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profiler_simulate.py
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profiler_simulate.py
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# Copyright (c) 2019-2020, RTE (https://www.rte-france.com)
# See AUTHORS.txt
# This Source Code Form is subject to the terms of the Mozilla Public License, version 2.0.
# If a copy of the Mozilla Public License, version 2.0 was not distributed with this file,
# you can obtain one at http://mozilla.org/MPL/2.0/.
# SPDX-License-Identifier: MPL-2.0
# This file is part of Grid2Op, Grid2Op a testbed platform to model sequential decision making in power systems.
"""
This file aims at profiling a case where the "simulate" function is heavily used.
"""
import grid2op
import warnings
try:
from lightsim2grid import LightSimBackend
bk_cls = LightSimBackend
nm_bk_used = "LightSimBackend"
print("LightSimBackend used")
except ImportError:
from grid2op.Backend import PandaPowerBackend
bk_cls = PandaPowerBackend
nm_bk_used = "PandaPowerBackend"
print("PandaPowerBackend used")
import os
import cProfile
import pdb
def make_env():
env_name = "l2rpn_icaps_2021"
with warnings.catch_warnings():
warnings.filterwarnings("ignore")
fake_env = grid2op.make(env_name, test=True)
param = fake_env.parameters
param.NO_OVERFLOW_DISCONNECTION = True
env = grid2op.make(env_name+"_small", backend=LightSimBackend(), param=param)
return env
def run_env(env):
done = False
while not done:
act = env.action_space()
obs, reward, done, info = env.step(act)
if not done:
simulate(obs, env.action_space())
def simulate(obs, act):
simobs, rim_r, sim_d, sim_info = obs.simulate(act)
if __name__ == "__main__":
env = make_env()
cp = cProfile.Profile()
cp.enable()
run_env(env)
cp.disable()
nm_f, ext = os.path.splitext(__file__)
nm_out = f"{nm_f}_{nm_bk_used}.prof"
cp.dump_stats(nm_out)
print("You can view profiling results with:\n\tsnakeviz {}".format(nm_out))