From 5208c41b07f1190fff362f1c29dfb606ba6af2ef Mon Sep 17 00:00:00 2001
From: nbwzlyd <420907013@qq.com>
Date: Sun, 11 Sep 2022 09:58:19 +0000
Subject: [PATCH] =?UTF-8?q?=E5=88=A0=E9=99=A4=20'script=5Fray=5Fcpu.py'?=
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---
 script_ray_cpu.py | 76 -----------------------------------------------
 1 file changed, 76 deletions(-)
 delete mode 100644 script_ray_cpu.py

diff --git a/script_ray_cpu.py b/script_ray_cpu.py
deleted file mode 100644
index 32554db..0000000
--- a/script_ray_cpu.py
+++ /dev/null
@@ -1,76 +0,0 @@
-import os
-
-import gym
-from agit import Agent#之前的是eternatus
-from gym.spaces import Discrete, Box
-from ray import tune
-
-
-class SimpleCorridor(gym.Env):
-    def __init__(self, config):
-        self.end_pos = config['corridor_length']
-        self.cur_pos = 0
-        self.action_space = Discrete(2)
-        self.observation_space = Box(0.0, self.end_pos, shape=(1,))
-
-    def reset(self):
-        self.cur_pos = 0
-        return [self.cur_pos]
-
-    def step(self, action):
-        if action == 0 and self.cur_pos > 0:
-            self.cur_pos -= 1
-        elif action == 1:
-            self.cur_pos += 1
-        done = self.cur_pos >= self.end_pos
-        return [self.cur_pos], 1 if done else 0, done, {}
-
-
-def main():
-    from datetime import datetime
-    start_time = datetime.utcnow()
-
-    print('Python start time: {} UTC'.format(start_time))
-
-    import tensorflow as tf
-    print('TensorFlow CUDA is available: {}'.format(tf.config.list_physical_devices('GPU')))
-
-    import torch
-    print('pyTorch CUDA is available: {}'.format(torch.cuda.is_available()))
-
-    if 'CLOUD_PROVIDER' in os.environ and os.environ['CLOUD_PROVIDER'] == 'Agit':
-        provider = 'Agit'
-
-        log_dir = '/root/.agit'
-        results_dir = '/root/.agit'
-    else:
-        provider = 'local'
-
-        log_dir = '../temp'
-        results_dir = '../temp'
-
-    # Initialize Ray Cluster
-    #ray_init()
-
-    tune.run(
-        'PPO',
-        queue_trials=True,  # Don't use this parameter unless you know what you do.
-        stop={'training_iteration': 10},
-        config={
-            'env': SimpleCorridor,
-            'env_config': {'corridor_length': 5}
-        }
-    )
-
-    with open(os.path.join(results_dir, 'model.pkl'), 'wb') as file:
-        file.write(b'model data')
-
-    complete_time = datetime.utcnow()
-
-    print('Python complete time: {} UTC'.format(complete_time))
-
-    print('Python resource time: {} UTC'.format(complete_time - start_time))
-
-
-if __name__ == '__main__':
-    main()
\ No newline at end of file