def save_image(figure, filepath=None):
if os.environ['PY_ENV'] == 'test':
return
if filepath is None:
filepath = f'{PLOT_FILEDIR}/{ps.get(figure, "layout.title")}.png'
filepath = util.smart_path(filepath)
dirname, filename = os.path.split(filepath)
try:
cmd = f'orca graph -o {filename} \'{json.dumps(figure)}\''
if 'linux' in sys.platform:
cmd = 'xvfb-run -a -s "-screen 0 1400x900x24" -- ' + cmd
proc = Popen(cmd,
cwd=dirname,
shell=True,
stderr=DEVNULL,
stdout=DEVNULL)
try:
outs, errs = proc.communicate(timeout=20)
except TimeoutExpired:
proc.kill()
outs, errs = proc.communicate()
logger.info(f'Graph saved to {dirname}/{filename}')
except Exception as e:
logger.exception(
'Please install orca for plotly and run retro-analysis to generate graphs.'
)
def test_logger(test_str):
logger.critical(test_str)
logger.debug(test_str)
logger.error(test_str)
logger.exception(test_str)
logger.info(test_str)
logger.warning(test_str)
def test_logger(test_multiline_str):
logger.critical(test_multiline_str)
logger.debug(test_multiline_str)
logger.error(test_multiline_str)
logger.exception(test_multiline_str)
logger.info(test_multiline_str)
logger.warn(test_multiline_str)
def calc_trial_fitness_df(trial):
'''
Calculate the trial fitness df by aggregating from the collected session_data_dict (session_fitness_df's).
Adds a consistency dimension to fitness vector.
'''
trial_fitness_data = {}
try:
all_session_fitness_df = pd.concat(list(trial.session_data_dict.values()))
except ValueError as e:
logger.exception('Sessions failed, no data to analyze. Check stack trace above')
for aeb in util.get_df_aeb_list(all_session_fitness_df):
aeb_fitness_df = all_session_fitness_df.loc[:, aeb]
aeb_fitness_sr = aeb_fitness_df.mean()
consistency = calc_consistency(aeb_fitness_df)
aeb_fitness_sr = aeb_fitness_sr.append(pd.Series({'consistency': consistency}))
aeb_fitness_df = pd.DataFrame([aeb_fitness_sr], index=[trial.index])
aeb_fitness_df = aeb_fitness_df.reindex(FITNESS_COLS, axis=1)
trial_fitness_data[aeb] = aeb_fitness_df
# form multi_index df, then take mean across all bodies
trial_fitness_df = pd.concat(trial_fitness_data, axis=1)
mean_fitness_df = calc_mean_fitness(trial_fitness_df)
trial_fitness_df = mean_fitness_df
trial_fitness = calc_fitness(mean_fitness_df)
logger.info(f'Trial mean fitness: {trial_fitness}\n{mean_fitness_df}')
return trial_fitness_df
def save_image(figure, filepath=None):
if os.environ['PY_ENV'] == 'test':
return
if filepath is None:
filepath = f'{PLOT_FILEDIR}/{ps.get(figure, "layout.title")}.png'
filepath = util.smart_path(filepath)
try:
pio.write_image(figure, filepath)
logger.info(f'Graph saved to {filepath}')
except Exception as e:
logger.exception(
'Failed to generate graph. Fix the issue and run retro-analysis to generate graphs.')
def save_image(figure, filepath=None):
if os.environ['PY_ENV'] == 'test':
return
if filepath is None:
filepath = f'{PLOT_FILEDIR}/{ps.get(figure, "layout.title")}.png'
filepath = util.smart_path(filepath)
dirname, filename = os.path.split(filepath)
try:
Popen(['orca', 'graph', '--verbose', '-o', filename, json.dumps(figure)], cwd=dirname)
except Exception as e:
logger.exception(
'Please install orca for plotly and run retro-analysis to generate graphs.')
