Legacy unused torch aggregator is removed

Author: daniil-lyakhov

src/nncf/common/tensor_statistics/reduction.py

@@ -28,10 +28,8 @@
 from nncf.common.tensor_statistics.collectors import MeanVarianceReducer
 from nncf.common.tensor_statistics.collectors import MinReducer
 from nncf.common.tensor_statistics.collectors import QuantileReducer
-from nncf.common.tensor_statistics.collectors import TensorCollector
 from nncf.tensor import Tensor
 from nncf.tensor import functions as fns
-from nncf.torch.tensor_statistics.algo import create_register_input_hook
 from tests.common.test_reducers_and_aggregators import TemplateTestReducersAggregators
 
 
@@ -122,17 +120,3 @@ def test_median_function(use_cuda, size, ref):
     res = fns.median(tensor, axis=0)
     assert res.data == ref
     assert res.data.is_cuda == (device == "cuda")
-
-
-def test_create_register_input_hook_with_return_type(mocker):
-    collector = TensorCollector()
-    collector.register_input_for_all_reducers = mocker.MagicMock()
-    hook = create_register_input_hook(collector)
-    input_ = torch.return_types.max([torch.tensor((1,))] * 2)
-    output_ = hook(input_)
-    assert input_ is output_
-    mocker = collector.register_input_for_all_reducers
-    mocker.assert_called_once()
-    attr = mocker.call_args_list[0][0][0]
-    assert isinstance(attr, Tensor)
-    assert attr.data == torch.tensor(1)

src/nncf/torch/statistics/aggregator.py

@@ -12,8 +12,8 @@
 
 from nncf.common.graph.transformations.commands import TargetType
 from nncf.tensor import Tensor
+from nncf.torch.function_hook.statistics.aggregator import PT2StatisticsAggregator
 from nncf.torch.graph.transformations.commands import PTTargetPoint
-from nncf.torch.statistics.aggregator import PTStatisticsAggregator
 from tests.cross_fw.test_templates.test_statistics_caching import TemplateTestStatisticsCaching
 
 
@@ -22,7 +22,7 @@ def create_target_point(self, target_point_type: TargetType, name: str, port_id:
         return PTTargetPoint(target_type=target_point_type, target_node_name=name, input_port_id=port_id)
 
     def get_statistics_aggregator(self):
-        return PTStatisticsAggregator(None)
+        return PT2StatisticsAggregator(None)
 
     def _create_dummy_min_max_tensor(self) -> Tensor:
         return Tensor(torch.zeros(3)), Tensor(torch.ones(3))