[pt2] add meta for cholesky (#106115)

Pull Request resolved: #106115
Approved by: https://github.com/Skylion007, https://github.com/ezyang

test/functorch/test_aotdispatch.py

@@ -2746,9 +2746,6 @@ def forward(self, x):
     skip('as_strided_scatter'),
     skip('as_strided', 'partial_views'),  # flaky
 
-    # Too annoying to generate random inputs
-    xfail('cholesky'),
-
     # Given input size: (s0xs1x2). Calculated output size: ...
     skip('max_pool2d_with_indices_backward'),
 

test/test_meta.py

@@ -633,7 +633,6 @@ def run_meta_crossref(
     torch.nn.functional.gaussian_nll_loss : {f16, f64, bf16, f32},
     torch.nn.functional.one_hot : {i64},
     torch._segment_reduce : {f64, f16, bf16, f32},
-    torch.cholesky : {f64, f32, c128, c64},
     torch.cholesky_inverse : {f64, f32, c128, c64},
     torch.linalg.eig : {f64, f32, c128, c64},
     torch.linalg.eigvals : {f64, f32, c128, c64},
@@ -804,8 +803,6 @@ def __torch_function__(self, func, types, args=(), kwargs=None):
 # these always fail
 meta_dispatch_expected_failures = {
     aten.allclose.default: {f16, bf16, f32, f64, c64, c128},  # NotImplementedError: 'aten::_local_scalar_dense'
-    aten.cholesky.default : {c64, c128, f64, f32},
-    aten.cholesky.out : {c64, c128, f64, f32},
     aten.cholesky_inverse.default : {c64, c128, f64, f32},
     aten.cholesky_inverse.out : {c64, c128, f64, f32},
     aten.geqrf.default : {c64, c128, f64, f32},

test/test_ops.py

@@ -1935,7 +1935,6 @@ def test_refs_are_in_decomp_table(self, op):
 
 fake_skips = (
     "aminmax",  # failing input
-    "cholesky",  # Could not run 'aten::cholesky' with arguments from the 'Meta' backend
     "cholesky_inverse",  # Could not run 'aten::cholesky' with arguments from the 'Meta' backend
     "cov",  # aweights cannot be negtaive
     "istft",  # window overlap add min: 0
@@ -2014,7 +2013,6 @@ def test_refs_are_in_decomp_table(self, op):
     "roll",
     "svd_lowrank",
     "sgn",
-    "cholesky",
 }
 
 fake_backward_xfails = {skip(s) for s in fake_backward_skips} | {

test/test_proxy_tensor.py

@@ -1521,7 +1521,6 @@ def f(t):
 fake_tensor_failures = {
     # FakeTensor fallback doesn't work
     xfail('_segment_reduce', 'lengths'),
-    xfail('cholesky'),
     xfail('cholesky_inverse'),
     # cannot do these as they rely on tensor data
     xfail('repeat_interleave'),

torch/_meta_registrations.py

@@ -575,6 +575,15 @@ def cholesky_solve(self: Tensor, A: Tensor, upper: bool = False) -> Tensor:
     return _cholesky_solve_helper(self_broadcasted, A_broadcasted, upper)
 
 
+@register_meta(aten.cholesky)
+@out_wrapper()
+def cholesky(self: Tensor, upper: bool = False) -> Tensor:
+    if self.numel() == 0:
+        return torch.empty_like(self, memory_format=torch.legacy_contiguous_format)
+    squareCheckInputs(self, "cholesky")
+    return cloneBatchedColumnMajor(self)
+
+
 # From aten/src/ATen/native/BatchLinearAlgebra.cpp
 @register_meta(aten.linalg_cholesky_ex.default)
 def linalg_cholesky_ex(A: Tensor, upper: bool = False, check_errors: bool = False):