Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/64282
OpInfos for:
- Tensor.bfloat16, Tensor.bool, Tensor.bypte, Tensor.char
- Tensor.double, Tensor.float, Tensor.half, Tensor.int
- Tensor.short, Tensor.long
None of these are supported by TorchScript. Also, the OpInfo autograd
test runner assumes that the operation is not allowed to change the
dtype of the argument, so only Tensor.double has
`supports_autograd=True` (in theory Tensor.bfloat16, Tensor.float,
Tensor.half should be differentiable).
Test Plan: - run tests
Reviewed By: dagitses
Differential Revision: D31452627
Pulled By: zou3519
fbshipit-source-id: b7f272e558558412c47aefe947af7f060dfb45c5
Summary:
Fixes https://github.com/pytorch/pytorch/issues/20972
log_sigmoid calculates something like `log(1 + x)` where x is always a
positive number less than one. This wastes floating point precision
because the exponent always becomes zero. Instead, using
`log1p(x)` gives the full mantissa precision around `x=0`.
This also fixes infinity propagation because the old code does,
`exp(in - in)` when `in` is negative. Which for infinity, results in a
NaN instead of 0.
cc albanD mruberry jbschlosser walterddr
Pull Request resolved: https://github.com/pytorch/pytorch/pull/66441
Reviewed By: bdhirsh
Differential Revision: D31619630
Pulled By: albanD
fbshipit-source-id: e7867f3459a91e944b92f8ca42b6e0697b13f89b
Summary:
I updated `sample_inputs_linalg_lstsq` and `test_nondifferentiable`
now correctly reveals the failure. The internal assert error was thrown
because autograd attempts to mark integer tensor as differentiable.
Fixes https://github.com/pytorch/pytorch/issues/66420.
cc ezyang albanD zou3519 gqchen pearu nikitaved soulitzer Lezcano Varal7
Pull Request resolved: https://github.com/pytorch/pytorch/pull/66426
Reviewed By: ejguan
Differential Revision: D31550942
Pulled By: albanD
fbshipit-source-id: 4a0ca60e62c5e9bb96af5020541da2d09ea3e405
Summary:
Enable testing of `torch.Tensor.resize_`.
The negative view test is skipped as the test doesn't work with resize_ see
https://github.com/pytorch/pytorch/issues/65945.
cc mruberry
Pull Request resolved: https://github.com/pytorch/pytorch/pull/66135
Reviewed By: dagitses
Differential Revision: D31444263
Pulled By: mruberry
fbshipit-source-id: 00c7fe05df28fba01508b31adb3ed4fdcf4d0326
Summary:
This PR adds forward AD for `*_solve` methods.
Additionally, `cholesky_solve` gets OpInfo + a bug fix when wrong leading dimensions could be passed to LAPACK,
and `lu_solve` gets forward AD with 2x`lu_solve` instead of 1x`lu_solve` + 2x`triangular_solve`.
cc ezyang albanD zou3519 gqchen pearu nikitaved soulitzer Lezcano Varal7 jianyuh mruberry walterddr IvanYashchuk xwang233
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65546
Reviewed By: dagitses
Differential Revision: D31431847
Pulled By: albanD
fbshipit-source-id: 0e343e0d9da3c3d2051fca215fad289d77275251
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/64572
Fixes https://github.com/pytorch/pytorch/issues/64256
It also fixes an inconsistent treatment of the case `reduction = "mean"`
when the whole target is equal to `ignore_index`. It now returns `NaN`
in this case, consistently with what it returns when computing the mean
over an empty tensor.
We add tests for all these cases.
Test Plan: Imported from OSS
Reviewed By: ezyang
Differential Revision: D31116297
Pulled By: albanD
fbshipit-source-id: cc44e79205f5eeabf1efd7d32fe61e26ba701b52
Summary:
This PR fixes https://github.com/pytorch/pytorch/issues/58547.
I added an OpInfo-based test that fails on master and passes with the
proposed changes.
cc ezyang albanD zou3519 gqchen pearu nikitaved soulitzer Lezcano Varal7 mruberry
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65714
Reviewed By: saketh-are, mruberry
Differential Revision: D31248307
Pulled By: albanD
fbshipit-source-id: 041eaa9b744c3043f78dd8ae5f457f67c311df4f
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65493
Added a last resolve to use whatever ATen operator that has Tensor outputs in the graph as the operator node to check alias annotation.
