_linalg_eig<float>(at::Tensor&, at::Tensor&, at::Tensor&, at::Tensor&, bool) (/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/lib/libtorch_cpu.so+0x998b256)
    #2 0x7f20257d902d in at::native::(anonymous namespace)::linalg_eig_kernel(at::Tensor&, at::Tensor&, at::Tensor&, at::Tensor const&, bool) (/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/lib/libtorch_cpu.so+0x998a02d)
    #3 0x7f20257b5b3d in at::native::linalg_eig_out_info(at::Tensor const&, at::Tensor&, at::Tensor&, at::Tensor&, bool) (/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/lib/libtorch_cpu.so+0x9966b3d)
    #4 0x7f20257b4770 in at::native::linalg_eig_out(at::Tensor const&, at::Tensor&, at::Tensor&) (/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/lib/libtorch_cpu.so+0x9965770)
    #5 0x7f20280710e6 in c10::impl::wrap_kernel_functor_unboxed_<c10::impl::detail::WrapFunctionIntoFunctor_<c10::CompileTimeFunctionPointer<std::tuple<at::Tensor&, at::Tensor&> (at::Tensor const&, at::Tensor&, at::Tensor&), &(at::(anonymous namespace)::(anonymous namespace)::wrapper_CPU_out_linalg_eig_out(at::Tensor const&, at::Tensor&, at::Tensor&))>, std::tuple<at::Tensor&, at::Tensor&>, c10::guts::typelist::typelist<at::Tensor const&, at::Tensor&, at::Tensor&> >, std::tuple<at::Tensor&, at::Tensor&> (at::Tensor const&, at::Tensor&, at::Tensor&)>::call(c10::OperatorKernel*, c10::DispatchKeySet, at::Tensor const&, at::Tensor&, at::Tensor&) (/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/lib/libtorch_cpu.so+0xc2220e6)
    #6 0x7f202727a045 in at::_ops::linalg_eig_out::call(at::Tensor const&, at::Tensor&, at::Tensor&) (/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/lib/libtorch_cpu.so+0xb42b045)
    #7 0x7f20257b7e29 in at::native::linalg_eig(at::Tensor const&) (/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/lib/libtorch_cpu.so+0x9968e29)
    #8 0x7f2028070bf0 in c10::impl::wrap_kernel_functor_unboxed_<c10::impl::detail::WrapFunctionIntoFunctor_<c10::CompileTimeFunctionPointer<std::tuple<at::Tensor, at::Tensor> (at::Tensor const&), &(at::(anonymous namespace)::(anonymous namespace)::wrapper_CPU__linalg_eig(at::Tensor const&))>, std::tuple<at::Tensor, at::Tensor>, c10::guts::typelist::typelist<at::Tensor const&> >, std::tuple<at::Tensor, at::Tensor> (at::Tensor const&)>::call(c10::OperatorKernel*, c10::DispatchKeySet, at::Tensor const&) (/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/lib/libtorch_cpu.so+0xc221bf0)
    #9 0x7f2026b1f787 in std::tuple<at::Tensor, at::Tensor> c10::Dispatcher::redispatch<std::tuple<at::Tensor, at::Tensor>, at::Tensor const&>(c10::TypedOperatorHandle<std::tuple<at::Tensor, at::Tensor> (at::Tensor const&)> const&, c10::DispatchKeySet, at::Tensor const&) const (/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/lib/libtorch_cpu.so+0xacd0787)
    #10 0x7f20273230a7 in at::_ops::linalg_eig::redispatch(c10::DispatchKeySet, at::Tensor const&) (/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/lib/libtorch_cpu.so+0xb4d40a7)
    #11 0x7f202c3cc32d in torch::autograd::VariableType::(anonymous namespace)::linalg_eig(c10::DispatchKeySet, at::Tensor const&) (/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/lib/libtorch_cpu.so+0x1057d32d)
    #12 0x7f202c3cba96 in c10::impl::wrap_kernel_functor_unboxed_<c10::impl::detail::WrapFunctionIntoFunctor_<c10::CompileTimeFunctionPointer<std::tuple<at::Tensor, at::Tensor> (c10::DispatchKeySet, at::Tensor const&), &(torch::autograd::VariableType::(anonymous namespace)::linalg_eig(c10::DispatchKeySet, at::Tensor const&))>, std::tuple<at::Tensor, at::Tensor>, c10::guts::typelist::typelist<c10::DispatchKeySet, at::Tensor const&> >, std::tuple<at::Tensor, at::Tensor> (c10::DispatchKeySet, at::Tensor const&)>::call(c10::OperatorKernel*, c10::DispatchKeySet, at::Tensor const&) (/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/lib/libtorch_cpu.so+0x1057ca96)
    #13 0x7f20272798e0 in at::_ops::linalg_eig::call(at::Tensor const&) (/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/lib/libtorch_cpu.so+0xb42a8e0)
    #14 0x7f2043d97ae3 in torch::autograd::THPVariable_linalg_eig(_object*, _object*, _object*) (/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/lib/libtorch_python.so+0x23feae3)
    #15 0x5072d6 in cfunction_call /usr/local/src/conda/python-3.9.17/Objects/methodobject.c:543:19
    ...

SUMMARY: UndefinedBehaviorSanitizer: undefined-behavior /var/lib/jenkins/workspace/aten/src/ATen/native/BatchLinearAlgebra.cpp:937:17 in

cc @jgong5 @mingfeima @XiaobingSuper @sanchitintel @ashokei @jingxu10

[pytorch-bot]

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As of commit 606d405:
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[malfet]

One more failure:

% python -c "import torch;print(torch.nn.functional.grid_sample(torch.rand([6, 5, 3, 2]), torch.empty([6, 0, 3, 2])))"
/var/lib/jenkins/workspace/aten/src/ATen/core/TensorAccessor.h:83:64: runtime error: applying non-zero offset 60 to null pointer
    #0 0x7f39397792ef in at::TensorAccessor<float, 4ul, at::DefaultPtrTraits, long>::operator[](long) (/var/lib/jenkins/workspace/torch/lib/libtorch_cpu.so+0x9ae62ef)

[malfet]

And another one:

% python test_autograd.py -v -k test_sparse_ctor_getter_backward_cpu_complex

[malfet]

Two more in sparse handling:

python ../test/test_linalg.py -v -k test_lobpcg_ortho_cpu_float64
python ../test/test_sparse.py -v -k test_bmm_cpu_float64

And one in topk:

python -c "import torch;print(torch.topk(torch.rand(2, 2), k=0, largest=False))"

[albanD]

This is not changing with iterations, so running the for loop is not really needed, we can bypass higher.

[malfet]

I thought about that, it will affect error checking, would it not? (I.e. we still need to check that col and row are within tensor dimensions...

[malfet]

Two more sparse ones:

% python test/test_sparse.py -v -k test_sparse_spdiags_cpu_bool
% python test/test_sparse.py -v -k test_sparse_sparse_mul_cpu_complex128

[malfet]

One more (part of test_dim_function_empty from test_torch.py):

% python -c "import torch;torch.rand((0, 1, 2, 0)).index_add(2, torch.tensor([0, 1]), torch.empty((0, 1, 2, 0)))"
/var/lib/jenkins/workspace/aten/src/ATen/native/TensorAdvancedIndexing.cpp:935:5: runtime error: applying non-zero offset 4 to null pointer