The source code and dockerfile for the GSW2024 AI Lab.
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from __future__ import annotations
import gymnasium as gym
import numpy as np
from pytest_mock import MockerFixture
from minigrid.benchmark import benchmark
from minigrid.manual_control import ManualControl
from minigrid.minigrid_env import MiniGridEnv
def test_benchmark():
"Test that the benchmark function works for a specific environment"
env_id = "MiniGrid-Empty-16x16-v0"
benchmark(env_id, num_resets=10, num_frames=100)
def test_manual_control(mocker: MockerFixture):
class FakeRandomKeyboardEvent:
active_actions = ["left", "right", "up", " ", "pageup", "pagedown"]
reset_action = "backspace"
close_action = "escape"
def __init__(self, reset: bool = False, close: bool = False) -> None:
if reset:
self.key = self.reset_action
return
if close:
self.key = self.close_action
return
self.key = np.random.choice(self.active_actions)
env_id = "MiniGrid-Empty-16x16-v0"
env: MiniGridEnv = gym.make(env_id, render_mode="human")
manual_control = ManualControl(env)
for i in range(3): # 3 resets
manual_control.reset()
for j in range(20): # Do 20 steps
manual_control.key_handler(FakeRandomKeyboardEvent())
fake_event = FakeRandomKeyboardEvent(reset=True)
manual_control.key_handler(fake_event)
# Close the environment
mocked_quit = mocker.patch("pygame.quit")
fake_event = FakeRandomKeyboardEvent(close=True)
manual_control.key_handler(fake_event)
mocked_quit.assert_called_once()