importmathimportrandomclassFAD:def__init__(self,x,name=None,dx=None):self.x=xifname!=None:self.dx=dict()self.dx[name]=1.0else:self.dx=dx# print(self.x,self.dx)def__str__(self):info=''for(key,grad)inself.dx.items
returnloss 从上面的代码可以看到step这个函数使用的是参数空间(param_groups)中的grad,也就是当前参数空间对应的梯度,这也就解释了为什么optimzier使用之前需要zero清零一下,因为如果不清零,那么使用的这个grad就得同上一个mini-BATch有关,这不是我们需要的结果。 再回过头来看,我们知道optimizer更新参数空间需要基于反向...
9 opt.zero_grad() # clear gradients for next train 10 loss.backward() # backpropagation, compute gradients 11 opt.step() # apply gradients 12 l_his.append(loss.data.numpy()) # loss recoder 13 SGD 是最普通的优化器, 也可以说没有加速效果, 而 Momentum 是SGD 的改良版, 它加入了动量...
(num_epochs): for batch in dataloader: # Zero the gradients optimizer.zero_grad() # Forward pass outputs = model(batch) loss = criterion(outputs, targets) # Backward pass loss.backward() # Update weights optimizer.step() # Adjusting learning rate scheduler = optim.lr_scheduler.StepLR(...
shape[0])) xs[0, :] = x v = 0 for i in range(max_iter): v = v + grad(x)**2 x = x - alpha * grad(x) / (eps + np.sqrt(v)) xs[i+1, :] = x return xs ###L=x^2+100y^2_Ir0.01 with Adadelta このコードはうまく収束していますが、今一つ理論が不明です。
[Zero-Dim] fix Tensor.numpy, cntrol whether to hack process to 1D (#51757) zhwesky2010authoredMar 20, 2023 Verified d703545 Commits on Mar 15, 2023 refine amp scaler (#51340) wanghuancoderauthoredMar 15, 2023 Verified 1e232e2 Commits on Mar 10, 2023 Delete duplicate code in op...
colocate_gradients_with_ops: If True, try colocating gradients with the corresponding op. grad_loss: Optional. A Tensor holding the gradient computed for loss.Returns:A list of (gradient, variable) pairs. Variable is always present, but gradient can be None.Raises...
def drumhead_height(n, k, distance, angle, t):kth_zero = special.jn_zeros(n, k)[-1]return np.cos(t) * np.cos(n*angle) * special.jn(n, distance*kth_zero) theta = np.r_[0:2*np.pi:50j]radius = np.r_[0:1:50j]x = np.array([r * np.cos(theta) for r in radius])...