def get_ray_results(pending_ids, ray_id_to_config):
'''Helper to wait and get ray results into a new trial_data_dict, or handle ray error'''
trial_data_dict = {}
for _t in range(len(pending_ids)):
ready_ids, pending_ids = ray.wait(pending_ids, num_returns=1)
ready_id = ready_ids[0]
try:
trial_data = ray.get(ready_id)
trial_index = trial_data.pop('trial_index')
trial_data_dict[trial_index] = trial_data
except:
logger.exception(f'Trial failed: {ray_id_to_config[ready_id]}')
return trial_data_dict
def get_ray_results(pending_ids, ray_id_to_config):
'''Helper to wait and get ray results into a new trial_data_dict, or handle ray error'''
trial_data_dict = {}
for _t in range(len(pending_ids)):
ready_ids, pending_ids = ray.wait(pending_ids, num_returns=1)
ready_id = ready_ids[0]
try:
trial_data = ray.get(ready_id)
trial_index = trial_data.pop('trial_index')
trial_data_dict[trial_index] = trial_data
except:
logger.exception(f'Trial failed: {ray_id_to_config[ready_id]}')
return trial_data_dict
def check_all():
'''Check all spec files, all specs.'''
spec_files = _.filter_(os.listdir(SPEC_DIR), lambda f: f.endswith('.json'))
for spec_file in spec_files:
spec_dict = util.read(f'{SPEC_DIR}/{spec_file}')
for spec_name, spec in spec_dict.items():
try:
spec['name'] = spec_name
check(spec)
except Exception as e:
logger.exception(f'spec_file {spec_file} fails spec check')
raise e
logger.info(f'Checked all specs from: {_.join(spec_files, ",")}')
return True
def check_all():
'''Check all spec files, all specs.'''
spec_files = ps.filter_(os.listdir(SPEC_DIR), lambda f: f.endswith('.json') and not f.startswith('_'))
for spec_file in spec_files:
spec_dict = util.read(f'{SPEC_DIR}/{spec_file}')
for spec_name, spec in spec_dict.items():
try:
spec['name'] = spec_name
spec['git_SHA'] = subprocess.check_output(['git', 'rev-parse', 'HEAD']).decode().strip()
check(spec)
except Exception as e:
logger.exception(f'spec_file {spec_file} fails spec check')
raise e
logger.info(f'Checked all specs from: {ps.join(spec_files, ",")}')
return True
def check_all():
'''Check all spec files, all specs.'''
spec_files = ps.filter_(os.listdir(SPEC_DIR), lambda f: f.endswith('.json') and not f.startswith('_'))
for spec_file in spec_files:
spec_dict = util.read(f'{SPEC_DIR}/{spec_file}')
for spec_name, spec in spec_dict.items():
# fill-in info at runtime
spec['name'] = spec_name
spec = extend_meta_spec(spec)
try:
check(spec)
except Exception as e:
logger.exception(f'spec_file {spec_file} fails spec check')
raise e
logger.info(f'Checked all specs from: {ps.join(spec_files, ",")}')
return True
def save_image(figure, filepath=None):
if os.environ['PY_ENV'] == 'test':
return
if filepath is None:
filepath = f'{PLOT_FILEDIR}/{ps.get(figure, "layout.title")}.png'
filepath = util.smart_path(filepath)
dirname, filename = os.path.split(filepath)
try:
cmd = f'orca graph -o {filename} \'{json.dumps(figure)}\''
if 'linux' in sys.platform:
cmd = 'xvfb-run -a -s "-screen 0 1400x900x24" -- ' + cmd
Popen(cmd, cwd=dirname, shell=True, stderr=DEVNULL, stdout=DEVNULL)
logger.info(f'Graph saved to {dirname}/{filename}')
except Exception as e:
logger.exception(
'Please install orca for plotly and run retro-analysis to generate graphs.')
