optim.py cs231n

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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…

cnn.py cs231n

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…

fc_net.py cs231n

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…

layers.py cs231n

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…

笔记：CS231n+assignment2（作业二）（一）

第二个作业难度很高,但做(抄)完之后收获还是很大的.... 一.Fully-Connected Neural Nets 首先是对之前的神经网络的程序进行重构,目的是可以构建任意大小的全连接的neural network,这里用模块化的思想构建整个代码,具体思路如下: #前向传播 def layer_forward(x, w): """ Receive inputs x and weights w """ # 做前向计算 z = # 需要存储的中间…

深度学习原理与框架-神经网络-cifar10分类(代码) 1.np.concatenate(进行数据串接) 2.np.hstack(将数据横着排列) 3.hasattr(判断.py文件的函数是否存在) 4.reshape(维度重构) 5.tanspose(维度位置变化) 6.pickle.load(f文件读入) 7.np.argmax(获得最大值索引) 8.np.maximum(阈值比较)

横1. np.concatenate(list, axis=0) 将数据进行串接,这里主要是可以将列表进行x轴获得y轴的串接参数说明:list表示需要串接的列表,axis=0,表示从上到下进行串接 2.np.hstack(list) 将列表进行横向排列参数说明:list.append([1, 2]), list.append([3, 4]) np.hstack(list) , list等于[1, 2, 3, 4] 3. hasattr(optim, 'sgd') 判断optim.py中是…

optim.py-使用tensorflow实现一般优化算法

optim.py Project URL:https://github.com/Codsir/optim.git Based on: tensorflow, numpy, copy, inspect Why Tensorflow? Tensorflow supports symbol computation well like Automatic derivation and the program could be excuted with GPU, which will save our t…