Fixed typo in the warning from compress_weights (#2267)

### Changes

renamed name to node_name in the warning

### Reason for changes

chatglm model support

### Related tickets

125045

### Tests

test_not_quantize_with_multiple_reduction_axes

nncf/quantization/algorithms/weight_compression/openvino_backend.py

@@ -77,8 +77,8 @@ def do_compression(
                 if isinstance(reduction_axes, tuple) and len(reduction_axes) != 1:
                     nncf_logger.warning(
                         f"Weight compression expects a single reduction axes, but given {len(reduction_axes)}. "
-                        f"Weight shape: {const_shape}, reduction axes: {reduction_axes}, node name: {nncf_node.name}. "
-                        "The node won't be quantized."
+                        f"Weight shape: {const_shape}, reduction axes: {reduction_axes}, "
+                        f"node name: {nncf_node.node_name}. The node won't be quantized."
                     )
                     continue
                 reduction_axis = reduction_axes[0] if isinstance(reduction_axes, tuple) else reduction_axes

tests/openvino/native/models.py

@@ -786,3 +786,17 @@ def _create_ov_model(self):
         result.get_output_tensor(0).set_names(set(["Result"]))
         model = ov.Model([result], [input_node])
         return model
+
+
+class GatherWithTwoReductionAxes(OVReferenceModel):
+    def _create_ov_model(self):
+        input_1 = opset.parameter([2, 3], name="Input")
+        convert_1 = opset.convert(input_1, destination_type="i64", name="Convert_1")
+
+        gather_2_data = opset.constant(self._rng.random((3, 2, 1)), dtype=np.float32, name="gather_2_data")
+        gather_2 = opset.gather(gather_2_data, convert_1, axis=0, batch_dims=0)
+        gather_2.set_friendly_name("Gather_2")
+
+        result = opset.result(gather_2, name="Result")
+        model = ov.Model([result], [input_1])
+        return model

tests/openvino/native/quantization/test_weights_compression.py

@@ -25,6 +25,7 @@
 from nncf.quantization.algorithms.weight_compression.openvino_backend import _reshape_weights_for_grouped_quantization
 from nncf.scopes import IgnoredScope
 from tests.openvino.native.common import get_openvino_version
+from tests.openvino.native.models import GatherWithTwoReductionAxes
 from tests.openvino.native.models import IntegerModel
 from tests.openvino.native.models import SequentialMatmulModel
 from tests.openvino.native.models import WeightsModel
@@ -202,6 +203,14 @@ def test_mixed_precision(ratio, group_size, ref_nf4_nodes):
             assert op.get_element_type() == ov.Type.nf4
 
 
+def test_not_quantize_with_multiple_reduction_axes():
+    model = GatherWithTwoReductionAxes().ov_model
+    compressed_model = compress_weights(model, mode=CompressWeightsMode.INT8)
+    for op in compressed_model.get_ordered_ops():
+        if op.get_type_name() == "Constant" and op.get_friendly_name() == "gather_2_data":
+            assert op.get_element_type() == ov.Type(np.float32)
+
+
 @dataclass
 class QuantErrorDesc:
     weight: List[float]