Test Plan: python test/test_ops.py -k test_variant_consistency_jit
Reviewed By: mrshenli
Differential Revision: D31321221
Pulled By: alanwaketan
fbshipit-source-id: f4a5cbfd36bd0867d8c1bf9de9a65365ee7c35d6
Summary:
Skip failing tests when LAPACK and MAGMA are not available for ` test_linalg.py` and ` test_ops.py`.
Note that there's no CI without LAPACK or MAGMA. I verified locally that now it works as expected, but in the future we have no guards against tests failing again for this situation.
<details>
<summary> test_ops.py failures that are fixed</summary>
```
FAILED test/test_ops.py::TestCommonCPU::test_out_linalg_tensorinv_cpu_float32 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_ops.py::TestCommonCPU::test_reference_testing_linalg_tensorinv_cpu_complex64 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_ops.py::TestCommonCPU::test_reference_testing_linalg_tensorinv_cpu_float32 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_ops.py::TestCommonCPU::test_variant_consistency_eager_linalg_tensorinv_cpu_complex64 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_ops.py::TestCommonCPU::test_variant_consistency_eager_linalg_tensorinv_cpu_float32 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_ops.py::TestCommonCPU::test_variant_consistency_eager_triangular_solve_cpu_complex64 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_ops.py::TestCommonCPU::test_variant_consistency_eager_triangular_solve_cpu_float32 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_ops.py::TestGradientsCPU::test_fn_grad_linalg_tensorinv_cpu_complex128 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_ops.py::TestGradientsCPU::test_fn_grad_linalg_tensorinv_cpu_float64 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_ops.py::TestGradientsCPU::test_fn_grad_triangular_solve_cpu_complex128 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_ops.py::TestGradientsCPU::test_fn_grad_triangular_solve_cpu_float64 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_ops.py::TestGradientsCPU::test_fn_gradgrad_linalg_tensorinv_cpu_complex128 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_ops.py::TestGradientsCPU::test_fn_gradgrad_linalg_tensorinv_cpu_float64 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_ops.py::TestGradientsCPU::test_fn_gradgrad_triangular_solve_cpu_complex128 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_ops.py::TestGradientsCPU::test_fn_gradgrad_triangular_solve_cpu_float64 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_ops.py::TestGradientsCPU::test_forward_mode_AD_linalg_tensorinv_cpu_complex128 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_ops.py::TestGradientsCPU::test_forward_mode_AD_linalg_tensorinv_cpu_float64 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_ops.py::TestGradientsCPU::test_forward_mode_AD_triangular_solve_cpu_complex128 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_ops.py::TestGradientsCPU::test_forward_mode_AD_triangular_solve_cpu_float64 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_ops.py::TestJitCPU::test_variant_consistency_jit_linalg_tensorinv_cpu_complex64 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_ops.py::TestJitCPU::test_variant_consistency_jit_triangular_solve_cpu_complex64 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_ops.py::TestJitCPU::test_variant_consistency_jit_triangular_solve_cpu_float32 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_ops.py::TestMathBitsCPU::test_conj_view_linalg_tensorinv_cpu_complex64 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_ops.py::TestMathBitsCPU::test_conj_view_triangular_solve_cpu_complex64 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_ops.py::TestMathBitsCPU::test_neg_view_linalg_tensorinv_cpu_float64 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_ops.py::TestMathBitsCPU::test_neg_view_triangular_solve_cpu_float64 - RuntimeError: svd: LAPACK library not found in compilation
```
</details>
<details>
<summary> test_linalg.py failures that are fixed</summary>
```
FAILED test/test_linalg.py::TestLinalgCPU::test_norm_dtype_cpu - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgCPU::test_norm_matrix_cpu_float32 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgCPU::test_norm_matrix_cpu_float64 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgCPU::test_nuclear_norm_axes_small_brute_force_old_cpu - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgMETA::test_eigh_hermitian_grad_meta_complex128 - RuntimeError: Calling torch.linalg.eigh or eigvalsh on a CPU tensor requires compiling PyTorch with LAPACK. Please use PyTorch built with LAPACK support.