def check(spec):
'''Check a single spec for validity'''
try:
spec_name = spec.get('name')
assert set(spec.keys()) >= set(SPEC_FORMAT.keys()), f'Spec needs to follow spec.SPEC_FORMAT. Given \n {spec_name}: {util.to_json(spec)}'
for agent_spec in spec['agent']:
check_comp_spec(agent_spec, SPEC_FORMAT['agent'][0])
for env_spec in spec['env']:
check_comp_spec(env_spec, SPEC_FORMAT['env'][0])
check_comp_spec(spec['body'], SPEC_FORMAT['body'])
check_comp_spec(spec['meta'], SPEC_FORMAT['meta'])
check_body_spec(spec)
except Exception as e:
logger.exception(f'spec {spec_name} fails spec check')
raise e
return True
def check(spec):
'''Check a single spec for validity'''
try:
spec_name = spec.get('name')
assert set(spec.keys()) >= set(SPEC_FORMAT.keys()), f'Spec needs to follow spec.SPEC_FORMAT. Given \n {spec_name}: {util.to_json(spec)}'
for agent_spec in spec['agent']:
check_comp_spec(agent_spec, SPEC_FORMAT['agent'][0])
for env_spec in spec['env']:
check_comp_spec(env_spec, SPEC_FORMAT['env'][0])
check_comp_spec(spec['body'], SPEC_FORMAT['body'])
check_comp_spec(spec['meta'], SPEC_FORMAT['meta'])
# check_body_spec(spec)
check_compatibility(spec)
except Exception as e:
logger.exception(f'spec {spec_name} fails spec check')
raise e
return True
def try_register_env(spec):
'''Try to additional environments for OpenAI gym.'''
try:
env_name = spec['env'][0]['name']
if env_name == 'vizdoom-v0':
assert 'cfg_name' in spec['env'][0].keys(
), 'Environment config name must be defined for vizdoom.'
cfg_name = spec['env'][0]['cfg_name']
register(id=env_name,
entry_point='slm_lab.env.vizdoom.vizdoom_env:VizDoomEnv',
kwargs={'cfg_name': cfg_name})
elif env_name.startswith('Unity'):
# NOTE: do not specify max_episode_steps, will cause shape inconsistency in done
register(id=env_name,
entry_point='slm_lab.env.unity:GymUnityEnv',
kwargs={'name': env_name})
except Exception as e:
logger.exception(e)
def check_all():
'''Check all spec files, all specs.'''
spec_files = ps.filter_(
os.listdir(SPEC_DIR),
lambda f: f.endswith('.json') and not f.startswith('_'))
for spec_file in spec_files:
spec_dict = util.read(f'{SPEC_DIR}/{spec_file}')
for spec_name, spec in spec_dict.items():
try:
spec['name'] = spec_name
spec['git_SHA'] = subprocess.check_output(
['git', 'rev-parse', 'HEAD']).decode().strip()
check(spec)
except Exception as e:
logger.exception(f'spec_file {spec_file} fails spec check')
raise e
logger.info(f'Checked all specs from: {ps.join(spec_files, ",")}')
return True
def subproc_worker(pipe, parent_pipe, env_fn_wrapper, obs_bufs, obs_shapes,
obs_dtypes, keys):
'''
Control a single environment instance using IPC and shared memory. Used by ShmemVecEnv.
'''
def _write_obs(maybe_dict_obs):
flatdict = obs_to_dict(maybe_dict_obs)
for k in keys:
dst = obs_bufs[k].get_obj()
dst_np = np.frombuffer(dst,
dtype=obs_dtypes[k]).reshape(obs_shapes[k])
np.copyto(dst_np, flatdict[k])
env = env_fn_wrapper.x()
parent_pipe.close()
try:
while True:
cmd, data = pipe.recv()
if cmd == 'reset':
pipe.send(_write_obs(env.reset()))
elif cmd == 'step':
obs, reward, done, info = env.step(data)
if done:
obs = env.reset()
pipe.send((_write_obs(obs), reward, done, info))
elif cmd == 'render':
pipe.send(env.render(mode='rgb_array'))
elif cmd == 'close':
pipe.send(None)
break
else:
raise RuntimeError(f'Got unrecognized cmd {cmd}')
except KeyboardInterrupt:
logger.exception('ShmemVecEnv worker: got KeyboardInterrupt')
finally:
env.close()
