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()
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