FAILED test/test_linalg.py::TestLinalgMETA::test_eigh_hermitian_grad_meta_float64 - RuntimeError: Calling torch.linalg.eigh or eigvalsh on a CPU tensor requires compiling PyTorch with LAPACK. Please use PyTorch built with LAPACK support.
FAILED test/test_linalg.py::TestLinalgMETA::test_inverse_meta_complex128 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgMETA::test_inverse_meta_complex64 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgMETA::test_inverse_meta_float32 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgMETA::test_inverse_meta_float64 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgMETA::test_lu_meta_complex128 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgMETA::test_lu_meta_complex64 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgMETA::test_lu_meta_float64 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgMETA::test_lu_solve_batched_broadcasting_meta_complex128 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgMETA::test_lu_solve_batched_broadcasting_meta_complex64 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgMETA::test_lu_solve_batched_broadcasting_meta_float32 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgMETA::test_lu_solve_batched_broadcasting_meta_float64 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgMETA::test_lu_solve_batched_non_contiguous_meta_complex128 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgMETA::test_lu_solve_batched_non_contiguous_meta_complex64 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgMETA::test_lu_solve_batched_non_contiguous_meta_float32 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgMETA::test_lu_solve_batched_non_contiguous_meta_float64 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgMETA::test_lu_solve_meta_complex128 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgMETA::test_lu_solve_meta_complex64 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgMETA::test_lu_solve_meta_float32 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgMETA::test_lu_solve_meta_float64 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgMETA::test_old_solve_batched_broadcasting_meta_complex128 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgMETA::test_old_solve_batched_broadcasting_meta_complex64 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgMETA::test_old_solve_batched_broadcasting_meta_float32 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgMETA::test_old_solve_batched_broadcasting_meta_float64 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgMETA::test_old_solve_batched_meta_complex128 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgMETA::test_old_solve_batched_meta_complex64 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgMETA::test_old_solve_batched_meta_float32 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgMETA::test_old_solve_batched_meta_float64 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgMETA::test_old_solve_batched_non_contiguous_meta_complex128 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgMETA::test_old_solve_batched_non_contiguous_meta_complex64 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgMETA::test_old_solve_batched_non_contiguous_meta_float32 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgMETA::test_old_solve_batched_non_contiguous_meta_float64 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgMETA::test_old_solve_meta_complex128 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgMETA::test_old_solve_meta_complex64 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgMETA::test_old_solve_meta_float32 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgMETA::test_old_solve_meta_float64 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgMETA::test_solve_batched_non_contiguous_meta_complex128 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgMETA::test_solve_batched_non_contiguous_meta_complex64 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgMETA::test_solve_batched_non_contiguous_meta_float32 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgMETA::test_solve_batched_non_contiguous_meta_float64 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgMETA::test_solve_meta_complex128 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgMETA::test_solve_meta_complex64 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgMETA::test_solve_meta_float32 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgMETA::test_solve_meta_float64 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgMETA::test_svd_square_col_maj_meta_float32 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgMETA::test_svd_square_col_maj_meta_float64 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgMETA::test_svd_square_meta_complex128 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgMETA::test_svd_square_meta_complex64 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgMETA::test_svd_square_meta_float32 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgMETA::test_svd_square_meta_float64 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgMETA::test_svd_tall_all_col_maj_meta_float32 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgMETA::test_svd_tall_all_col_maj_meta_float64 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgMETA::test_svd_tall_all_meta_float32 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgMETA::test_svd_tall_all_meta_float64 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgMETA::test_svd_tall_some_col_maj_meta_float32 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgMETA::test_svd_tall_some_col_maj_meta_float64 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgMETA::test_svd_tall_some_meta_float32 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgMETA::test_svd_tall_some_meta_float64 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgCUDA::test_inverse_cuda_complex128 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgCUDA::test_inverse_cuda_complex64 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgCUDA::test_inverse_cuda_float32 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgCUDA::test_inverse_cuda_float64 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgCUDA::test_svd_lowrank_cuda_float64 - RuntimeError: Calling torch.lu on a CUDA tensor requires compiling PyTorch with MAGMA. lease rebuild with MAGMA.
