[v1.5.0] Fix another case of float2::x and float2::y may not be the same on RO…

[gchanan]

…Cm (#35785)

Summary:
This is another case of the issue fixed in #35783. Mirroring 35786.
Pull Request resolved: #35785

Differential Revision: D20800317

Pulled By: ezyang

fbshipit-source-id: de5f32839755d5ff5aefff8408df69adbab4d0a1

[dr-ci]

💊 CircleCI build failures summary and remediations

As of commit 95ed37a (more details on the Dr. CI page):

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• 2/2 failures introduced in this PR

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🕵️ 2 new failures recognized by patterns

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

binary_linux_libtorch_2_7m_cpu_gcc5_4_cxx11-abi_shared-with-deps_build (1/2)

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

Apr 02 21:24:31 numpy/random/mtrand/mtrand.c:39645:11: error: �PyThreadState {aka struct _ts}� has no member named �exc_traceback�

Apr 02 21:24:31                            ^ 
Apr 02 21:24:31     numpy/random/mtrand/mtrand.c:39642:20: error: �PyThreadState {aka struct _ts}� has no member named �exc_traceback� 
Apr 02 21:24:31          tmp_tb = tstate->exc_traceback; 
Apr 02 21:24:31                         ^ 
Apr 02 21:24:31     numpy/random/mtrand/mtrand.c:39643:11: error: �PyThreadState {aka struct _ts}� has no member named �exc_type� 
Apr 02 21:24:31          tstate->exc_type = local_type; 
Apr 02 21:24:31                ^ 
Apr 02 21:24:31     numpy/random/mtrand/mtrand.c:39644:11: error: �PyThreadState {aka struct _ts}� has no member named �exc_value� 
Apr 02 21:24:31          tstate->exc_value = local_value; 
Apr 02 21:24:31                ^ 
Apr 02 21:24:31     numpy/random/mtrand/mtrand.c:39645:11: error: �PyThreadState {aka struct _ts}� has no member named �exc_traceback� 
Apr 02 21:24:31          tstate->exc_traceback = local_tb; 
Apr 02 21:24:31                ^ 
-x86_64-3.7/numpy/core/include/numpy -Inumpy/core/src/private -Inumpy/core/src -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray -Inumpy/core/src/umath -Inumpy/core/src/npysort -I/opt/conda/include/python3.7m -Ibuild/src.linux-x86_64-3.7/numpy/core/src/private -Ibuild/src.linux-x86_64-3.7/numpy/core/src/private -Ibuild/src.linux-x86_64-3.7/numpy/core/src/private -c numpy/random/mtrand/mtrand.c -o build/temp.linux-x86_64-3.7/numpy/random/mtrand/mtrand.o" failed with exit status 1 
Apr 02 21:24:31     ---------------------------------------- 
, tokenize; sys.argv[0] = '"'"'/tmp/pip-install-wlf32e6_/numpy/setup.py'"'"'; __file__='"'"'/tmp/pip-install-wlf32e6_/numpy/setup.py'"'"';f=getattr(tokenize, '"'"'open'"'"', open)(__file__);code=f.read().replace('"'"'\r\n'"'"', '"'"'\n'"'"');f.close();exec(compile(code, __file__, '"'"'exec'"'"'))' install --record /tmp/pip-record-444wxc_f/install-record.txt --single-version-externally-managed --compile --install-headers /opt/conda/include/python3.7m/numpy Check the logs for full command output. 

pytorch_linux_backward_compatibility_check_test (2/2)

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

Apr 02 21:34:50 The PR is introducing backward incompatible changes to the operator library. Please contact PyTorch team to confirm whether this change is wanted or not.

Apr 02 21:34:50 processing existing schema:  aten::sparse_coo_tensor.size(int[] size, *, int dtype, int layout, Device device, bool pin_memory=False) -> (Tensor) 
Apr 02 21:34:50 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) 
Apr 02 21:34:50 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) 
Apr 02 21:34:50 processing existing schema:  aten::split_with_sizes(Tensor self, int[] split_sizes, int dim=0) -> (Tensor[]) 
Apr 02 21:34:50 processing existing schema:  aten::squeeze(Tensor(a) self) -> (Tensor(a)) 
Apr 02 21:34:50 processing existing schema:  aten::squeeze.dim(Tensor(a) self, int dim) -> (Tensor(a)) 
Apr 02 21:34:50 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) 
Apr 02 21:34:50 processing existing schema:  aten::sub_.Tensor(Tensor(a!) self, Tensor other, *, Scalar alpha=1) -> (Tensor(a!)) 
Apr 02 21:34:50 processing existing schema:  aten::sub_.Scalar(Tensor(a!) self, Scalar other, Scalar alpha=1) -> (Tensor(a!)) 
Apr 02 21:34:50 processing existing schema:  aten::t(Tensor(a) self) -> (Tensor(a)) 
Apr 02 21:34:50 The PR is introducing backward incompatible changes to the operator library. Please contact PyTorch team to confirm whether this change is wanted or not.  
Apr 02 21:34:50  
Apr 02 21:34:50 Broken ops: [ 
Apr 02 21:34:50 	aten::owner(RRef(t) self) -> (__torch__.torch.classes.dist_rpc.WorkerInfo) 
Apr 02 21:34:50 	_aten::to.device(Tensor self, Device device, int dtype, bool non_blocking=False, bool copy=False, int? memory_format=None) -> (Tensor) 
Apr 02 21:34:50 	_aten::select.int(Tensor self, int dim, int index) -> (Tensor) 
Apr 02 21:34:50 	_aten::dequantize(Tensor self) -> (Tensor) 
Apr 02 21:34:50 	_aten::detach(Tensor self) -> (Tensor) 
Apr 02 21:34:50 	_aten::slice.Tensor(Tensor self, int dim, int start, int end, int step) -> (Tensor) 
Apr 02 21:34:50 	_aten::quantize_per_tensor(Tensor self, float scale, int zero_point, int dtype) -> (Tensor) 
Apr 02 21:34:50 	_prim::NumToTensor.Scalar(Scalar _0) -> (Tensor _0) 

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