From 83d77df216667db173a97c54bf06a5bfbe58afe1 Mon Sep 17 00:00:00 2001
From: steffen-illium <steffen.illium@ifi.lmu.de>
Date: Fri, 14 May 2021 15:21:31 +0200
Subject: [PATCH] Monitor and Agent State Merge
---
environments/factory/base_factory.py | 2 +-
.../factory/simple_factory_getting_dirty.py | 25 +++++++++++++------
2 files changed, 18 insertions(+), 9 deletions(-)
diff --git a/environments/factory/base_factory.py b/environments/factory/base_factory.py
index 2553245..b33c628 100644
--- a/environments/factory/base_factory.py
+++ b/environments/factory/base_factory.py
@@ -90,7 +90,7 @@ class BaseFactory:
self.slice_strings = {0: 'level', **{i: f'agent#{i}' for i in range(1, self.n_agents+1)}}
self.reset()
- def reset(self):
+ def reset(self) -> (np.ndarray, int, bool, dict):
self.done = False
self.steps = 0
self.cumulative_reward = 0
diff --git a/environments/factory/simple_factory_getting_dirty.py b/environments/factory/simple_factory_getting_dirty.py
index 1062091..4490e76 100644
--- a/environments/factory/simple_factory_getting_dirty.py
+++ b/environments/factory/simple_factory_getting_dirty.py
@@ -60,12 +60,12 @@ class GettingDirty(BaseFactory):
else:
raise RuntimeError('This should not happen!!!')
- def reset(self) -> None:
- # ToDo: When self.reset returns the new states and stuff, use it here!
- super().reset() # state, agents, ... =
+ def reset(self) -> (np.ndarray, int, bool, dict):
+ state, r, done, _ = super().reset() # state, reward, done, info ... =
dirt_slice = np.zeros((1, *self.state.shape[1:]))
self.state = np.concatenate((self.state, dirt_slice)) # dirt is now the last slice
self.spawn_dirt()
+ return self.state, r, self.done, {}
def calculate_reward(self, agent_states: List[AgentState]) -> (int, dict):
this_step_reward = 0
@@ -85,8 +85,17 @@ if __name__ == '__main__':
import random
dirt_props = DirtProperties()
factory = GettingDirty(n_agents=1, dirt_properties=dirt_props)
- random_actions = [random.randint(0, 8) for _ in range(2000)]
- for random_action in random_actions:
- state, r, done, _ = factory.step(random_action)
- print(f'Factory run done, reward is:\n {r}')
- print(f'The following running stats have been recorded:\n{dict(factory.monitor)}')
+ monitor_list = list()
+ for epoch in range(100):
+ random_actions = [random.randint(0, 7) for _ in range(200)]
+ state, r, done, _ = factory.reset()
+ for action in random_actions:
+ state, r, done, info = factory.step(action)
+ monitor_list.append(factory.monitor)
+ print(f'Factory run done, reward is:\n {r}')
+ from pathlib import Path
+ import pickle
+ out_path = Path('debug_out')
+ out_path.mkdir(exist_ok=True, parents=True)
+ with (out_path / 'monitor.pick').open('rb') as f:
+ pickle.dump(monitor_list, f)