Adding Len checks for subset size test

tests/openvino/native/quantization/test_quantization_pipeline.py

@@ -197,3 +197,34 @@ def test_ignored_scope_dump(ignored_options, expected_dump, tmp_path):
             assert dumped_model.get_rt_info(rt_path) == value
         else:
             assert dumped_model.has_rt_info(rt_path) is False
+
+@pytest.mark.parametrize("subset_size, expected_actual_subset_size", [[1, 1], [2, 1]])
+def test_dump(subset_size, expected_actual_subset_size, tmp_path):
+    model = WeightsModel().ov_model
+    dataset = get_dataset_for_test(model)  # dataset.get_length() == 1
+    quantize_parameters = {
+        "preset": QuantizationPreset.PERFORMANCE,
+        "target_device": TargetDevice.CPU,
+        "subset_size": subset_size,
+        "fast_bias_correction": True,
+    }
+
+    quantized_model = quantize_impl(model, dataset, **quantize_parameters)
+    ov.save_model(quantized_model, tmp_path / "ov_model.xml")
+    core = ov.Core()
+    dumped_model = core.read_model(tmp_path / "ov_model.xml")
+
+    assert dumped_model.get_rt_info(["nncf", "quantization", "actual_subset_size"]) == str(expected_actual_subset_size)
+
+    # Check if dataset has __len__ implemented
+    if hasattr(dataset, '__len__'):
+        with warnings.catch_warnings(record=True) as w:
+            collect_statistics(dataset, subset_size)
+            if len(dataset) < subset_size:
+                assert len(w) > 0
+                assert "smaller than subset_size" in str(w[-1].message)
+    else:
+        # Handle the case when __len__ is not implemented
+        with warnings.catch_warnings(record=True) as w:
+            collect_statistics(dataset, subset_size)
+            assert len(w) == 0  # No warning expected