huangfu/InteractionImitation
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

BUG FIXES: moving around when policy is loaded, adding BaseAlgorithm abstract classes, correcting metrics, normalizng actions if idm environment is a normalized action one, manually updating environment graph when using idm, implementing idm forward class

Browse Source
This commit is contained in:
Arec
2022-02-05 21:48:56 -08:00
parent 795e1c08b6
commit 3e6fce42ee
6 changed files with 195 additions and 197 deletions
Download Patch File Download Diff File Expand all files Collapse all files

24
src/evaluation/evaluation.py
View File

@@ -1,7 +1,7 @@
import numpy as np
from stable_baselines3.common.vec_env import VecEnv
from stable_baselines3.common.evaluation import evaluate_policy
from intersim.envs.intersimple import Intersimple
from intersim.envs.intersimple import Intersimple, IncrementingAgent
from typing import Callable, Dict, Optional
import os
import pickle
@@ -19,21 +19,18 @@ class IntersimpleEvaluation:
- whether there was a collision
- whether there was a hard brake
"""
def __init__(self, eval_env, use_pbar:bool=True):
def __init__(self, eval_env:IncrementingAgent, use_pbar:bool=True):
"""
Initialize evaluation environment with an Intersimple IncrementingAgent environment
Args:
eval_env (Intersimple.IncrementingAgent): evaluation environment that increments agent upon reset
eval_env (IncrementingAgent): evaluation environment that increments agent upon reset
use_pbar (bool): whether to use a progress bar
"""
# if env is a VecEnv, the code needs to be adapted, since the callback will be called after each step,
# so transitions of different envs will be mixed and the total number of episodes could be larger than n_eval_episodes!
assert not isinstance(eval_env, VecEnv)
# make sure we have specified an environment which increments the agent number on reset
assert isinstance(eval_env, Intersimple.IncrementingAgent)
self.env = eval_env
self.n_episodes = eval_env.nv
self.use_pbar = use_pbar
@@ -54,7 +51,7 @@ class IntersimpleEvaluation:
"""
Reset metrics prior to evaluation
"""
self._metrics = {key: [[]]*self.n_episodes for key in self.metric_keys_all}
self._metrics = {key: [[] for _ in range(self.n_episodes)] for key in self.metric_keys_all}
self._metrics.update({key: [None]*self.n_episodes for key in self.metric_keys_single})
def save(self, filestr):
@@ -66,8 +63,8 @@ class IntersimpleEvaluation:
"""
# assert metrics all have correct length
for key in self.metric_keys:
assert(len(self._metrics[key])==self.n_episodes,
f'_metrics[{key}] does not have length {self.n_episodes}')
assert len(self._metrics[key])==self.n_episodes, \
f'_metrics[{key}] does not have length {self.n_episodes}'
# make filepath
os.makedirs(os.path.dirname(filestr))
@@ -91,13 +88,13 @@ class IntersimpleEvaluation:
evaluate_policy(
policy,
self.env,
n_eval_episodes=self.n_eval_episodes,
n_eval_episodes=self.n_episodes,
callback=self.evaluate_policy_callback,
return_episode_rewards=False
)
if self.use_pbar:
self.pbar.close()
self.post_proc()
if filestr:
self.save(filestr)
@@ -119,6 +116,7 @@ class IntersimpleEvaluation:
self._metrics['v_all'][_agent].append(info['prev_state'][_agent,2].item())
self._metrics['a_all'][_agent].append(info['action_taken'][_agent,0].item())
col = info['collision']
if col:
assert done
self._metrics['col_all'][_agent].append(col)
@@ -138,7 +136,7 @@ class IntersimpleEvaluation:
self._metrics['a_all'][i] = np.array(self._metrics['a_all'][i])
# jerk
self._metrics['j_all'][i] = np.diff(self._metrics['a_all'][i]) / self.eval_env._env._dt
self._metrics['j_all'][i] = np.diff(self._metrics['a_all'][i]) / self.env._env._dt
# average velocity and acceleration
self._metrics['v_avg'][i] = np.mean(self._metrics['v_all'][i])