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param update

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Steffen Illium
2021-11-24 17:59:02 +01:00
parent 3833a0a064
commit 3c84ba483b
2 changed files with 7 additions and 10 deletions
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5
reload_agent.py
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@@ -50,9 +50,8 @@ if __name__ == '__main__':
rew, done_bool = 0, False
while not done_bool:
if n_agents > 1:
actions = [model.predict(
np.stack([env_state[i][j] for i in range(env_state.shape[0])]),
deterministic=determin)[0] for j, model in enumerate(models)]
actions = [model.predict(env_state[model_idx], deterministic=True)[0]
for model_idx, model in enumerate(models)]
else:
actions = models[0].predict(env_state, deterministic=determin)[0]
env_state, step_r, done_bool, info_obj = env.step(actions)

12
studies/e_1.py
View File

@@ -121,8 +121,7 @@ def load_model_run_baseline(seed_path, env_to_run):
if done_bool:
break
print(f'Factory run {episode} done, reward is:\n {rew}')
monitored_env_factory.save_run(filepath=seed_path / f'{ood_monitor_file}.pick')
monitored_env_factory.save_run(filepath=seed_path / f'{baseline_monitor_file}.pick')
def load_model_run_study(seed_path, env_to_run, additional_kwargs_dict):
@@ -147,9 +146,8 @@ def load_model_run_study(seed_path, env_to_run, additional_kwargs_dict):
rew, done_bool = 0, False
while not done_bool:
try:
actions = [model.predict(
np.stack([env_state[i][j] for i in range(env_state.shape[0])]),
deterministic=True)[0] for j, model in enumerate(models)]
actions = [model.predict(env_state[model_idx], deterministic=True)[0]
for model_idx, model in enumerate(models)]
except ValueError as e:
print(e)
print('Env_Kwargs are:\n')
@@ -205,7 +203,7 @@ if __name__ == '__main__':
frames_to_stack = 3
# Define a global studi save path
start_time = 'obs_stack_3_gae_0.25_n_steps_16' # int(time.time())
start_time = 'adam_no_weight_decay' # int(time.time())
study_root_path = Path(__file__).parent.parent / 'study_out' / f'{Path(__file__).stem}_{start_time}'
# Define Global Env Parameters
@@ -228,7 +226,7 @@ if __name__ == '__main__':
spawn_frequency=30, n_drop_off_locations=2,
max_agent_inventory_capacity=15)
factory_kwargs = dict(n_agents=1, max_steps=400, parse_doors=True,
level_name='rooms', record_episodes=False, doors_have_area=True,
level_name='rooms', doors_have_area=True,
verbose=False,
mv_prop=move_props,
obs_prop=obs_props,