upd reference

tests/cross_fw/test_templates/template_test_weights_compression.py

@@ -147,16 +147,17 @@ def test_scale_estimation(self, mocker):
         model = self.get_model_for_test_scale_estimation()
 
         # prepare dataset with one input tensor
-        input = np.arange(0, 32 * 32, dtype=np.float32).reshape(1, 32, 32)
-        input[0, 15] *= 100  # make one channel relatively higher.
+        input = np.arange(0, 8 * 8, dtype=np.float32).reshape(1, 8, 8)
+        input[0, 4] *= 100  # make one channel relatively higher.
+
         input = self.to_tensor(input)
         dataset = Dataset([input])
 
         _ = compress_weights(
             model,
             mode=CompressWeightsMode.INT4_ASYM,
             ratio=1.0,
-            group_size=32,
+            group_size=4,
             scale_estimation=True,
             all_layers=True,
             dataset=dataset,

tests/openvino/native/models.py

@@ -1187,11 +1187,11 @@ def _create_ov_model(self):
         return model
 
 
-class MLP(OVReferenceModel):
+class MatMul(OVReferenceModel):
     def _create_ov_model(self):
-        input_node = opset.parameter([1, 32, 32], name="Input")
+        input_node = opset.parameter([1, 8, 8], name="Input")
 
-        weights_data = np.arange(0, 32 * 32, dtype=np.float32).reshape(32, 32)
+        weights_data = np.arange(0, 8 * 8, dtype=np.float32).reshape(8, 8)
         weights_node = opset.constant(weights_data, dtype=np.float32, name="Weights")
 
         matmul_node = opset.matmul(input_node, weights_node, transpose_a=False, transpose_b=True, name="MatMul")

tests/openvino/native/quantization/test_weights_compression.py

@@ -50,13 +50,13 @@
 from tests.cross_fw.test_templates.template_test_weights_compression import ACTIVATION
 from tests.cross_fw.test_templates.template_test_weights_compression import TemplateWeightCompression
 from tests.openvino.native.common import get_actual_reference_for_current_openvino
-from tests.openvino.native.models import MLP
 from tests.openvino.native.models import AWQActMatmulModel
 from tests.openvino.native.models import AWQMatmulModel
 from tests.openvino.native.models import GatherAndMatmulShareData
 from tests.openvino.native.models import GatherWithTwoReductionAxes
 from tests.openvino.native.models import IdentityMatmul
 from tests.openvino.native.models import IntegerModel
+from tests.openvino.native.models import MatMul
 from tests.openvino.native.models import ModelNamedConsts
 from tests.openvino.native.models import OVReferenceModel
 from tests.openvino.native.models import SequentialMatmulModel
@@ -1550,43 +1550,19 @@ def check_weights(model: ov.Model, ref_ids: List[int]) -> None:
 
     @staticmethod
     def get_model_for_test_scale_estimation():
-        return MLP().ov_model
+        return MatMul().ov_model
 
     @staticmethod
     def get_scale_estimation_ref():
         return np.array(
             [
-                [[2.0666666]],
-                [[3.7624273]],
-                [[5.884783]],
-                [[8.03606]],
-                [[10.136832]],
-                [[12.291862]],
-                [[14.34415]],
-                [[16.449669]],
-                [[18.608639]],
-                [[20.802698]],
-                [[22.9477]],
-                [[25.083504]],
-                [[27.152409]],
-                [[29.141987]],
-                [[31.171442]],
-                [[33.044716]],
-                [[35.178047]],
-                [[37.31138]],
-                [[39.444714]],
-                [[41.578045]],
-                [[43.71138]],
-                [[45.844715]],
-                [[47.978046]],
-                [[50.11138]],
-                [[52.244713]],
-                [[54.378044]],
-                [[56.511383]],
-                [[58.644714]],
-                [[60.77805]],
-                [[62.91138]],
-                [[65.044716]],
-                [[67.17805]],
+                [[0.2], [0.41354424]],
+                [[0.6782236], [0.9470368]],
+                [[1.1691767], [1.4355733]],
+                [[1.7025099], [1.9689066]],
+                [[2.2722175], [2.543369]],
+                [[2.8146443], [3.0858421]],
+                [[3.3025098], [3.5689068]],
+                [[3.8358433], [4.1022396]],
             ]
         )

tests/torch/ptq/test_weights_compression.py

@@ -383,43 +383,19 @@ def check_weights(model: torch.nn.Module, ref_ids: List[int]) -> None:
 
     @staticmethod
     def get_model_for_test_scale_estimation():
-        return LinearModel(torch.arange(0, 32 * 32, dtype=torch.float32).reshape(32, 32))
+        return LinearModel(torch.arange(0, 8 * 8, dtype=torch.float32).reshape(8, 8))
 
     @staticmethod
     def get_scale_estimation_ref():
         return torch.tensor(
             [
-                [[2.0666666]],
-                [[3.7624271]],
-                [[5.8847833]],
-                [[8.0360603]],
-                [[10.1368332]],
-                [[12.2918606]],
-                [[14.3441496]],
-                [[16.4496689]],
-                [[18.6086369]],
-                [[20.8027000]],
-                [[22.9477024]],
-                [[25.0835018]],
-                [[27.1524105]],
-                [[29.1419849]],
-                [[31.1714401]],
-                [[33.0447121]],
-                [[35.1780472]],
-                [[37.3113823]],
-                [[39.4447136]],
-                [[41.5780487]],
-                [[43.7113838]],
-                [[45.8447189]],
-                [[47.9780464]],
-                [[50.1113815]],
-                [[52.2447128]],
-                [[54.3780441]],
-                [[56.5113831]],
-                [[58.6447144]],
-                [[60.7780533]],
-                [[62.9113808]],
-                [[65.0447083]],
-                [[67.1780548]],
+                [[0.200000], [0.413544]],
+                [[0.678224], [0.947037]],
+                [[1.169177], [1.435573]],
+                [[1.702510], [1.968907]],
+                [[2.272218], [2.543369]],
+                [[2.814644], [3.085842]],
+                [[3.302510], [3.568907]],
+                [[3.835843], [4.102240]],
             ]
         )