PGPortfolio: Policy Gradient Portfolio, the source code of "A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem"(https://arxiv.org/pdf/1706.10059.pdf).
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Tradertrainer's _evaluate method does not support set_name "validation" #96
_evaluate method in Tradertrainer is called with args {set_name : "validation"} in rollingtrainer line 37 is not supported by the method _evaluate.
_evaluate method only support set_name "test" and "training"
in tradertrainer.py line 74
``
def _evaluate(self, set_name, *tensors):
if set_name == "test":
feed = self.test_set
elif set_name == "training":
feed = self.training_set
else:
raise ValueError()
result = self._agent.evaluate_tensors(feed["X"],feed["y"],last_w=feed["last_w"],
setw=feed["setw"], tensors=tensors)
return result
``
in rollingtrainer.py line 32
``
def __rolling_logging(self):
fast_train = self.train_config["fast_train"]
if not fast_train:
tflearn.is_training(False, self._agent.session)
v_pv, v_log_mean = self._evaluate("validation",
self._agent.portfolio_value,
self._agent.log_mean)
t_pv, t_log_mean = self._evaluate("test", self._agent.portfolio_value, self._agent.log_mean)
loss_value = self._evaluate("training", self._agent.loss)
logging.info('training loss is %s\n' % loss_value)
logging.info('the portfolio value on validation asset is %s\nlog_mean is %s\n' %
(v_pv,v_log_mean))
logging.info('the portfolio value on test asset is %s\n mean is %s' % (t_pv,t_log_mean))
_evaluate method in Tradertrainer is called with args {set_name : "validation"} in rollingtrainer line 37 is not supported by the method _evaluate.
_evaluate method only support set_name "test" and "training"
in tradertrainer.py line 74 ``
``
in rollingtrainer.py line 32
``
``