def evaluate(self):
"""Predicts resuts for the test dataset"""
LOG.info('\n Prediction started...')
self._set_training_parameters()
eval_parameters = {
'device': self.device,
'model': self.model,
'dataloaders': (self.trainloader, self.testloader),
'epochs': None,
'optimizer': self.optimizer,
'criterion': self.criterion,
'metrics': self.metric,
'save_ckpt_interval': None,
'ckpt_dir': self.paths.ckpt_dir,
'summary_dir': self.paths.summary_dir,
}
trainer = Trainer(**eval_parameters)
trainer.eval()
def train(self):
"""Compiles and trains the model"""
LOG.info('\n Training started.')
self._set_training_parameters()
train_parameters = {
'device': self.device,
'model': self.model,
'dataloaders': (self.trainloader, self.valloader),
'epochs': self.epochs,
'optimizer': self.optimizer,
'criterion': self.criterion,
'metrics': self.metric,
'save_ckpt_interval': self.save_ckpt_interval,
'ckpt_dir': self.paths.ckpt_dir,
'summary_dir': self.paths.summary_dir,
}
trainer = Trainer(**train_parameters)
trainer.train()
def evaluate(self):
"""Predicts resuts for the test dataset"""
LOG.info('\n Prediction started...')
self._set_training_parameters()
eval_parameters = {
'device': self.device,
'model': self.model,
'dataloaders': (self.trainloader, self.testloader),
'epochs': None,
'optimizer': self.optimizer,
'criterion': self.criterion,
'metrics': self.metric,
'save_ckpt_interval': None,
'ckpt_dir': self.paths.ckpt_dir,
'summary_dir': self.paths.summary_dir,
'img_size': self.config.data.img_size,
'vis_img': VisImage(n_classes=self.n_classes, label_color_map=self.config.data.label_color_map),
'img_outdir': self.paths.img_outdir,
}
trainer = Trainer(**eval_parameters)
trainer.eval(epoch=0, inference=True)
def train(self):
"""Compiles and trains the model"""
LOG.info('\n Training started.')
self._set_training_parameters()
train_parameters = {
'device': self.device,
'model': self.model,
'dataloaders': (self.trainloader, self.valloader),
'epochs': self.epochs,
'optimizer': self.optimizer,
'criterion': self.criterion,
'metrics': self.metric,
'save_ckpt_interval': self.save_ckpt_interval,
'ckpt_dir': self.paths.ckpt_dir,
'summary_dir': self.paths.summary_dir,
'img_size': self.config.data.img_size,
'vis_img': VisImage(n_classes=self.n_classes, label_color_map=self.config.data.label_color_map),
'img_outdir': self.paths.img_outdir,
}
trainer = Trainer(**train_parameters)
trainer.train()