def __init__(self, model, args, device_id=None, verbose=False):
self.model = model
self.args = args
self.device_id = device_id
self.verbose = verbose
self.opt = optim.SGD(self.model.parameters(),
lr=self.args.lr,
momentum=self.args.momentum,
nesterov=(self.args.nesterov
and self.args.momentum > 0))
self.crit = Criterion(self.model.word_dict, device_id=device_id)
self.sel_crit = Criterion(self.model.item_dict,
device_id=device_id,
bad_toks=['<disconnect>', '<disagree>'])
if self.args.visual:
self.model_plot = vis.ModulePlot(self.model,
plot_weight=False,
plot_grad=True)
self.loss_plot = vis.Plot(['train', 'valid', 'valid_select'],
'loss',
'loss',
'epoch',
running_n=1)
self.ppl_plot = vis.Plot(['train', 'valid', 'valid_select'],
'perplexity',
'ppl',
'epoch',
running_n=1)
def __init__(self, model, args, verbose=False):
self.model = model
self.args = args
self.verbose = verbose
self.opt = self.make_opt(self.args.lr)
self.crit = Criterion(self.model.word_dict)
self.sel_crit = Criterion(
self.model.item_dict, bad_toks=['<disconnect>', '<disagree>'])
if self.args.visual:
self.model_plot = vis.ModulePlot(self.model, plot_weight=True, plot_grad=False)
self.loss_plot = vis.Plot(['train', 'valid', 'valid_select'],
'loss', 'loss', 'epoch', running_n=1, write_to_file=False)
self.ppl_plot = vis.Plot(['train', 'valid', 'valid_select'],
'perplexity', 'ppl', 'epoch', running_n=1, write_to_file=False)
def __init__(self, model, args, name='Alice'):
super(RlAgent, self).__init__(model, args, name=name)
self.opt = optim.SGD(
self.model.parameters(),
lr=self.args.rl_lr,
momentum=self.args.momentum,
nesterov=(self.args.nesterov and self.args.momentum > 0))
self.all_rewards = []
if self.args.visual:
self.model_plot = vis.ModulePlot(self.model, plot_weight=False, plot_grad=True)
self.reward_plot = vis.Plot(['reward',], 'reward', 'reward')
self.loss_plot = vis.Plot(['loss',], 'loss', 'loss')
self.t = 0
# Explicitly activate training_mode to avoid runtime error with pytorch > 0.4.0
self.model.train()
def __init__(self, model, args, name='Alice'):
super(RlAgent, self).__init__(model, args, name=name)
self.opt = optim.SGD(self.model.parameters(),
lr=self.args.rl_lr,
momentum=self.args.momentum,
nesterov=(self.args.nesterov
and self.args.momentum > 0))
self.all_rewards = []
if self.args.visual:
self.model_plot = vis.ModulePlot(self.model,
plot_weight=False,
plot_grad=True)
self.reward_plot = vis.Plot([
'reward',
], 'reward', 'reward')
self.loss_plot = vis.Plot([
'loss',
], 'loss', 'loss')
self.t = 0
