加载 CIFAR 100 后，我尝试训练我的神经网络。但我不知道为什么会出现如下所示的越界错误
Optimizing the network with batch size 25
Epoch: 0 of 30 Average loss: -
/mnt_home/klee/LBSBGenGapSharpnessResearch/vgg.py:43: UserWarning: Implicit dimension choice for log_softmax has been deprecated. Change the call to include dim=X as an argument.
return F.log_softmax(x)
Traceback (most recent call last):
File "plot_parametric_pytorch_cifar100.py", line 130, in <module>
loss_fn = F.nll_loss(ops, tgts)
File "/home/klee/anaconda3/envs/sharpenv/lib/python3.7/site-packages/torch/nn/functional.py", line 2115, in nll_loss
ret = torch._C._nn.nll_loss(input, target, weight, _Reduction.get_enum(reduction), ignore_index)
IndexError: Target 42 is out of bounds.
这是我正在运行的脚本：
cudnn.benchmark = True
(X_train, y_train), …我正在尝试将以下 Keras 模型代码转换为 pytorch，但在处理 padding='same' 时遇到问题。
model = Sequential()
model.add(Conv2D(64, (3, 3), input_shape=img_size))
model.add(BatchNormalization(axis=1))
model.add(Activation('relu'))
model.add(Dropout(0.3))
model.add(Conv2D(64, (3, 3), padding='same'))
model.add(BatchNormalization(axis=1))
model.add(Activation('relu'))
model.add(MaxPooling2D(pool_size=(2,2), strides=(2,2), padding='same'))
这产生以下摘要：
Layer (type) Output Shape Param #
=================================================================
conv2d_1 (Conv2D) (None, 30, 30, 64) 1792
_________________________________________________________________
batch_normalization_1 (Batch (None, 30, 30, 64) 120
_________________________________________________________________
activation_1 (Activation) (None, 30, 30, 64) 0
_________________________________________________________________
dropout_1 (Dropout) (None, 30, 30, 64) 0
_________________________________________________________________
conv2d_2 (Conv2D) (None, 30, 30, 64) 36928
_________________________________________________________________
batch_normalization_2 (Batch (None, 30, 30, 64) 120 …