Statistics caching update from pickle to safetensors (#3122)

### Changes

Update module to dump and load statistics from pickle to safetensors.
Statistics are saved and are loaded in the backend tensor representation
(torch, numpy).

### Reason for changes

Safe issues with pickle

### Related tickets

157343

### Tests

Tests were updated

Author: kshpv

docs/api/source/conf.py

@@ -143,6 +143,8 @@ def collect_api_entities() -> APIInfo:
     "nncf.tensor.functions.numpy_linalg",
     "nncf.tensor.functions.torch_numeric",
     "nncf.tensor.functions.torch_linalg",
+    "nncf.tensor.functions.torch_io",
+    "nncf.tensor.functions.numpy_io",
 ]
 
 with mock(mock_modules):

licensing/third-party-programs.txt

@@ -1617,3 +1617,212 @@ NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE
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+
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+
+huggingface/safetensors
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nncf/__init__.py

@@ -26,6 +26,7 @@
 from nncf.errors import InvalidQuantizerGroupError as InvalidQuantizerGroupError
 from nncf.errors import ModuleNotFoundError as ModuleNotFoundError
 from nncf.errors import ParameterNotSupportedError as ParameterNotSupportedError
+from nncf.errors import StatisticsCacheError as StatisticsCacheError
 from nncf.errors import UnknownDatasetError as UnknownDatasetError
 from nncf.errors import UnsupportedBackendError as UnsupportedBackendError
 from nncf.errors import UnsupportedDatasetError as UnsupportedDatasetError

nncf/common/tensor_statistics/aggregator.py

@@ -12,11 +12,10 @@
 from abc import ABC
 from abc import abstractmethod
 from itertools import islice
+from pathlib import Path
 from typing import Any, Dict, Optional, TypeVar
 
 import nncf
-import nncf.common.tensor_statistics.statistics_serializer as statistics_serializer
-import nncf.common.tensor_statistics.statistics_validator as statistics_validator
 from nncf.common import factory
 from nncf.common.graph.graph import NNCFGraph
 from nncf.common.graph.transformations.commands import TargetPoint
@@ -25,6 +24,8 @@
 from nncf.common.logging.track_progress import track
 from nncf.common.tensor import NNCFTensor
 from nncf.common.tensor_statistics.statistic_point import StatisticPointsContainer
+from nncf.common.tensor_statistics.statistics_serializer import dump_statistics
+from nncf.common.tensor_statistics.statistics_serializer import load_statistics
 from nncf.common.utils.backend import BackendType
 from nncf.data.dataset import DataItem
 from nncf.data.dataset import Dataset
@@ -96,16 +97,15 @@ def collect_statistics(self, model: TModel, graph: NNCFGraph) -> None:
                 f"smaller than the requested subset size {self.stat_subset_size}."
             )
 
-    def load_statistics_from_dir(self, dir_path: str) -> None:
+    def load_statistics_from_dir(self, dir_path: Path) -> None:
         """
         Loads statistics from a directory and populates the statistic points with the loaded data.
 
         :param dir_path: The name of the directory from which to load the statistics.
         """
-        loaded_data, metadata = statistics_serializer.load_from_dir(dir_path)
-        statistics_validator.validate_backend(metadata, self.BACKEND)
+        loaded_data = load_statistics(dir_path, self.BACKEND)
         self._load_statistics(loaded_data)
-        nncf_logger.info(f"Statistics were successfully loaded from a directory {dir_path}.")
+        nncf_logger.info(f"Statistics were successfully loaded from a directory {dir_path.absolute()}")
 
     def _load_statistics(self, data: Dict[str, Any]) -> None:
         """
@@ -118,19 +118,19 @@ def _load_statistics(self, data: Dict[str, Any]) -> None:
             statistics_key = self._get_statistics_key(statistics, statistic_point.target_point)
             if statistics_key not in data:
                 raise nncf.ValidationError(f"Not found statistics for {statistics_key}")
-            statistics_container = tensor_collector.create_statistics_container(data[statistics_key])
-            tensor_collector.set_cache(statistics_container)
+            statistics.load_data(data[statistics_key])
+            tensor_collector.set_cache(statistics)
 
-    def dump_statistics(self, dir_path: str) -> None:
+    def dump_statistics(self, dir_path: Path) -> None:
         """
         Dumps the current statistics to a directory in a compressed format.
 
         :param dir_path: The path of the directory where the statistics will be saved.
         """
         data_to_dump = self._prepare_statistics()
-        metadata = {"backend": self.BACKEND.value, "subset_size": self.stat_subset_size}
-        statistics_serializer.dump_to_dir(data_to_dump, dir_path, metadata)
-        nncf_logger.info(f"Statistics were successfully saved to a directory {dir_path}.")
+        additional_metadata = {"subset_size": self.stat_subset_size}
+        dump_statistics(data_to_dump, dir_path, self.BACKEND, additional_metadata)
+        nncf_logger.info(f"Statistics were successfully saved to a directory {dir_path.absolute()}")
 
     def _prepare_statistics(self) -> Dict[str, Any]:
         """
@@ -142,7 +142,7 @@ def _prepare_statistics(self) -> Dict[str, Any]:
         for _, statistic_point, tensor_collector in self.statistic_points.get_tensor_collectors():
             statistics = tensor_collector.get_statistics()
             statistics_key = self._get_statistics_key(statistics, statistic_point.target_point)
-            data = statistics.get_data()
+            data = statistics.get_data(is_serialized=True)
             data_to_dump[statistics_key] = data
         return data_to_dump