1) Fixed bug with clamp range in scale estimation.

nncf/quantization/algorithms/weight_compression/openvino_backend.py

@@ -33,6 +33,7 @@
 from nncf.quantization.algorithms.weight_compression.awq_patterns import get_awq_patterns
 from nncf.quantization.algorithms.weight_compression.backend import AWQAlgoBackend
 from nncf.quantization.algorithms.weight_compression.backend import WeightCompressionAlgoBackend
+from nncf.quantization.algorithms.weight_compression.config import WeightCompressionConfig
 from nncf.quantization.algorithms.weight_compression.config import WeightCompressionParameters
 from nncf.quantization.algorithms.weight_compression.weight_lowering import compress_weight
 from nncf.tensor import Tensor
@@ -222,11 +223,9 @@ def dump_parameters(
         dump_parameters(model, parameters, algo_name, path)
 
     @staticmethod
-    def get_compress_decompress_pipeline(
-        weight_compression_parameter: WeightCompressionParameters, w_shape, s_shape, z_p_shape=None
-    ):
+    def get_compress_decompress_pipeline(config: WeightCompressionConfig, w_shape, s_shape, z_p_shape=None):
         parameters, clamp = OVWeightCompressionAlgoBackend.get_compress_pipeline(
-            weight_compression_parameter, w_shape, s_shape, z_p_shape, True
+            config, w_shape, s_shape, z_p_shape, True
         )
 
         if len(parameters) == 3:
@@ -243,16 +242,14 @@ def get_compress_decompress_pipeline(
         return lambda parameters: compiled_model(parameters)[0]
 
     @staticmethod
-    def get_compress_pipeline(
-        weight_compression_parameter: WeightCompressionParameters, w_shape, s_shape, z_p_shape=None, return_nodes=False
-    ):
-        config = weight_compression_parameter.compression_config
+    def get_compress_pipeline(config: WeightCompressionConfig, w_shape, s_shape, z_p_shape=None, return_nodes=False):
         mode = config.mode
         assert mode in [CompressWeightsMode.INT4_SYM, CompressWeightsMode.INT4_ASYM]
         num_bits = config.num_bits
 
-        level_low = 0
-        level_high = 2**num_bits - 1
+        asym_quant = mode in [CompressWeightsMode.INT4_ASYM]
+        level_low = 0 if asym_quant else -(2 ** (num_bits - 1))
+        level_high = 2**num_bits - 1 if asym_quant else 2 ** (num_bits - 1) - 1
 
         w = opset.parameter(w_shape, name="w")
         s = opset.parameter(s_shape, name="s")

nncf/quantization/algorithms/weight_compression/scale_estimation.py

@@ -211,9 +211,11 @@ def apply(
                 compress_model = compress_decompress_cache[key]["compress_model"]
             else:
                 compress_decompress_model = self._backend_entity.get_compress_decompress_pipeline(
-                    wp, q_weights.shape, scale.shape, zp_shape
+                    wp.compression_config, q_weights.shape, scale.shape, zp_shape
+                )
+                compress_model = self._backend_entity.get_compress_pipeline(
+                    wp.compression_config, q_weights.shape, scale.shape, zp_shape
                 )
-                compress_model = self._backend_entity.get_compress_pipeline(wp, q_weights.shape, scale.shape, zp_shape)
                 compress_decompress_cache[key] = {
                     "compress_decompress_model": compress_decompress_model,
                     "compress_model": compress_model,

tests/openvino/native/quantization/test_weights_compression.py

@@ -28,6 +28,9 @@
 from nncf.quantization.algorithms.weight_compression.config import WeightCompressionConfig
 from nncf.quantization.algorithms.weight_compression.config import WeightCompressionParameters
 from nncf.quantization.algorithms.weight_compression.mixed_precision import MIXED_PRECISION_CRITERIA
+from nncf.quantization.algorithms.weight_compression.openvino_backend import OVWeightCompressionAlgoBackend
+from nncf.quantization.algorithms.weight_compression.weight_lowering import do_dequantization
+from nncf.quantization.algorithms.weight_compression.weight_lowering import do_integer_quantization
 from nncf.quantization.algorithms.weight_compression.weight_lowering import get_integer_quantization_error
 from nncf.quantization.algorithms.weight_compression.weight_lowering import reshape_weight_for_grouped_quantization
 from nncf.scopes import IgnoredScope
@@ -906,3 +909,31 @@ def test_mixed_precision_e2m1(mode, all_layers, ratio, ref_ids):
     }
     ref_nf4_nodes = {f"weights_{i}" for i in ref_ids}
     assert ref_nf4_nodes == names
+
+
+@pytest.mark.parametrize("mode", (CompressWeightsMode.INT4_SYM, CompressWeightsMode.INT4_ASYM))
+def test_np_ov_compression_decompression(mode):
+    sz = 8
+    w = np.arange(-sz, sz).reshape(2, sz).astype(np.float32)
+    w = Tensor(w)
+
+    config = WeightCompressionConfig(mode)
+
+    compressed_weighs, scale, zp = do_integer_quantization(w, -1, config)
+    decompressed_weighs = do_dequantization(compressed_weighs, scale, zp)
+
+    compressed_weighs = compressed_weighs.data
+    decompressed_weighs = decompressed_weighs.data
+    zp_shape = zp.shape if zp is not None else None
+
+    compress = OVWeightCompressionAlgoBackend.get_compress_pipeline(config, w.shape, scale.shape, zp_shape)
+    compress_decompress = OVWeightCompressionAlgoBackend.get_compress_decompress_pipeline(
+        config, w.shape, scale.shape, zp_shape
+    )
+
+    params = [w.data, scale.data, zp.data] if zp is not None else [w.data, scale.data]
+    compressed_weighs_ov = compress(params)
+    decompressed_weighs_ov = compress_decompress(params)
+
+    assert np.allclose(compressed_weighs, compressed_weighs_ov)
+    assert np.allclose(decompressed_weighs, decompressed_weighs_ov)