# Copyright (c) Facebook, Inc. and its affiliates.
# Copyright (c) Facebook, Inc. and its affiliates. # All rights reserved. # # This source code is licensed under the license found in the # LICENSE file in the root directory of this source tree. # import argparse import os import sys import pprint from set_path import append_sys_path append_sys_path() import torch import tube from pytube import DataChannelManager import minirts import numpy as np import random import pickle from collections import defaultdict from rnn_coach import ConvRnnCoach from onehot_coach import ConvOneHotCoach from rnn_generator import RnnGenerator from itertools import groupby from executor_wrapper import ExecutorWrapper from executor import Executor from common_utils import to_device, ResultStat, Logger from best_models import best_executors, best_coaches from tqdm import tqdm p1dict = defaultdict(list)
result1 = ResultStat('reward', None)
result2 = ResultStat('reward', None)
i = 0
while not context.terminated():
i += 1
if i % 1000 == 0:
print('%d, progress agent1: win %d, loss %d' %
(i, result1.win, result1.loss))
data = dc.get_input(max_timeout_s=1)
if len(data) == 0:
continue
for key in data:
# print(key)
batch = to_device(data[key], device)
if key == 'act1':
result1.feed(batch)
with torch.no_grad():
reply = model1.forward(batch)
elif key == 'act2':
result2.feed(batch)
with torch.no_grad():
reply = model2.forward(batch)
else:
assert False
dc.set_reply(key, reply)
print(result1.log(0))
print(result2.log(0))
dc.terminate()
# Copyright (c) Facebook, Inc. and its affiliates.