# -*- coding: utf-8 -*- # MegEngine is Licensed under the Apache License, Version 2.0 (the "License") # # Copyright (c) 2014-2021 Megvii Inc. All rights reserved. # # Unless required by applicable law or agreed to in writing, # software distributed under the License is distributed on an # "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. import re from typing import Union from ..core import set_option as _set_option from ..core._imperative_rt.core2 import clear_candidates as _clear_candidates _eviction_threshold = 0 _evictee_minimum_size = 1024 ** 2 _enable_sqrt_sampling = False def _str2bytes(text: str) -> int: regex = re.compile(r"(\d+(?:\.\d+)?)\s*([kmg]?b)", re.IGNORECASE) order = ["b", "kb", "mb", "gb"] result = regex.findall(text) if len(result) != 1: raise ValueError( "Formatting of `value` only supports bytes(B), kilobyte(KB), megabyte(MB) and gigabyte(GB) units" ) return int(float(result[0][0]) * 1024 ** order.index(result[0][1].lower())) @property def eviction_threshold(mod): r"""Get or set the eviction threshold in bytes. It can also be set to a string, whose formatting supports byte(B), kilobyte(KB), megabyte(MB) and gigabyte(GB) units. Note: When GPU memory usage exceeds this value, DTR will heuristically select and evict resident tensors until the amount of used memory falls below this threshold. Examples: .. code-block:: import megengine as mge mge.dtr.eviction_threshold = "2GB" """ return _eviction_threshold @eviction_threshold.setter def eviction_threshold(mod, value: Union[int, str]): global _eviction_threshold if isinstance(value, str): _eviction_threshold = _str2bytes(value) elif isinstance(value, int): _eviction_threshold = value else: raise TypeError("`value` should be a str or an int") _set_option("dtr_eviction_threshold", _eviction_threshold) @property def evictee_minimum_size(mod): r"""Get or set the memory threshold of tensors in bytes. It can also be set to a string, whose formatting supports byte(B), kilobyte(KB), megabyte(MB) and gigabyte(GB) units. Note: Only tensors whose size exceeds this threshold will be added to the candidate set. A tensor that is not added to the candidate set will never be evicted during its lifetime. Examples: .. code-block:: import megengine as mge mge.dtr.evictee_minimum_size = "2MB" """ return _evictee_minimum_size @evictee_minimum_size.setter def evictee_minimum_size(mod, value: Union[int, str]): global _evictee_minimum_size if isinstance(value, str): _evictee_minimum_size = _str2bytes(value) elif isinstance(value, int): _evictee_minimum_size = value else: raise TypeError("`value` should be a str or an int") _set_option("dtr_evictee_minimum_size", _evictee_minimum_size) @property def enable_sqrt_sampling(mod): r"""Get or set whether sqrt sampling is allowed. Sqrt sampling means that given the size of the candidate set is N, only enumerate sqrt(N) tensors. When the number of tensors is very high, enabling this optimization will speed up the training. Examples: .. code-block:: import megengine as mge mge.dtr.enable_sqrt_sampling = True """ return _enable_sqrt_sampling @enable_sqrt_sampling.setter def enable_sqrt_sampling(mod, value: bool): global _enable_sqrt_sampling _enable_sqrt_sampling = value _set_option("enable_dtr_sqrt_sampling", _enable_sqrt_sampling) def enable(): r"""Enable to record computing path of tensors and to perform DTR policy.""" _set_option("enable_dtr_auto_drop", 1) _set_option("enable_drop", 1) _set_option("record_computing_path", 1) def disable(): r"""Stop recording computing path of tensors and performing DTR policy.""" _set_option("enable_dtr_auto_drop", 0) _set_option("enable_drop", 0) _set_option("record_computing_path", 0) _clear_candidates()