2021-05-20 16:05:53 +02:00

149 lines
4.6 KiB
Python

import pickle
from pathlib import Path
from collections import defaultdict
from stable_baselines3.common.callbacks import BaseCallback
class FactoryMonitor:
def __init__(self, env):
self._env = env
self._monitor = defaultdict(lambda: defaultdict(lambda: 0))
self._last_vals = defaultdict(lambda: 0)
def __iter__(self):
for key, value in self._monitor.items():
yield key, dict(value)
def add(self, key, value, step=None):
assert step is None or step >= 1 # Is this good practice?
step = step or self._env.steps
self._last_vals[key] = self._last_vals[key] + value
self._monitor[key][step] = self._last_vals[key]
return self._last_vals[key]
def set(self, key, value, step=None):
assert step is None or step >= 1 # Is this good practice?
step = step or self._env.steps
self._last_vals[key] = value
self._monitor[key][step] = self._last_vals[key]
return self._last_vals[key]
def remove(self, key, value, step=None):
assert step is None or step >= 1 # Is this good practice?
step = step or self._env.steps
self._last_vals[key] = self._last_vals[key] - value
self._monitor[key][step] = self._last_vals[key]
return self._last_vals[key]
def to_dict(self):
return dict(self)
def to_pd_dataframe(self):
import pandas as pd
df = pd.DataFrame.from_dict(self.to_dict())
try:
df.loc[0] = df.iloc[0].fillna(0)
except IndexError:
return None
df = df.fillna(method='ffill')
return df
def reset(self):
raise RuntimeError("DO NOT DO THIS! Always initalize a new Monitor per Env-Run.")
class MonitorCallback(BaseCallback):
ext = 'png'
def __init__(self, env, filepath=Path('debug_out/monitor.pick')):
super(MonitorCallback, self).__init__()
self.filepath = Path(filepath)
self._monitor_list = list()
self.env = env
self.started = False
self.closed = False
@property
def monitor_as_df_list(self):
return [x.to_pd_dataframe() for x in self._monitor_list]
def __enter__(self):
self._on_training_start()
def __exit__(self, exc_type, exc_val, exc_tb):
self._on_training_end()
def _on_training_start(self) -> None:
if self.started:
pass
else:
self.filepath.parent.mkdir(exist_ok=True, parents=True)
self.started = True
pass
def _on_training_end(self) -> None:
if self.closed:
pass
else:
# self.out_file.unlink(missing_ok=True)
with self.filepath.open('wb') as f:
pickle.dump(self.monitor_as_df_list, f, protocol=pickle.HIGHEST_PROTOCOL)
self.prepare_plot()
self.closed = True
def _on_step(self) -> bool:
if self.locals['dones'].item():
self._monitor_list.append(self.env.monitor)
else:
pass
def plot(self, **kwargs):
from matplotlib import pyplot as plt
plt.rcParams.update(kwargs)
plt.tight_layout()
figure = plt.gcf()
plt.show()
figure.savefig(str(self.filepath.parent / f'{self.filepath.stem}_monitor_measures.{self.ext}'), format=self.ext)
def prepare_plot(self):
# %% Imports
import pandas as pd
import seaborn as sns
# %% Load MonitorList from Disk
with self.filepath.open('rb') as f:
monitor_list = pickle.load(f)
result = pd.concat(monitor_list, sort=False)
# result.tail()
# %%
lineplot = sns.lineplot(data=result)
lineplot.title.title = f'Lineplot Summary of {len(monitor_list)} Episodes'
# %%
sns.set_theme(palette='husl', style='whitegrid')
font_size = 16
tex_fonts = {
# Use LaTeX to write all text
"text.usetex": True,
"font.family": "serif",
# Use 10pt font in plots, to match 10pt font in document
"axes.labelsize": font_size,
"font.size": font_size,
# Make the legend/label fonts a little smaller
"legend.fontsize": font_size - 2,
"xtick.labelsize": font_size - 2,
"ytick.labelsize": font_size - 2
}
try:
self.plot(**tex_fonts)
except FileNotFoundError:
tex_fonts['text.usetex'] = False
self.plot(**tex_fonts)