blob: e962cf99be1fff01e6c58d9c993472078e72c483 [file] [log] [blame]
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
import mxnet as mx
class Config(object):
def __init__(self, args):
# Default training settings
self.ctx = mx.gpu(0) if args.gpu else mx.cpu()
self.init_func = mx.init.Xavier(rnd_type='uniform', factor_type="in",
magnitude=1)
self.learning_rate = 1e-3
self.update_rule = "adam"
self.grad_clip = True
self.clip_magnitude = 40
# Default model settings
self.hidden_size = 200
self.gamma = 0.99
self.lambda_ = 1.0
self.vf_wt = 0.5 # Weight of value function term in the loss
self.entropy_wt = 0.01 # Weight of entropy term in the loss
self.num_envs = 16
self.t_max = 50
# Override defaults with values from `args`.
for arg in self.__dict__:
if arg in args.__dict__:
self.__setattr__(arg, args.__dict__[arg])