[BE] Unskip some tensor creation tests on Mac (pytorch#146952)

Followup after pytorch#145367

One should never use skip, but rather xfail otherwise one never knows when test is finally fixed.

`test_float_to_int_conversion_finite` were fixed on MacOS a while back (guess since the time Intel builds were disbaled), while `test_float_to_int_conversion_nonfinite` is fixed by pytorch#145367 that selects architecture-appropriate reference values for Arm ISA

Note, that results of floating to integral types cast are undefined if floating point value is outside of integral dynamic range

"Fixes" pytorch#38752

Pull Request resolved: pytorch#146952
Approved by: https://github.com/atalman, https://github.com/seemethere

Author: malfet

test/test_tensor_creation_ops.py

@@ -26,9 +26,7 @@
     set_default_dtype,
     set_default_tensor_type,
     TEST_SCIPY,
-    IS_MACOS,
     IS_PPC,
-    IS_JETSON,
     IS_WINDOWS,
     IS_FBCODE,
     IS_SANDCASTLE,
@@ -1051,8 +1049,6 @@ def _float_to_int_conversion_helper(self, vals, device, dtype, refs=None):
     # errors with UBSAN. These casts are deliberate in PyTorch, however, and
     # NumPy may have the same behavior.
     @onlyNativeDeviceTypes
-    @unittest.skipIf(IS_MACOS or IS_JETSON, "Test is broken on MacOS and Jetson, \
-        see https://github.com/pytorch/pytorch/issues/38752")
     @unittest.skipIf(IS_PPC, "Test is broken on PowerPC, see https://github.com/pytorch/pytorch/issues/39671")
     @dtypes(torch.bool, torch.uint8, torch.int8, torch.int16, torch.int32, torch.int64)
     def test_float_to_int_conversion_finite(self, device, dtype):
@@ -1081,10 +1077,10 @@ def test_float_to_int_conversion_finite(self, device, dtype):
         self._float_to_int_conversion_helper(vals, device, dtype, refs)
 
     # Note: CUDA will fail this test on most dtypes, often dramatically.
+    # Note: This test validates undefined behavior consistency in float-to-ints casts
     # NB: torch.uint16, torch.uint32, torch.uint64 excluded as this
     # nondeterministically fails, warning "invalid value encountered in cast"
     @onlyCPU
-    @unittest.skipIf(IS_MACOS, "Nonfinite conversion results on MacOS are different from others.")
     @unittest.skipIf(IS_S390X, "Test fails for int16 on s390x. Needs investigation.")
     @dtypes(torch.bool, torch.uint8, torch.int8, torch.int16, torch.int32, torch.int64)
     def test_float_to_int_conversion_nonfinite(self, device, dtype):