piiswrong closed pull request #9046: Fix example example/reinforcement-learning/a3c URL: https://github.com/apache/incubator-mxnet/pull/9046
This is a PR merged from a forked repository. As GitHub hides the original diff on merge, it is displayed below for the sake of provenance: As this is a foreign pull request (from a fork), the diff is supplied below (as it won't show otherwise due to GitHub magic): diff --git a/CONTRIBUTORS.md b/CONTRIBUTORS.md index a1a5a5b50e..9c68dc2333 100644 --- a/CONTRIBUTORS.md +++ b/CONTRIBUTORS.md @@ -153,3 +153,4 @@ List of Contributors * [Marco de Abreu](https://github.com/marcoabreu) - Marco is the creator of the current MXNet CI. * [Julian Salazar](https://github.com/JulianSlzr) +* [Meghna Baijal](https://github.com/mbaijal) diff --git a/example/reinforcement-learning/a3c/README.md b/example/reinforcement-learning/a3c/README.md index 63faf92d7e..5eaba66a5b 100644 --- a/example/reinforcement-learning/a3c/README.md +++ b/example/reinforcement-learning/a3c/README.md @@ -7,8 +7,14 @@ The algorithm should be mostly correct. However I cannot reproduce the result in Note this is a generalization of the original algorithm since we use `batch_size` threads for each worker instead of the original 1 thread. +## Prerequisites + - Install OpenAI Gym: `pip install gym` + - Install the Atari Env: `pip install gym[atari]` + - You may need to install flask: `pip install flask` + - You may have to install cv2: `pip install opencv-python` + ## Usage run `python a3c.py --batch-size=32 --gpus=0` to run training on gpu 0 with batch-size=32. run `python launcher.py --gpus=0,1 -n 2 python a3c.py` to launch training on 2 gpus (0 and 1), each gpu has two workers. - +Note: You might have to update the path to dmlc-core in launcher.py. diff --git a/example/reinforcement-learning/a3c/a3c.py b/example/reinforcement-learning/a3c/a3c.py index 4d89a24852..f74ce77b65 100644 --- a/example/reinforcement-learning/a3c/a3c.py +++ b/example/reinforcement-learning/a3c/a3c.py @@ -26,6 +26,11 @@ import gym from datetime import datetime import time +import sys +try: + from importlib import reload +except ImportError: + pass parser = argparse.ArgumentParser(description='Traing A3C with OpenAI Gym') parser.add_argument('--test', action='store_true', help='run testing', default=False) @@ -139,7 +144,7 @@ def train(): module.save_params('%s-%04d.params'%(save_model_prefix, epoch)) - for _ in range(epoch_size/args.t_max): + for _ in range(int(epoch_size/args.t_max)): tic = time.time() # clear gradients for exe in module._exec_group.grad_arrays: diff --git a/example/reinforcement-learning/a3c/rl_data.py b/example/reinforcement-learning/a3c/rl_data.py index ad78975753..70f2853978 100644 --- a/example/reinforcement-learning/a3c/rl_data.py +++ b/example/reinforcement-learning/a3c/rl_data.py @@ -21,13 +21,18 @@ import gym import cv2 import math -import Queue from threading import Thread import time import multiprocessing import multiprocessing.pool from flask import Flask, render_template, Response import signal +import sys +is_py3 = sys.version[0] == '3' +if is_py3: + import queue as queue +else: + import Queue as queue def make_web(queue): app = Flask(__name__) @@ -62,7 +67,7 @@ def visual(X, show=True): buf = np.zeros((h*n, w*n, X.shape[3]), dtype=np.uint8) for i in range(N): x = i%n - y = i/n + y = i//n buf[h*y:h*(y+1), w*x:w*(x+1), :] = X[i] if show: cv2.imshow('a', buf) @@ -88,7 +93,7 @@ def __init__(self, batch_size, input_length, nthreads=6, web_viz=False): self.web_viz = web_viz if web_viz: - self.queue = Queue.Queue() + self.queue = queue.Queue() self.thread = Thread(target=make_web, args=(self.queue,)) self.thread.daemon = True self.thread.start() @@ -117,7 +122,7 @@ def act(self, action): reward = np.asarray([i[1] for i in new], dtype=np.float32) done = np.asarray([i[2] for i in new], dtype=np.float32) - channels = self.state_.shape[1]/self.input_length + channels = self.state_.shape[1]//self.input_length state = np.zeros_like(self.state_) state[:,:-channels,:,:] = self.state_[:,channels:,:,:] for i, (ob, env) in enumerate(zip(new, self.env)): @@ -151,7 +156,7 @@ def make_env(self): return gym.make(self.game) def visual(self): - data = self.state_[:4, -self.state_.shape[1]/self.input_length:, :, :] + data = self.state_[:4, -self.state_.shape[1]//self.input_length:, :, :] return visual(np.asarray(data, dtype=np.uint8), False) if __name__ == '__main__': ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
