def __init__(self):
super(Net, self).__init__()
# 1 input image channel, 6 output channels, 3x3 square convolution
# kernel
self.conv1 = nn.Conv2d(1, 6, 3)
self.conv2 = nn.Conv2d(6, 16, 3)
# an affine operation: y = Wx + b
self.fc1 = nn.Linear(16 * 6 * 6, 120) # 6*6 from image dimension
self.fc2 = nn.Linear(120, 84)
self.fc3 = nn.Linear(84, 10)
从上面的图片和PyTorch神经网络教程的代码中,我可以理解卷积的维度。如何确定“ nn.Linear”的输出尺寸?另外,为什么我们需要三个完全连接的层?
任何帮助将不胜感激。 TIA