value="4.0"> *="" 9=""> R_all = { -1.0, -0.0, 0.0, { -1.0, -0.0, 0.0, 0.0, -1.0, 0.0, 0.0, 0.0, 1.0, 0.9999999999920636, -0.0, 0.0, -0.0, -0.0007013484622411433, 0.9999997540472005, 0.0, -0.999999754055137, -0.0007013484622467095 0007013484622467095, 0.9999993163649181, 0.0, -0.001169289425224364, -0.0, 0.9999994508798468, 0.0010479601216713834, 0.001169294705420077, -0.00104795423012248, 0.9999987672701519, 0.9999999072555382

without the prior written permission of the publisher. Art. No 0 ISBN 000-00-0000-00-0 Edition 0.0 Cover design by Dezeming Family Published by Dezeming Printed in China ## 目录 0.1 本书前言 5 1 value=1) ) transform 是对数据的转换，ToTensor() 函数将 PIL 图像或者 NumPy 的 ndarray 转换为 FloatTensor 类型的，并且把图像的每个像素值压缩到 [0.0, 1.0] 之间。 是标签的转换，分类中我们需要将标签表示为向量的形式，例如一共有三类，则表示为： $$ \left[1\quad0\quad0\right] $$ $$ \left[0\quad1\quad0\right] shape) print(m.bias.shape) # 权重分布符合正态分布 m.weight.data.normal_(0.0, 1) # 偏置归0 m.bias.data.zero() ### Chapter 3. 更完善的神经网络 注意 bias 是权重，因为当前层的 bias 会连接下一层的每个神经元，所以

using the bitstring func�on: julia> 0.0 == -0.0 true julia> bitstring(0.0) "0000000000000000000000000000000000000000000000000000000000000000" julia> bitstring(-0.0) "1000000000000000000000000000000000 standard, these floa�ng-point values are the results of certain arithme�c opera�ons: julia> 1/Inf 0.0 julia> 1/0 Inf julia> -5/0 -Inf julia> 0.000001/0 Inf julia> 0/0 NaN julia> 500 + Inf Inf julia> 500 220446049250313e-16 julia> eps(1000.) 1.1368683772161603e-13 julia> eps(1e-27) 1.793662034335766e-43 julia> eps(0.0) 5.0e-324 The distance between two adjacent representable floa�ng-point numbers is not constant, but

binary representations, as can be seen using the bitstring function: julia> 0.0 == -0.0 true julia> bitstring(0.0) 000000000000000000000000000000000000000000000000000000000000000000000000000000 standard, these floating-point values are the results of certain arithmetic operations: julia> 1/Inf 0.0 julia> 1/0 Inf julia> -5/0 -Inf julia> 0.000001/0 Inf julia> 0/0 NaN julia> 500 julia> eps(1000.) 1.1368683772161603e-13 julia> eps(1e-27) 1.793662034335766e-43 julia> eps(0.0) 5.0e-324 The distance between two adjacent representable floating-point numbers is not constant,

0xb2) ## 浮点数中的零 浮点数有两个零，正零和负零。它们相互相等但有着不同的二进制表示，可以使用 bitstring 函数来查看： julia> 0.0 == -0.0 true julia> bitstring(0.0) "0000000000000000000000000000000000000000000000000000000000000000000000000 对于这些非有限浮点值相互之间以及关于其它浮点值的顺序的更多讨论，请参见数值比较。根据IEEE 754标准，这些浮点值是某些算术运算的结果： #### 5.2. 浮点数 julia> 1/Inf 0.0 julia> 1/0 Inf julia> -5/0 -Inf julia> 0.000001/0 Inf julia> 0/0 NaN julia> 500 julia> eps(1000.) 1.1368683772161603e-13 julia> eps(1e-27) 1.793662034335766e-43 julia> eps(0.0) 5.0e-324 两个相邻可表示的浮点数之间的距离并不是常数，数值越小，间距越小，数值越大，间距越大。换句话说，可表示的浮点数在实数轴上的零点附近最稠密，并沿着远离零点的方向以指数型的速度变得越来越稀疏。根据定义，

binary representations, as can be seen using the bitstring function: julia> 0.0 == -0.0 true julia> bitstring(0.0) 000000000000000000000000000000000000000000000000000000000000000000000000000000 standard, these floating-point values are the results of certain arithmetic operations: julia > 1/Inf 0.0 julia > 1/0 Inf julia > -5/0 -Inf julia > 0.000001/0 Inf julia > 0/0 NaN julia > julia> eps(1000.) 1.1368683772161603e-13 julia> eps(1e-27) 1.793662034335766e-43 julia> eps(0.0) 5.0e-324 The distance between two adjacent representable floating-point numbers is not constant,

binary representations, as can be seen using the bitstring function: julia> 0.0 == -0.0 true julia> bitstring(0.0) 000000000000000000000000000000000000000000000000000000000000000000000000000000 standard, these floating-point values are the results of certain arithmetic operations: julia > 1/Inf 0.0 julia > 1/0 Inf julia > -5/0 -Inf julia > 0.000001/0 Inf julia > 0/0 NaN julia > julia> eps(1000.) 1.1368683772161603e-13 julia> eps(1e-27) 1.793662034335766e-43 julia> eps(0.0) 5.0e-324 The distance between two adjacent representable floating-point numbers is not constant,

binary representations, as can be seen using the bitstring function: julia> 0.0 == -0.0 true julia> bitstring(0.0) "0000000000000000000000000000000000000000000000000000000000000000000000000 standard, these floating-point values are the results of certain arithmetic operations: julia> 1/Inf 0.0 julia> 1/0 Inf julia> -5/0 -Inf julia> 0.000001/0 Inf julia > 0 / 0 NaN julia > 500 julia> eps(1000.) 1.1368683772161603e-13 julia> eps(1e-27) 1.793662034335766e-43 julia> eps(0.0) 5.0e-324 The distance between two adjacent representable floating-point numbers is not constant,