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* Fix failing set_env test * Fix test failiing due to deprectation of env.seed * Adjust mean reward threshold in failing test * Fix her test failing due to rng * Change seed and revert reward threshold to 90 * Pin gym version * Make VecEnv compatible with gym seeding change * Revert change to VecEnv reset signature * Change subprocenv seed cmd to call reset instead * Fix type check * Add backward compat * Add `compat_gym_seed` helper * Add goal env checks in env_checker * Add docs on HER requirements for envs * Capture user warning in test with inverted box space * Update ale-py version * Fix randint * Allow noop_max to be zero * Update changelog * Update docker image * Update doc conda env and dockerfile * Custom envs should not have any warnings * Fix test for numpy >= 1.21 * Add check for vectorized compute reward * Bump to gym 0.24 * Fix gym default step docstring * Test downgrading gym * Revert "Test downgrading gym" This reverts commit 0072b77156c006ada8a1d6e26ce347ed85a83eeb. * Fix protobuf error * Fix in dependencies * Fix protobuf dep * Use newest version of cartpole * Update gym * Fix warning * Loosen required scipy version * Scipy no longer needed * Try gym 0.25 * Silence warnings from gym * Filter warnings during tests * Update doc * Update requirements * Add gym 26 compat in vec env * Fixes in envs and tests for gym 0.26+ * Enforce gym 0.26 api * format * Fix formatting * Fix dependencies * Fix syntax * Cleanup doc and warnings * Faster tests * Higher budget for HER perf test (revert prev change) * Fixes and update doc * Fix doc build * Fix breaking change * Fixes for rendering * Rename variables in monitor * update render method for gym 0.26 API backwards compatible (mode argument is allowed) while using the gym 0.26 API (render mode is determined at environment creation) * update tests and docs to new gym render API * undo removal of render modes metatadata check * set rgb_array as default render mode for gym.make * undo changes & raise warning if not 'rgb_array' * Fix type check * Remove recursion and fix type checking * Remove hacks for protobuf and gym 0.24 * Fix type annotations * reuse existing render_mode attribute * return tiled images for 'human' render mode * Allow to use opencv for human render, fix typos * Add warning when using non-zero start with Discrete (fixes #1197) * Fix type checking * Bug fixes and handle more cases * Throw proper warnings * Update test * Fix new metadata name * Ignore numpy warnings * Fixes in vec recorder * Global ignore * Filter local warning too * Monkey patch not needed for gym 26 * Add doc of VecEnv vs Gym API * Add render test * Fix return type * Update VecEnv vs Gym API doc * Fix for custom render mode * Fix return type * Fix type checking * check test env test_buffer * skip render check * check env test_dict_env * test_env test_gae * check envs in remaining tests * Update tests * Add warning for Discrete action space with non-zero (#1295) * Fix atari annotation * ignore get_action_meanings [attr-defined] * Fix mypy issues * Add patch for gym/gymnasium transition * Switch to gymnasium * Rely on signature instead of version * More patches * Type ignore because of https://github.com/Farama-Foundation/Gymnasium/pull/39 * Fix doc build * Fix pytype errors * Fix atari requirement * Update env checker due to change in dtype for Discrete * Fix type hint * Convert spaces for saved models * Ignore pytype * Remove gitlab CI * Disable pytype for convert space * Fix undefined info * Fix undefined info * Upgrade shimmy * Fix wrappers type annotation (need PR from Gymnasium) * Fix gymnasium dependency * Fix dependency declaration * Cap pygame version for python 3.7 * Point to master branch (v0.28.0) * Fix: use main not master branch * Rename done to terminated * Fix pygame dependency for python 3.7 * Rename gym to gymnasium * Update Gymnasium * Fix test * Fix tests * Forks don't have access to private variables * Fix linter warnings * Update read the doc env * Fix env checker for GoalEnv * Fix import * Update env checker (more info) and fix dtype * Use micromamab for Docker * Update dependencies * Clarify VecEnv doc * Fix Gymnasium version * Copy file only after mamba install * [ci skip] Update docker doc * Polish code * Reformat * Remove deprecated features * Ignore warning * Update doc * Update examples and changelog * Fix type annotation bundle (SAC, TD3, A2C, PPO, base class) (#1436) * Fix SAC type hints, improve DQN ones * Fix A2C and TD3 type hints * Fix PPO type hints * Fix on-policy type hints * Fix base class type annotation, do not use defaults * Update version * Disable mypy for python 3.7 * Rename Gym26StepReturn * Update continuous critic type annotation * Fix pytype complain --------- Co-authored-by: Carlos Luis <carlos.luisgonc@gmail.com> Co-authored-by: Quentin Gallouédec <45557362+qgallouedec@users.noreply.github.com> Co-authored-by: Thomas Lips <37955681+tlpss@users.noreply.github.com> Co-authored-by: tlips <thomas.lips@ugent.be> Co-authored-by: tlpss <thomas17.lips@gmail.com> Co-authored-by: Quentin GALLOUÉDEC <gallouedec.quentin@gmail.com>
111 lines
3.9 KiB
Python
111 lines
3.9 KiB
Python
import json
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import os
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import uuid
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import gymnasium as gym
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import pandas
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from stable_baselines3.common.monitor import Monitor, get_monitor_files, load_results
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def test_monitor(tmp_path):
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"""
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Test the monitor wrapper
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"""
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env = gym.make("CartPole-v1")
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env.reset(seed=0)
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monitor_file = os.path.join(str(tmp_path), f"stable_baselines-test-{uuid.uuid4()}.monitor.csv")
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monitor_env = Monitor(env, monitor_file)
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monitor_env.reset()
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total_steps = 1000
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ep_rewards = []
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ep_lengths = []
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ep_len, ep_reward = 0, 0
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for _ in range(total_steps):
