Efficiency-of-Neural-Archit.../stopping_crit.py

22 lines
893 B
Python

def earlyStopping(early_stopping: list, train_acc: float, sensitivity: float=1e-9):
early_stopping.append(train_acc)
if epoch % 4 == 0 and epoch > 0:
print("Value 1: {} >= {}, Value 2: {} >= {}, \
Value 2: {} >= {}".format(early_stopping[0], \
train_acc-sensitivity,early_stopping[1], \
train_acc-sensitivity, early_stopping[2], train_acc-sensitivity))
if abs(early_stopping[0]) >= train_acc-sensitivity and \
abs(early_stopping[1]) >= train_acc-sensitivity and \
abs(early_stopping[2]) >= train_acc-sensitivity:
return None
early_stopping = []
def energyBound(threshold: float=100000.0):
if gpu_sample_draw.total_watt_consumed() > threshold:
return None
def accuracyBound(train_acc: float, threshold: float=0.99):
if train_acc >= threshold:
return None