Update on "[Array API] Add linalg.vecdot"

lezcano · lezcano · commit c926457252dc · 2022-01-03T10:51:21.000Z
This PR adds the function `linalg.vecdot` specified by the [Array API](https://data-apis.org/array-api/latest/API_specification/linear_algebra_functions.html#function-vecdot) For the complex case, it chooses to implement \sum x_i y_i. See the discussion in data-apis/array-api#356 Edit. When it comes to testing, this function is not quite a binopt, nor a reduction opt. As such, we're this close to be able to get the extra testing, but we don't quite make it. Now, it's such a simple op that I think we'll make it without this. cc mruberry rgommers pmeier asmeurer leofang AnirudhDagar asi1024 emcastillo kmaehashi [ghstack-poisoned]
diff --git a/torch/testing/_internal/common_methods_invocations.py b/torch/testing/_internal/common_methods_invocations.py
@@ -968,7 +968,7 @@ def sample_inputs_reduction(op_info, device, dtype, requires_grad, **kwargs):
     supports_multiple_dims: bool = kwargs.get('supports_multiple_dims', True)
 
     # TODO(@heitorschueroff) Once all reduction operators are using ReductionOpInfo
-    # use op_info.genearte_args_kwargs directly.
+    # use op_info.generate_args_kwargs directly.
     generate_args_kwargs = kwargs.get('generate_args_kwargs', lambda *args, **kwargs: (yield tuple(), {}))
 
     inputs: List[SampleInput] = []
@@ -1101,7 +1101,7 @@ class ReductionOpInfo(OpInfo):
     the optional keyword parameters of the ReductionOpInfo constructor.
 
     If a reduction operator does not yet implement the full required API of
-    reduction operators, this should be documented by skipping the failing
+    reduction operators, this should be documented by xfailing the failing
     tests rather than adding optional parameters to ReductionOpInfo.
 
     NOTE
@@ -9787,17 +9787,16 @@ def ref_pairwise_distance(input1, input2):
            gradcheck_wrapper=gradcheck_wrapper_hermitian_input,
            decorators=[skipCUDAIfNoMagmaAndNoCusolver, skipCUDAIfRocm, skipCPUIfNoLapack],
            ),
-    BinaryUfuncInfo('linalg.vecdot',
-                    aten_name='linalg_vecdot',
-                    ref=lambda x, y, *, dim=-1: (x * y).sum(dim),
-                    dtypes=all_types_and_complex_and(torch.half, torch.bfloat16, torch.bool),
-                    sample_inputs_func=sample_inputs_linalg_vecdot,
-                    supports_forward_ad=True,
-                    supports_fwgrad_bwgrad=True,
-                    skips=(
-                        # torch.sum(out=) has an incorrect behaviour
-                        DecorateInfo(unittest.expectedFailure, 'TestCommon', 'test_out'),
-                    ),),
+    OpInfo('linalg.vecdot',
+           aten_name='linalg_vecdot',
+           ref=lambda x, y, *, dim=-1: (x * y).sum(dim),
+           dtypes=all_types_and_complex_and(torch.half, torch.bfloat16, torch.bool),
+           sample_inputs_func=sample_inputs_linalg_vecdot,
+           supports_forward_ad=True,
+           supports_fwgrad_bwgrad=True,
+           skips=(
+               # FIXME torch.sum(out=) has an incorrect behaviour
+               DecorateInfo(unittest.expectedFailure, 'TestCommon', 'test_out'),),),
     OpInfo('linalg.cond',
            aten_name='linalg_cond',
            dtypes=floating_and_complex_types(),
