def on_epoch_end(self, *args, **kwargs):
if self.epoch_every and ((self.epoch_id % self.epoch_every) == 0):
self.model.eval()
val_loss, val_acc = score_model_multi_output(
self.model, self.loss_function, self.validation_datagen)
self.model.train()
logger.info('epoch {0} validation loss: {1:.5f}'.format(
self.epoch_id, val_loss))
logger.info('epoch {0} validation accuracy: {1:.5f}'.format(
self.epoch_id, val_acc))
self.epoch_id += 1
self.batch_id = 0
def on_epoch_end(self, *args, **kwargs):
epoch_avg_loss = self.epoch_loss_averager.value
epoch_avg_acc = self.epoch_acc_averager.value
self.epoch_loss_averager.reset()
self.epoch_acc_averager.reset()
self.model.eval()
val_loss, val_acc = score_model_multi_output(self.model,
self.loss_function,
self.validation_datagen)
self.model.train()
logs = {
'epoch_id': self.epoch_id,
'batch_id': self.batch_id,
'epoch_loss': epoch_avg_loss,
'epoch_acc': epoch_avg_acc,
'epoch_val_loss': val_loss,
'epoch_val_acc': val_acc
}
self._send_numeric_channels(logs)
for i, (image, y_pred, y_true) in enumerate(
predict_on_batch_multi_output(self.model,
self.validation_datagen)):
image_with_keypoints = overlay_keypoints(image, y_pred, y_true,
self.bins_nr)
pill_image = Image.fromarray(
(image_with_keypoints * 255.).astype(np.uint8))
self.ctx.channel_send(
"plotted key points",
neptune.Image(name='epoch{}_batch{}_idx{}'.format(
self.epoch_id, self.batch_id, i),
description="true and prediction key points",
data=pill_image))
if i == self.img_nr:
break
self.epoch_id += 1
def on_epoch_end(self, *args, **kwargs):
epoch_avg_loss = self.epoch_loss_averager.value
epoch_avg_acc = self.epoch_acc_averager.value
self.epoch_loss_averager.reset()
self.epoch_acc_averager.reset()
self.model.eval()
val_loss, val_acc = score_model_multi_output(self.model,
self.loss_function,
self.validation_datagen)
self.model.train()
logs = {
'epoch_id': self.epoch_id,
'batch_id': self.batch_id,
'epoch_loss': epoch_avg_loss,
'epoch_acc': epoch_avg_acc,
'epoch_val_loss': val_loss,
'epoch_val_acc': val_acc
}
self._send_numeric_channels(logs)
self.epoch_id += 1