93 lines
2.9 KiB
Python
93 lines
2.9 KiB
Python
import pickle
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from pathlib import Path
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from collections import defaultdict
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from stable_baselines3.common.callbacks import BaseCallback
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class FactoryMonitor:
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def __init__(self, env):
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self._env = env
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self._monitor = defaultdict(lambda: defaultdict(lambda: 0))
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self._last_vals = defaultdict(lambda: 0)
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def __iter__(self):
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for key, value in self._monitor.items():
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yield key, dict(value)
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def add(self, key, value, step=None):
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assert step is None or step >= 1 # Is this good practice?
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step = step or self._env.steps
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self._last_vals[key] = self._last_vals[key] + value
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self._monitor[key][step] = self._last_vals[key]
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return self._last_vals[key]
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def set(self, key, value, step=None):
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assert step is None or step >= 1 # Is this good practice?
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step = step or self._env.steps
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self._last_vals[key] = value
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self._monitor[key][step] = self._last_vals[key]
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return self._last_vals[key]
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def remove(self, key, value, step=None):
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assert step is None or step >= 1 # Is this good practice?
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step = step or self._env.steps
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self._last_vals[key] = self._last_vals[key] - value
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self._monitor[key][step] = self._last_vals[key]
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return self._last_vals[key]
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def to_dict(self):
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return dict(self)
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def to_pd_dataframe(self):
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import pandas as pd
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df = pd.DataFrame.from_dict(self.to_dict())
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try:
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df.loc[0] = df.iloc[0].fillna(0)
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except IndexError:
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return None
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df = df.fillna(method='ffill')
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return df
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def reset(self):
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raise RuntimeError("DO NOT DO THIS! Always initalize a new Monitor per Env-Run.")
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class MonitorCallback(BaseCallback):
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def __init__(self, env, outpath='debug_out', filename='monitor'):
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super(MonitorCallback, self).__init__()
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self._outpath = Path(outpath)
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self._filename = filename
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self.out_file = self._outpath / f'{self._filename.split(".")[0]}.pick'
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self.env = env
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self.started = False
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self.closed = False
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def __enter__(self):
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self._on_training_start()
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def __exit__(self, exc_type, exc_val, exc_tb):
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self._on_training_end()
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def _on_training_start(self) -> None:
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if self.started:
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pass
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else:
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self.out_file.parent.mkdir(exist_ok=True, parents=True)
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self.started = True
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pass
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def _on_training_end(self) -> None:
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if self.closed:
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pass
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else:
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# self.out_file.unlink(missing_ok=True)
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with self.out_file.open('wb') as f:
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pickle.dump(self.env.monitor_as_df_list, f, protocol=pickle.HIGHEST_PROTOCOL)
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self.closed = True
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def _on_step(self) -> bool:
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pass
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