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_, reward, terminated, truncated, _ = monitor_env.step(monitor_env.action_space.sample())
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ep_len += 1
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ep_reward += reward
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if terminated or truncated:
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ep_rewards.append(ep_reward)
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ep_lengths.append(ep_len)
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monitor_env.reset()
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ep_len, ep_reward = 0, 0
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monitor_env.close()
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assert monitor_env.get_total_steps() == total_steps
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assert sum(ep_lengths) == sum(monitor_env.get_episode_lengths())
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assert sum(monitor_env.get_episode_rewards()) == sum(ep_rewards)
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_ = monitor_env.get_episode_times()
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with open(monitor_file) as file_handler:
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first_line = file_handler.readline()
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assert first_line.startswith("#")
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metadata = json.loads(first_line[1:])
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assert metadata["env_id"] == "CartPole-v1"
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assert set(metadata.keys()) == {"env_id", "t_start"}, "Incorrect keys in monitor metadata"
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last_logline = pandas.read_csv(file_handler, index_col=None)
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assert set(last_logline.keys()) == {"l", "t", "r"}, "Incorrect keys in monitor logline"
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os.remove(monitor_file)
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# Check missing filename directories are created
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monitor_dir = os.path.join(str(tmp_path), "missing-dir")
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monitor_file = os.path.join(monitor_dir, f"stable_baselines-test-{uuid.uuid4()}.monitor.csv")
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assert os.path.exists(monitor_dir) is False
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_ = Monitor(env, monitor_file)
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assert os.path.exists(monitor_dir) is True
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os.remove(monitor_file)
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os.rmdir(monitor_dir)
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def test_monitor_load_results(tmp_path):
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"""
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test load_results on log files produced by the monitor wrapper
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"""
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tmp_path = str(tmp_path)
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env1 = gym.make("CartPole-v1")
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env1.reset(seed=0)
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monitor_file1 = os.path.join(tmp_path, f"stable_baselines-test-{uuid.uuid4()}.monitor.csv")
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monitor_env1 = Monitor(env1, monitor_file1)
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monitor_files = get_monitor_files(tmp_path)
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assert len(monitor_files) == 1
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assert monitor_file1 in monitor_files
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monitor_env1.reset()
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episode_count1 = 0
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for _ in range(1000):
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_, _, terminated, truncated, _ = monitor_env1.step(monitor_env1.action_space.sample())
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if terminated or truncated:
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episode_count1 += 1
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monitor_env1.reset()
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results_size1 = len(load_results(os.path.join(tmp_path)).index)
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assert results_size1 == episode_count1
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env2 = gym.make("CartPole-v1")
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env2.reset(seed=0)
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monitor_file2 = os.path.join(tmp_path, f"stable_baselines-test-{uuid.uuid4()}.monitor.csv")
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monitor_env2 = Monitor(env2, monitor_file2)
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monitor_files = get_monitor_files(tmp_path)
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assert len(monitor_files) == 2
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assert monitor_file1 in monitor_files
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assert monitor_file2 in monitor_files
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episode_count2 = 0
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for _ in range(2):
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# Test appending to existing file
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monitor_env2 = Monitor(env2, monitor_file2, override_existing=False)
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monitor_env2.reset()
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for _ in range(1000):
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_, _, terminated, truncated, _ = monitor_env2.step(monitor_env2.action_space.sample())
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if terminated or truncated:
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episode_count2 += 1
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monitor_env2.reset()
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results_size2 = len(load_results(os.path.join(tmp_path)).index)
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assert results_size2 == (results_size1 + episode_count2)
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os.remove(monitor_file1)
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os.remove(monitor_file2)
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