如果有错误,欢迎指出,不胜感激. import numpy as np def affine_forward(x, w, b): 第一个最简单的 affine_forward简单的前向传递,返回 out,cache """ Computes the forward pass for an affine (fully-connected) layer. The input x has shape (N, d_1, ..., d_k) and contains a minibat…
n import numpy as np from cs231n.layers import * from cs231n.fast_layers import * from cs231n.layer_utils import * class ThreeLayerConvNet(object): """ A three-layer convolutional network with the following architecture: conv - relu - 2x2 m…
n如果有错误,欢迎指出,不胜感激 import numpy as np from cs231n.layers import * from cs231n.layer_utils import * class TwoLayerNet(object): """ A two-layer fully-connected neural network with ReLU nonlinearity and softmax loss that uses a modular layer des…
n如果有错误,欢迎指出,不胜感激 import numpy as np """ This file implements various first-order update rules that are commonly used for training neural networks. Each update rule accepts current weights and the gradient of the loss with respect to those w…
