From 60b730d019313dade48abc04a784bff3fb3e37ef Mon Sep 17 00:00:00 2001
From: u214892 <u214892@sbb.ch>
Date: Tue, 9 Jul 2019 11:50:19 +0200
Subject: [PATCH] #42 run baselines in ci
---
requirements_torch_training.txt | 2 ++
torch_training/multi_agent_training.py | 2 +-
torch_training/training_navigation.py | 21 ++++++++-------------
3 files changed, 11 insertions(+), 14 deletions(-)
diff --git a/requirements_torch_training.txt b/requirements_torch_training.txt
index 03f6383..d8c4a46 100644
--- a/requirements_torch_training.txt
+++ b/requirements_torch_training.txt
@@ -1,2 +1,4 @@
git+https://gitlab.aicrowd.com/flatland/flatland.git@master
+importlib-metadata>=0.17
+importlib_resources>=1.0.2
torch>=1.1.0
\ No newline at end of file
diff --git a/torch_training/multi_agent_training.py b/torch_training/multi_agent_training.py
index ba9f144..0037f95 100644
--- a/torch_training/multi_agent_training.py
+++ b/torch_training/multi_agent_training.py
@@ -1,11 +1,11 @@
from collections import deque
-from sys import path
import matplotlib.pyplot as plt
import numpy as np
import random
import torch
from dueling_double_dqn import Agent
+from importlib_resources import path
import torch_training.Nets
from flatland.envs.generators import complex_rail_generator
diff --git a/torch_training/training_navigation.py b/torch_training/training_navigation.py
index 1857b67..c52a891 100644
--- a/torch_training/training_navigation.py
+++ b/torch_training/training_navigation.py
@@ -1,12 +1,11 @@
-from sys import path
-
-import random
from collections import deque
import matplotlib.pyplot as plt
import numpy as np
+import random
import torch
from dueling_double_dqn import Agent
+from importlib_resources import path
import torch_training.Nets
from flatland.envs.generators import complex_rail_generator
@@ -14,7 +13,6 @@ from flatland.envs.observations import TreeObsForRailEnv
from flatland.envs.predictions import ShortestPathPredictorForRailEnv
from flatland.envs.rail_env import RailEnv
from flatland.utils.rendertools import RenderTool
-
from utils.observation_utils import norm_obs_clip, split_tree
random.seed(1)
@@ -70,7 +68,7 @@ file_load = False
"""
observation_helper = TreeObsForRailEnv(max_depth=3, predictor=ShortestPathPredictorForRailEnv())
-env_renderer = RenderTool(env, gl="PILSVG",)
+env_renderer = RenderTool(env, gl="PILSVG", )
handle = env.get_agent_handles()
features_per_node = 9
state_size = features_per_node * 85 * 2
@@ -94,11 +92,9 @@ agent = Agent(state_size, action_size, "FC", 0)
with path(torch_training.Nets, "avoid_checkpoint30000.pth") as file_in:
agent.qnetwork_local.load_state_dict(torch.load(file_in))
-
demo = True
record_images = False
-
for trials in range(1, n_trials + 1):
if trials % 50 == 0 and not demo:
@@ -136,7 +132,7 @@ for trials in range(1, n_trials + 1):
agent_data = np.clip(agent_data, -1, 1)
obs[a] = np.concatenate((np.concatenate((data, distance)), agent_data))
agent_data = env.agents[a]
- speed = 1 #np.random.randint(1,5)
+ speed = 1 # np.random.randint(1,5)
agent_data.speed_data['speed'] = 1. / speed
for i in range(2):
@@ -145,7 +141,6 @@ for trials in range(1, n_trials + 1):
for a in range(env.get_num_agents()):
agent_obs[a] = np.concatenate((time_obs[0][a], time_obs[1][a]))
-
score = 0
env_done = 0
# Run episode
@@ -206,10 +201,10 @@ for trials in range(1, n_trials + 1):
print(
'\rTraining {} Agents on ({},{}).\t Episode {}\t Average Score: {:.3f}\tDones: {:.2f}%\tEpsilon: {:.2f} \t Action Probabilities: \t {}'.format(
env.get_num_agents(), x_dim, y_dim,
- trials,
- np.mean(scores_window),
- 100 * np.mean(done_window),
- eps, action_prob / np.sum(action_prob)), end=" ")
+ trials,
+ np.mean(scores_window),
+ 100 * np.mean(done_window),
+ eps, action_prob / np.sum(action_prob)), end=" ")
if trials % 100 == 0:
print(
--
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