Conditionally define autocast_dtypes for different torch versions

tests/L0/run_fused_layer_norm/test_fused_layer_norm.py

@@ -75,8 +75,11 @@ def _prep_inputs(batch_size, normalized_shape, dtype):
         native = fused.clone().to(dtype).requires_grad_(True)
     return native, fused
 
-
-autocast_dtypes = (torch.half, torch.bfloat16) if torch.cuda.is_bf16_supported() else (torch.half,)
+TORCH_MAJOR, TORCH_MINOR = int(torch.__version__.split('.')[0]), int(torch.__version__.split('.')[1])
+if (TORCH_MAJOR <= 1 and TORCH_MINOR < 10):
+    autocast_dtypes = (torch.half,)
+else:
+    autocast_dtypes = (torch.half, torch.bfloat16) if torch.cuda.is_bf16_supported() else (torch.half,)
 
 
 class TestAutocastFusedLayerNorm(unittest.TestCase):