FAILED test/test_linalg.py::TestLinalgCUDA::test_svd_square_col_maj_cuda_float32 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgCUDA::test_svd_square_col_maj_cuda_float64 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgCUDA::test_svd_square_cuda_complex128 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgCUDA::test_svd_square_cuda_complex64 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgCUDA::test_svd_square_cuda_float32 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgCUDA::test_svd_square_cuda_float64 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgCUDA::test_svd_tall_all_col_maj_cuda_float32 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgCUDA::test_svd_tall_all_col_maj_cuda_float64 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgCUDA::test_svd_tall_all_cuda_float32 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgCUDA::test_svd_tall_all_cuda_float64 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgCUDA::test_svd_tall_some_col_maj_cuda_float32 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgCUDA::test_svd_tall_some_col_maj_cuda_float64 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgCUDA::test_svd_tall_some_cuda_float32 - RuntimeError: svd: LAPACK library not found in compilation
FAILED test/test_linalg.py::TestLinalgCUDA::test_svd_tall_some_cuda_float64 - RuntimeError: svd: LAPACK library not found in compilation
```
</details>
Fixes https://github.com/pytorch/pytorch/issues/59662
cc mruberry jianyuh nikitaved pearu walterddr IvanYashchuk xwang233 Lezcano
Pull Request resolved: https://github.com/pytorch/pytorch/pull/64930
Reviewed By: H-Huang
Differential Revision: D31137652
Pulled By: mruberry
fbshipit-source-id: c969f75d7cf185765211004a0878e7c8a5d3cbf7
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65493
Added a last resolve to use whatever ATen operator that has Tensor outputs in the graph as the operator node to check alias annotation.
Test Plan:
python test/test_ops.py -k test_variant_consistency_jit_linalg_tensorinv
python test/test_ops.py -k test_variant_consistency_jit_nn_functional_normalize
Reviewed By: eellison
Differential Revision: D31132861
Pulled By: alanwaketan
fbshipit-source-id: 26fc2e6bc77be3a296967cf29a3f6ded231302fa
Summary:
Fixes https://github.com/pytorch/pytorch/issues/64999
- Adds a flag to gradcheck `check_backward_ad` that can be used to disable gradcheck for backward ad
- This is a bit bc-breaking in terms of positional args, but I prefer this ordering
- In OpInfo tests for forward ad:
- set `check_backward_ad` False
- In test_ops treat `supports_autograd` as if it is `supports_backward_ad` (it basically already is)
- the only modification needed is to no longer skip forward ad tests if `supports_autograd` is false
- test_dtype, test_variant_consistency, etc behave correctly as-is
- In a follow-up PR, we can rename it to actually be `supports_backward_ad`
- Testing
- https://github.com/pytorch/pytorch/pull/65060
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65040
Reviewed By: albanD
Differential Revision: D31238177
Pulled By: soulitzer
fbshipit-source-id: f068d4cbe7ffb094930b16cddb210583b9b7b2c4
Summary:
This PR attempts to port `baddbmm` and `bmm` to structured kernels. The reason it's in the same PR: because a lot of it is common for both the ops, including the checks and implementation.
Issue tracker: https://github.com/pytorch/pytorch/issues/55070
cc: ysiraichi ezyang
Pull Request resolved: https://github.com/pytorch/pytorch/pull/64805
Reviewed By: gchanan
Differential Revision: D31134454
Pulled By: ezyang
fbshipit-source-id: 3294619834a8cc6a0407aea660c556d3a42b6261
Summary:
This PR adds forward AD for `*_solve` methods.
Additionally, `cholesky_solve` gets OpInfo + a bug fix when wrong leading dimensions could be passed to LAPACK,
and `lu_solve` gets forward AD with 2x`lu_solve` instead of 1x`lu_solve` + 2x`triangular_solve`.
cc ezyang albanD zou3519 gqchen pearu nikitaved soulitzer Lezcano Varal7 jianyuh mruberry walterddr IvanYashchuk xwang233
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65546
Reviewed By: gchanan
Differential Revision: D31206837
Pulled By: albanD
fbshipit-source-id: 040beda97442e7a88a9df9abc7bb18313ce55bc3
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63010
This changes `test_neg_view` to call the operator with the same numeric values as the original sample input.
