def createSummaries(self, labelsOH, predsOH, loss, learning_rate):
labels = layers.onehot_to_class(labelsOH)
preds = layers.onehot_to_class(predsOH)
acc = layers.accuracy(labels, preds)
prec = layers.precision(labels, preds)
rec = layers.recall(labels, preds)
tf.summary.scalar('learning_rate', learning_rate)
tf.summary.scalar('loss', loss)
tf.summary.scalar('accuracy', acc[1])
tf.summary.scalar('precision', prec[1])
tf.summary.scalar('recall', rec[1])
return acc, prec, rec
def createSummaries(self, labelsOH, predsOH, loss, learning_rate):
labels = layers.onehot_to_class(labelsOH)
preds = layers.onehot_to_class(predsOH)
acc = layers.accuracy(labels, preds)
prec = layers.precision(labels, preds)
rec = layers.recall(labels, preds)
tf.summary.scalar('learning_rate', learning_rate)
tf.summary.scalar('loss', loss)
tf.summary.scalar('accuracy', acc[1])
tf.summary.scalar('precision', prec[1])
tf.summary.scalar('recall', rec[1])
return acc, prec, rec