|
28 | 28 | "_empty_dim_order.out(int[] size, *, int[]? dim_order=None, Tensor(a!) out) -> Tensor(a!)" |
29 | 29 | ) |
30 | 30 |
|
31 | | -lib.define( |
32 | | - "_clone_dim_order(Tensor self, *, bool non_blocking=False, int[]? dim_order=None) -> Tensor" |
33 | | -) |
34 | | - |
35 | | -lib.define( |
36 | | - "_clone_dim_order.out(Tensor self, *, bool non_blocking=False, int[]? dim_order=None, Tensor(a!) out) -> Tensor(a!)" |
37 | | -) |
38 | | - |
39 | 31 |
|
40 | 32 | def _op_impl(target, *args, **kwargs): |
41 | 33 | kwargs["memory_format"] = get_memory_format(kwargs.get("dim_order", None)) |
@@ -65,16 +57,6 @@ def _empty_dim_order_out_impl(*args, **kwargs): |
65 | 57 | return _op_impl(torch.ops.aten.empty.out, *args, **kwargs) |
66 | 58 |
|
67 | 59 |
|
68 | | -@impl(lib, "_clone_dim_order", "CompositeImplicitAutograd") |
69 | | -def _clone_dim_order_impl(*args, **kwargs): |
70 | | - return _op_impl(torch.ops.aten.clone.default, *args, **kwargs) |
71 | | - |
72 | | - |
73 | | -@impl(lib, "_clone_dim_order.out", "CompositeImplicitAutograd") |
74 | | -def _clone_dim_order_out_impl(*args, **kwargs): |
75 | | - return _op_impl(torch.ops.aten.clone.out, *args, **kwargs) |
76 | | - |
77 | | - |
78 | 60 | """ |
79 | 61 | Defines a map of edge ops to the corresponding dim_order ops for quick lookup |
80 | 62 | """ |
|
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