Test Plan: Imported from OSS
Reviewed By: pbelevich
Differential Revision: D31082824
Pulled By: anjali411
fbshipit-source-id: 7d50f99dc0d1343247e366cbe9b0ca081bd0a9b1
Summary:
Addresses https://github.com/facebookresearch/functorch/issues/78 and https://github.com/pytorch/pytorch/issues/54261.
* There exists `torch.batch_norm` but it takes an extra arg: `cudnn_enabled` (not there in functional variant). This is passed from the functional variant to `torch.batch_norm` here: https://github.com/pytorch/pytorch/blob/master/torch/nn/functional.py#L2282. `test_variant_consistency_jit` fails with an error: (when passed an alias)
```python
File "/home/krshrimali/Documents/Projects/Quansight/pytorch/test/test_ops.py", line 457, in _test_consistency_helper
variant_forward = variant(cloned,
TypeError: batch_norm() missing 1 required positional arguments: "cudnn_enabled"
```
* I'm not sure of a solution to this, as AFIK - there is no way to pass a lambda wrapper for an alias. Hence, I've skipped adding this as an alias there.
* On second thought, is this even an alias?
cc: mruberry zou3519 kshitij12345
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63218
Reviewed By: bdhirsh
Differential Revision: D31019785
Pulled By: zou3519
fbshipit-source-id: 2a834d05835da975289efc544a7ad7e98c99438f
Summary:
This is step 3/7 of https://github.com/pytorch/pytorch/issues/50276. It only adds support for the argument but doesn't implement new indexing modes yet.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/62722
Test Plan:
Verified this is not FC breaking by adding logging to both meshgrid
overloads and then called meshgrid twice:
`meshgrid(*tensors)`
and
`meshgrid(*tensors, indexing='ij')`
This confirmed that the former signature triggered the original native
function and the latter signature triggered the new native function.
Reviewed By: H-Huang
Differential Revision: D30394313
Pulled By: dagitses
fbshipit-source-id: e265cb114d8caae414ee2305dc463b34fdb57fa6
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63530
how to review: pretty much just check that the inputs generated are a good representation of the op semantics, that should be sufficient for correctness, and then you can also double check the op size semantics by going to https://codebrowser.bddppq.com/pytorch/pytorch/ typing in native::{op_name} and looking at the op implementation as a bonus if you want
Test Plan: Imported from OSS
Reviewed By: driazati
Differential Revision: D30738147
Pulled By: eellison
fbshipit-source-id: cf52339e572ee04e0d6167fd95d8a82d58ea7706
Summary:
OpInfo tracker: https://github.com/pytorch/pytorch/issues/54261
- Eliminate duplicated testing logic in test_autograd
- Moved tests that rely on this testing logic to use OpInfos
- `cat` already has OpInfo (no action needed)
- Created OpInfo for `block_diag` and `broadcast_tensors`
Running into some FX errors. Added op to skip-list and created an issue here: https://github.com/pytorch/pytorch/issues/64997
Both `block_diag` and `broadcast_tensors` are variadic, so skipping `test_variant_consistency_jit` (from comments on other OpInfos, it looks like JIT does not support variadic tensors)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/64993
Reviewed By: jbschlosser
Differential Revision: D30961736
Pulled By: soulitzer
fbshipit-source-id: e169305384a683acae1178c4e12e9e214a67226a
Summary:
This PR adds forward mode differentiation for `torch.linalg.eigh` and a few other functions required for tests to pass.
For some reason running tests for `torch.linalg.eigvalsh` and complex `torch.linalg.eigh` hangs. These tests are skipped for now.
cc ezyang albanD zou3519 gqchen pearu nikitaved soulitzer Lezcano Varal7 jianyuh mruberry heitorschueroff walterddr IvanYashchuk xwang233
Pull Request resolved: https://github.com/pytorch/pytorch/pull/62163
Reviewed By: jbschlosser
Differential Revision: D30903988
Pulled By: albanD
fbshipit-source-id: d6a74adb9e6d2f4be8ac707848ecabf06d629823
