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Refine error_handle for BatchLinearAlgebra Ops #2321

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Refine error_handle for BatchLinearAlgebra Ops #2321

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ecf4f66
Remove work-around used for 2025.2
CuiYifeng Nov 10, 2025
3066ba2
Reactivate skipped test cases
CuiYifeng Nov 10, 2025
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14 changes: 2 additions & 12 deletions src/ATen/native/xpu/mkl/BatchLinearAlgebra.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -44,16 +44,6 @@ void error_handle(
auto errs = be.exceptions();
auto ids = be.ids();

if (!errs.size()) {
TORCH_WARN(
"Caught lapack exception:\nWhat: ", be.what(), "\nInfo: ", be.info());
for (auto& i : ids) {
TORCH_WARN("Error in matrix #", i);
info_cpu[i] = 1;
}
return;
}

for (size_t i = 0; i < errs.size(); ++i) {
try {
std::rethrow_exception(errs[i]);
Expand All @@ -65,10 +55,10 @@ void error_handle(
e.info(),
"\nDetail: ",
e.detail());
info_cpu[i] = e.info();
info_cpu[ids[i]] = e.info();
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Copilot AI Dec 1, 2025

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Potential out-of-bounds access: ids[i] is used to index info_cpu, but there's no validation that ids[i] is within the bounds of info_cpu. This could cause a segfault or memory corruption if the batch exception contains an invalid matrix ID.

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} catch (const sycl::exception& e) {
TORCH_WARN("Caught SYCL exception:\nWhat: ", e.what(), "\nInfo: -1");
info_cpu[i] = -1;
info_cpu[ids[i]] = -1;
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Copilot AI Dec 1, 2025

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Potential out-of-bounds access: Same issue as above - ids[i] is used to index info_cpu without bounds checking. Consider adding validation that ids[i] < info_cpu.size() before indexing.

Copilot uses AI. Check for mistakes.
}
}
}
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9 changes: 0 additions & 9 deletions test/xpu/skip_list_common.py
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Expand Up @@ -290,15 +290,6 @@
"test_scaled_gemm_offline_tunableop_xpu_float8_e5m2fnuz",
# case need to port for xpu
"test_gemm_bias_offline_tunableop_xpu_bfloat16",
# Exception is temporarily unavailable due to regression in oneMKL
"test_inv_errors_and_warnings_xpu_float32",
"test_inv_errors_and_warnings_xpu_float64",
"test_inverse_errors_large_xpu_float32",
"test_inverse_errors_large_xpu_float64",
"test_inverse_errors_xpu_float32",
"test_inverse_errors_xpu_float64",
"test_inv_ex_singular_xpu_float32",
"test_inv_ex_singular_xpu_float64",
),
"test_ops_fwd_gradients_xpu.py": (
# All of the followings are oneDNN issues
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