Update test_nvfp4_tensor.py

Author: andrewor14

test/prototype/mx_formats/test_nvfp4_tensor.py

@@ -525,13 +525,23 @@ def test_nvfp4_matmul_with_amax(
     )
 
 
-@pytest.mark.skipif(not torch.cuda.is_available(), reason="CUDA not available")
-@pytest.mark.skipif(
-    not TORCH_VERSION_AT_LEAST_2_8, reason="NVFP4 requires PyTorch 2.8+"
-)
-def test_nvfp4_to_copy():
-    from torchao.prototype.mx_formats.nvfp4_tensor import NVFP4Tensor
-
-    torch.ops.aten._to_copy(
-        NVFP4Tensor.to_nvfp4(torch.randn((32, 128))), dtype=torch.bfloat16
-    )
+@pytest.mark.skipif(not torch.cuda.is_available(), reason="CUDA not available")                                     
+@pytest.mark.skipif(                                                                                                
+    not TORCH_VERSION_AT_LEAST_2_8, reason="NVFP4 requires PyTorch 2.8+"                                            
+)                                                                                                                   
+def test_nvfp4_to_copy():                                                                                           
+    from torchao.prototype.mx_formats.nvfp4_tensor import NVFP4Tensor                                               
+                                                                                                                    
+    x = NVFP4Tensor.to_nvfp4(torch.randn((32, 128))).cuda()                                                         
+    y = torch.ops.aten._to_copy(x, dtype=torch.bfloat16)                                                            
+    assert torch.equal(x.qdata, y.qdata)                                                                            
+    assert torch.equal(x._scale_e4m3, y._scale_e4m3)                                                                
+    assert x._per_tensor_scale is None                                                                              
+    assert y._per_tensor_scale is None                                                                              
+    assert x._act_per_tensor_scale is None                                                                          
+    assert y._act_per_tensor_scale is None                                                                          
+    assert x._block_size == y._block_size                                                                           
+    assert x.use_triton_kernel == y.use_triton_kernel                                                               
+    assert x.act_quant_kwargs == y.act_quant_kwargs                                                                 
+    assert x.dtype == torch.float32                                                                                 
+    assert y.dtype == torch.bfloat16