def optimize(model,
data,
itermax=50,
k=1,
act_fn=round): # round rounds .5 to zero
weights = [model.W]
accuracies = [model.test_acc(data, k=k, act_fn=act_fn)]
for _ in range(itermax):
model.W = Optimizer.gradient_descent(model, data)
weights.append(model.W)
accuracies.append(model.test_acc(data, k=k, act_fn=act_fn))
return weights, accuracies
def optimize(model,
data,
itermax=50,
k=1,
act_fn=round): # round rounds .5 to zero
weights = [model.W]
acc, res = model.test_acc(data, k=k, act_fn=act_fn)
accuracies = [acc]
ress = [res]
for _ in range(itermax):
# import pdb
# pdb.set_trace()
model.W = Optimizer.gradient_descent(model, data)
weights.append(model.W)
acc, res = model.test_acc(data, k=k, act_fn=act_fn)
accuracies.append(acc)
ress.append(ress)
return weights, accuracies, ress
