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Don't check for linalg errors on meta tensors

Browse Source 
Signed-off-by: Edward Z. Yang <ezyangfb.com>

Pull Request resolved: https://github.com/pytorch/pytorch/pull/78467

Approved by: https://github.com/Chillee
This commit is contained in:
Edward Z. Yang 2022-05-30 20:30:51 -07:00 committed by PyTorch MergeBot
parent 59fdb627a3
commit 789115e05e
2 changed files with 3 additions and 18 deletions
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3
aten/src/ATen/native/BatchLinearAlgebra.cpp
View File

@ -1294,6 +1294,9 @@ void _linalg_check_errors(
const Tensor& info,
const c10::string_view api_name,
bool is_matrix) {
if (info.is_meta()) {
return;
}
if (is_matrix) {
singleCheckErrors(info.item<int64_t>(), api_name);
} else {

18
test/test_meta.py
View File

@ -603,14 +603,10 @@ meta_function_expected_failures = {
torch.linalg.eigvals: {f32, f64},
torch.linalg.eigvalsh: {f32, f64}, # aten::linalg_eigvalsh.out
torch.linalg.householder_product: {f32, f64}, # aten::linalg_householder_product
torch.linalg.inv: {f32, f64}, # aten::_local_scalar_dense
torch.linalg.ldl_factor: {f32, f64}, # aten::_local_scalar_dense
torch.linalg.lstsq: {f32, f64}, # aten::linalg_lstsq.out
torch.linalg.lu_factor: {f32, f64}, # aten::_local_scalar_dense
torch.linalg.slogdet: {f32, f64}, # aten::linalg_slogdet
torch.linalg.solve: {f32, f64}, # aten::linalg_solve, aten::linalg_solve.out
torch.linalg.solve_triangular: {f32, f64}, # aten::linalg_solve_triangular
torch.linalg.tensorinv: {f32, f64}, # aten::_local_scalar_dense
torch.linalg.tensorsolve: {f32, f64}, # aten::linalg_solve
torch.logdet: {f32, f64}, # aten::_local_scalar_dense, aten::nonzero
}
@ -640,9 +636,6 @@ meta_function_skips = {
torch.nn.functional.cross_entropy: {bf16, f32, f64},
torch.nn.functional.interpolate: {bf16, f32, f64, u8},
torch.nn.functional.nll_loss: {bf16, f32, f64}, # TODO
torch.inverse: {f32, f64},
torch.linalg.matrix_power: {f32, f64},
torch.linalg.matrix_rank: {f32, f64},
torch.linalg.pinv: {f32, f64},
torch.empty: {b8, bf16, c128, c64, c32, f16, f32, f64, i16, i32, i64, i8, u8},
}
@ -685,11 +678,7 @@ meta_function_device_expected_failures['cuda'] = {
torch.linalg.cholesky: {f32, f64}, # aten::linalg_cholesky_ex, aten::linalg_cholesky_ex.L
torch.linalg.cholesky_ex: {f32, f64}, # aten::linalg_cholesky_ex
torch.linalg.householder_product: {f32, f64}, # aten::linalg_householder_product, aten::linalg_householder_product.out
torch.linalg.inv: {f32, f64}, # aten::_local_scalar_dense
torch.linalg.ldl_factor: {f32, f64}, # aten::_local_scalar_dense
torch.linalg.lu_factor: {f32, f64}, # aten::_local_scalar_dense
torch.linalg.solve_triangular: {f32, f64}, # aten::linalg_solve_triangular, aten::linalg_solve_triangular.out
torch.linalg.tensorinv: {f32, f64}, # aten::_local_scalar_dense
torch.logcumsumexp: {bf16, f16}, # aten::_logcumsumexp, aten::_logcumsumexp.out
torch.matrix_exp: {f16}, # aten::linalg_matrix_exp
torch.median: {f16}, # aten::median, aten::median.dim_values
@ -726,7 +715,6 @@ meta_function_device_skips['cuda'] = {
torch.cummin: {f16},
torch.functional.tensordot: {f16},
torch.inner: {f16},
torch.inverse: {f32, f64},
torch.linalg.matrix_power: {f32, f64},
torch.linalg.matrix_rank: {f32, f64},
torch.linalg.svd: {f32, f64},
@ -873,7 +861,6 @@ meta_dispatch_expected_failures = {
aten.vdot.default: {i64, bf16, u8, f32, i8, f64, i16, i32},
aten.vdot.out: {i64, bf16, u8, f32, i8, f64, i16, i32},
aten._det_lu_based_helper.default: {f32, f64}, # aten::_det_lu_based_helper
aten._linalg_check_errors.default: {c128, c64, f32, f64}, # aten::_local_scalar_dense
aten.cholesky.default: {f32, f64}, # aten::cholesky
aten.cholesky.out: {f32, f64}, # aten::cholesky.out
aten.cholesky_inverse.default: {f32, f64}, # aten::cholesky_inverse
@ -882,7 +869,6 @@ meta_dispatch_expected_failures = {
aten.cholesky_solve.out: {f32, f64}, # aten::_cholesky_solve_helper
aten.eig.default: {f32, f64}, # aten::_local_scalar_dense
aten.geqrf.default: {f32, f64}, # aten::geqrf
aten.inverse.out: {f32, f64}, # aten::_local_scalar_dense
aten.linalg_cholesky_ex.L: {f32, f64}, # aten::linalg_cholesky_ex.L
aten.linalg_cholesky_ex.default: {f32, f64}, # aten::linalg_cholesky_ex
aten.linalg_eig.default: {f32, f64}, # aten::linalg_eig
@ -929,7 +915,6 @@ meta_dispatch_device_expected_failures['cuda'] = {
aten._fft_c2r.out: {c32, f16}, # aten::_fft_c2r.out
aten._fft_r2c.default: {f16}, # aten::_fft_r2c
aten._fft_r2c.out: {f16}, # aten::_fft_r2c.out
aten._linalg_check_errors.default: {c128, c64, f32, f64}, # aten::_local_scalar_dense
aten._unique2.default: {f16}, # aten::_unique2
aten._use_cudnn_ctc_loss.default: {f32, f64}, # aten::_use_cudnn_ctc_loss
aten.addbmm.default: {f16}, # aten::addbmm
@ -944,7 +929,6 @@ meta_dispatch_device_expected_failures['cuda'] = {
aten.histc.default: {i16, i32, i64, i8}, # aten::histc
aten.histc.out: {i16, i32, i64, i8}, # aten::histc.out
aten.index.Tensor: {c32}, # aten::index.Tensor
aten.inverse.out: {f32, f64}, # aten::_local_scalar_dense
aten.kthvalue.default: {f16}, # aten::kthvalue.values
aten.linalg_cholesky_ex.L: {f32, f64}, # aten::linalg_cholesky_ex.L
aten.linalg_cholesky_ex.default: {f32, f64}, # aten::linalg_cholesky_ex
@ -990,11 +974,9 @@ meta_dispatch_device_expected_failures['cuda'] = {
meta_dispatch_device_skips['cuda'] = {
aten._conj.default: {c32, f16},
aten._linalg_svd.default: {f32, f64},
aten.cudnn_batch_norm.default: {f32, f64},
aten.cummax.default: {f16},
aten.cummin.default: {f16},
aten.inverse.default: {f32, f64},
# ROCm stuff; technically this should be expected failure but it's
# not worth it; these should get unified anyway
aten.miopen_batch_norm.default: {f32},