[v1.5.0] float2::x and float2::y may not be the same as float on ROCm…

[gchanan]

… (#35593)

Summary:
This causes ambiguity and can be triggered sometimes (e.g., by #35217). Explicitly convert them to float.

error: conditional expression is ambiguous; 'const
hip_impl::Scalar_accessor<float, Native_vec_, 0>' can be converted to
'float' and vice versa

Pull Request resolved: #35593

Differential Revision: D20735663

Pulled By: ezyang

fbshipit-source-id: ae6a38a08e59821bae13eb0b9f9bdf21a008d5c0

[dr-ci]

💊 CircleCI build failures summary and remediations

As of commit 8bd6fad (more details on the Dr. CI page):

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• 1/1 failures introduced in this PR

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🕵️ 1 new failure recognized by patterns

The following build failures do not appear to be due to upstream breakages:

pytorch_linux_backward_compatibility_check_test (1/1)

Step: "Test" (full log | pattern match details) <confirmed not flaky by 2 failures>

Mar 31 23:32:09 The PR is introducing backward incompatible changes to the operator library. Please contact PyTorch team to confirm whether this change is wanted or not.

Mar 31 23:32:09 processing existing schema:  aten::sparse_coo_tensor.size(int[] size, *, int dtype, int layout, Device device, bool pin_memory=False) -> (Tensor) 
Mar 31 23:32:09 processing existing schema:  aten::sparse_coo_tensor.indices(Tensor indices, Tensor values, *, int? dtype=None, int? layout=None, Device? device=None, bool? pin_memory=None) -> (Tensor) 
Mar 31 23:32:09 processing existing schema:  aten::sparse_coo_tensor.indices_size(Tensor indices, Tensor values, int[] size, *, int? dtype=None, int? layout=None, Device? device=None, bool? pin_memory=None) -> (Tensor) 
Mar 31 23:32:09 processing existing schema:  aten::split_with_sizes(Tensor self, int[] split_sizes, int dim=0) -> (Tensor[]) 
Mar 31 23:32:09 processing existing schema:  aten::squeeze(Tensor(a) self) -> (Tensor(a)) 
Mar 31 23:32:09 processing existing schema:  aten::squeeze.dim(Tensor(a) self, int dim) -> (Tensor(a)) 
Mar 31 23:32:09 processing existing schema:  aten::stft(Tensor self, int n_fft, int? hop_length=None, int? win_length=None, Tensor? window=None, bool normalized=False, bool onesided=True) -> (Tensor) 
Mar 31 23:32:09 skipping schema:  aten::sub_.Tensor(Tensor(a!) self, Tensor other, *, Scalar alpha=1) -> (Tensor(a!)) 
Mar 31 23:32:09 skipping schema:  aten::sub_.Scalar(Tensor(a!) self, Scalar other, Scalar alpha=1) -> (Tensor(a!)) 
Mar 31 23:32:09 processing existing schema:  aten::t(Tensor(a) self) -> (Tensor(a)) 
Mar 31 23:32:09 The PR is introducing backward incompatible changes to the operator library. Please contact PyTorch team to confirm whether this change is wanted or not.  
Mar 31 23:32:09  
Mar 31 23:32:09 Broken ops: [ 
Mar 31 23:32:09 	aten::local_value(RRef(t) self) -> (t) 
Mar 31 23:32:09 	_aten::full(int[] size, Scalar fill_value, *, int? dtype=None, int? layout=None, Device? device=None, bool? pin_memory=None) -> (Tensor) 
Mar 31 23:32:09 	_aten::dequantize(Tensor self) -> (Tensor) 
Mar 31 23:32:09 	_aten::quantize_per_tensor(Tensor self, float scale, int zero_point, int dtype) -> (Tensor) 
Mar 31 23:32:09 	_aten::div.Tensor(Tensor self, Tensor other) -> (Tensor) 
Mar 31 23:32:09 	_aten::detach(Tensor self) -> (Tensor) 
Mar 31 23:32:09 	prim::id(AnyClassType? x) -> (int) 
Mar 31 23:32:09 	aten::owner(RRef(t) self) -> (__torch__.torch.classes.dist_rpc.WorkerInfo) 

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This comment has been revised 2 times.

[gchanan]

Going to merge this because it looks like it half fixes the problem, see master PR #35784 for more.