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b86de98 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 | import gym
import memory_profiler
import pytest
from metaworld.envs.mujoco.env_dict import ALL_V1_ENVIRONMENTS
from tests.helpers import step_env
def build_and_step(env_cls):
env = env_cls()
step_env(env, max_path_length=150, iterations=10, render=False)
env.close()
def build_and_step_all(classes):
envs = []
for env_cls in classes:
env = build_and_step(env_cls)
envs += [env]
@pytest.fixture(scope='module')
def mt50_usage():
profile = {}
for env_cls in ALL_V1_ENVIRONMENTS.values():
target = (build_and_step, [env_cls], {})
memory_usage = memory_profiler.memory_usage(target)
profile[env_cls] = max(memory_usage)
return profile
@pytest.mark.skip
@pytest.mark.parametrize('env_cls', ALL_V1_ENVIRONMENTS.values())
def test_max_memory_usage(env_cls, mt50_usage):
# No env should use more than 250MB
#
# Note: this is quite a bit higher than the average usage cap, because
# loading a single environment incurs a fixed memory overhead which can't
# be shared among environment in the same process
assert mt50_usage[env_cls] < 250
@pytest.mark.skip
def test_avg_memory_usage():
# average usage no greater than 60MB/env
target = (build_and_step_all, [ALL_V1_ENVIRONMENTS.values()], {})
usage = memory_profiler.memory_usage(target)
average = max(usage) / len(ALL_V1_ENVIRONMENTS)
assert average < 60
@pytest.mark.skip
def test_from_task_memory_usage():
target = (ALL_V1_ENVIRONMENTS['reach-v1'], (), {})
usage = memory_profiler.memory_usage(target)
assert max(usage) < 250
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