def after_eval_step(self, *args, **kwargs):
self.report_dict = filter_dict(
flatten_dict(
self._trainer._meter_interface.tracking_status(
group_name=self._val_groupname)))
self.tqdm_indicator.update()
self.tqdm_indicator.set_postfix(self.report_dict)
def _eval_report_dict(self):
return filter_dict(
{
"val_loss": self.METERINTERFACE["val_loss"].summary()["mean"],
"val_acc": self.METERINTERFACE["val_acc"].summary()["acc"],
}
)
def _training_report_dict(self):
return filter_dict(
{
"tra_loss": self.METERINTERFACE["train_loss"].summary()["mean"],
"tra_acc": self.METERINTERFACE["train_acc"].summary()["acc"],
}
)
def _training_report_dict(self):
report_dict = super()._training_report_dict
report_dict.update({
"marginal":
self.METERINTERFACE["marginal"].summary()["mean"],
"centropy":
self.METERINTERFACE["centropy"].summary()["mean"],
})
return filter_dict(report_dict)
def _training_report_dict(self):
report_dict = super()._training_report_dict
report_dict.update(
{
"unl_acc": self.METERINTERFACE["unl_acc"].summary()["acc"],
"uda_reg": self.METERINTERFACE["uda_reg"].summary()["mean"],
"marginal": self.METERINTERFACE["marginal"].summary()["mean"],
}
)
return filter_dict(report_dict)