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Statistics caching update from pickle to safetensors (#3122)
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### 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
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kshpv authored Dec 13, 2024
1 parent 044e544 commit d927956
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2 changes: 2 additions & 0 deletions docs/api/source/conf.py
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Expand Up @@ -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):
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209 changes: 209 additions & 0 deletions licensing/third-party-programs.txt
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Expand Up @@ -1617,3 +1617,212 @@ NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE
LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION
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huggingface/safetensors

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-------------------------------------------------------------
1 change: 1 addition & 0 deletions nncf/__init__.py
Original file line number Diff line number Diff line change
Expand Up @@ -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
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26 changes: 13 additions & 13 deletions nncf/common/tensor_statistics/aggregator.py
Original file line number Diff line number Diff line change
Expand Up @@ -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
Expand All @@ -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
Expand Down Expand Up @@ -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:
"""
Expand All @@ -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]:
"""
Expand All @@ -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

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