MegEngine/imperative/python/megengine/jit/sublinear_memory_config.py

# -*- coding: utf-8 -*-
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2020 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.
from ..device import get_device_count


class SublinearMemoryConfig:
    r"""
    Configuration for sublinear memory optimization.

    :param thresh_nr_try: number of samples both for searching in linear space
        and around current thresh in sublinear memory optimization. Default: 10.
        It can also be set through the environmental variable 'MGB_SUBLINEAR_MEMORY_THRESH_NR_TRY'.
    :param genetic_nr_iter: number of iterations to find the best checkpoints in genetic algorithm.
        Default: 0.
        It can also be set through the environmental variable 'MGB_SUBLINEAR_MEMORY_GENETIC_NR_ITER'.
    :param genetic_pool_size: number of samples for the crossover random selection
        during genetic optimization. Default: 20.
        It can also be set through the environmental variable 'MGB_SUBLINEAR_MEMORY_GENETIC_POOL_SIZE'.
    :param lb_memory: memory lower bound of bottleneck size in MB for sublinear memory optimization.
        It can be used to perform manual tradeoff between memory and speed. Default: 0.
        It can also be set through the environmental variable 'MGB_SUBLINEAR_MEMORY_LOWER_BOUND_MB'.
    :param num_worker: number of thread workers to search the optimum checkpoints
        in sublinear memory optimization. Default: half of cpu number in the system.
        Note: the value must be greater or equal to one.
        It can also be set through the environmental variable 'MGB_SUBLINEAR_MEMORY_WORKERS'.

    Note that the environmental variable MGB_COMP_GRAPH_OPT must be set to 'enable_sublinear_memory_opt=1'
    in order for the above environmental variable to be effective.
    """

    def __init__(
        self,
        thresh_nr_try: int = 10,
        genetic_nr_iter: int = 0,
        genetic_pool_size: int = 20,
        lb_memory: int = 0,
        num_worker: int = max(1, get_device_count("cpu") // 2),
    ):
        assert thresh_nr_try >= 0, "thresh_nr_try must be greater or equal to zero"
        self.thresh_nr_try = thresh_nr_try
        assert genetic_nr_iter >= 0, "genetic_nr_iter must be greater or equal to zero"
        self.genetic_nr_iter = genetic_nr_iter
        assert (
            genetic_pool_size >= 0
        ), "genetic_pool_size must be greater or equal to zero"
        self.genetic_pool_size = genetic_pool_size
        self.lb_memory = lb_memory
        assert num_worker > 0, "num_worker must be greater or equal to one"
        self.num_worker = num_worker