add torch_npu version assertion and show downstream testing result

Author: orangeH25

README.md

@@ -60,6 +60,12 @@ TorchAO is an easy to use quantization library for native PyTorch. TorchAO works
 
 Check out our [docs](https://docs.pytorch.org/ao/main/) for more details!
 
+## Third-party Pipeline Status
+
+| Backend    | Inference                                                    |
+| ---------- | ------------------------------------------------------------ |
+| Ascend NPU | [![Ascend NPU](https://github.com/Ascend/Ascend-CI/actions/workflows/torchao.yml/badge.svg)]( |
+
 ## 🚀 Quick Start
 
 First, install TorchAO. We recommend installing the latest stable version:

torchao/quantization/quantize_/workflows/int4/int4_plain_int32_tensor.py

@@ -163,9 +163,12 @@ def _from_hp_npu(
     w: torch.Tensor,
     block_size: List[int],
 ):
-    # Require PyTorch 2.7.1+ for NPU backend ops and backward compatibility.
-    assert torch_version_at_least("2.7.1"), (
-        "Need pytorch 2.7.1+ for NPU backend op support."
+    assert (
+        torch.accelerator.is_available()
+        and torch.accelerator.current_accelerator().type == "npu"
+        and torch_version_at_least("2.7.1")
+    ), (
+        f"PyTorch NPU 2.7.1+ needed for int4 packing and matmul ops, {torch.__version__} found"
     )
 
     assert w.ndim == 2 and w.device.type == "npu", (