Logsoftmax pytorch dim. softmax(x / temperature, dim=1) 文章浏览阅读2.

Logsoftmax pytorch dim Softmax(dim=None) Applies the Softmax function to an n-dimensional input Tensor rescaling them so that the elements of the n-dimensional output Tensor lie in the range [0,1] and sum to 1. Softmax函数常用的用法是指定参数dim就可以：（1）dim=0：对每一列的所有元素进行softmax运算，并使得每一列所 LogSoftmax (dim = 1) x_log = log_softmax (x) print (NLLLoss (x_log, y)) # tensor(2. distributions」を提供しています。その中でも、ポアソン分布を扱うためのクラスが「torch. 10, CrossEntropyLoss accepts probabilistic targets (that are floating-point numbers), in addition to LogSoftmax (dim: Optional[int] = None) [source] ¶ Applies the log ⁡ ( Softmax ( x ) ) \log(\text{Softmax}(x)) lo g ( Softmax ( x ) ) function to an n-dimensional input Tensor. Softmax(input,dim=None)tf. Softmax函数常用的用法是指定参数dim就可以: (1)dim=0:对每一列的所有元素进行softmax运算,并使得每一列所有元素和为1. Here’s how: def temperature_softmax(x, temperature=1. 10. softmax、torch. Often, instead of calculating softmax probabilities directly, This is the standard way to train a classification model in PyTorch. e. 5w次，点赞76次，收藏169次。最近看了一些Pytorch的代码，代码中使用了Log_Softmax方法，Loss函数使用了NLLLoss，作为深度学习新手，便上网查了一些资料，将相关知识总结记录以下。本文主要参考了这篇文章，在此基础上加入了一些自己的理解。 Hi, What are criteria for choosing “dim=0 or 1” for nn. log_softmax是PyTorch提供的用于计算log(softmax)的函数，通常用于多分类任务和计算交叉熵损失，可以提高数值稳定性并防止数值溢出。比softmax+log更稳定，更高效。在分类任务中，cross_entropy已包含log_softmax，无需额外计算。在强化学习、VAE等任务中，log_softmax也是常用的概率计算方法。 一、函数解释. nn as nnを追加する。 LogSoftmaxには、dim引数があります。この引数は、対数確率値を計算する軸を指定するために使用 You need to initialize the module first and call it later assuming you want to stick to the nn. NLLLoss() # input is of size N x C = 1 X 3 # Input is a perfectly matching on-hot for category 0 input = torch. Softmax(dim=-1) mu, sigma = 0, 0. dim – A dimension along which softmax will be computed. Variation of the example from the docs for NLLLoss: m = nn. distributions. fc(x) return self. [PyTorch] 在PyTorch中，softmax函数有多种实现方式，包括torch. randn(3, 5, Shape: Input: (∗) (*) where * means, any number of additional dimensions Output: (∗) (*), same shape as the input Parameters. The LogSoftmax formulation can be simplified as: 文章浏览阅读3. CrossEntropyLoss三个类的使用。nn. log_softmax on your model output (not multiplying with -1!). LogSoftmax. 4w次，点赞185次，收藏414次。torch. The docs are fixed too. is that Hi, I couldn’t understand from the documentation how can I go about using nn. If you are dealing with a binary classification use case, you could use nn. 文章浏览阅读3. LogSoftmax (dim = 1) >>> input = torch. Efficient softmax approximation. 本文简要介绍python语言中 torch. Usually you would like to normalize the probabilities (log probabilities) in the feature dimension \log (\text {Softmax} (x)) function to an n-dimensional input Tensor. Familiarize yourself with PyTorch concepts and modules. sum() )? It looks to me like you have misunderstood the argument dim of LogSoftmax. At issue is that some new functionality has been added to pytorch’s CrossEntropyLoss as of pytorch version 1. This question is more focused on why LogSoftmax is claimed to be better (both numerically and in terms of speed) than applying Hi, at the last 2 lines how does it work? as in why do we need to exp? i thought we can just model(img) and we will obtain the result? because when we model(img). PyTorch 实战秘籍. 在本地运行 PyTorch 或使用支持的云平台之一快速入门. 2w次，点赞30次，收藏76次。本文详细介绍了PyTorch中的Softmax函数，它用于多分类任务，将输入张量转换为概率分布。Softmax操作沿指定维度将每个元素归一化，使得输出张量的每个维度和为1。在实践中，常使用torch. class Softmax(Module): # モジュールが定数として扱う属性を指定します __constants__ = ['dim'] dim: Optional[int] def __init__(self, dim: Optional[int] = None) -> None: # 親クラスの初期化メソッドを呼び出します Run PyTorch locally or get started quickly with one of the supported cloud platforms. 选一个softmax计算的维度（这个维度上的和为1） 2. LogSoftmax (dim = None) Applies the function to an n-dimensional input Tensor. , i. Softmax(dim=1) >>> input = torch. softmax是PyTorch内置的softmax函数，可以直接应用于张量（tensor）上。其基本语法为torch. 1. sum(-target * nn. tensor and each t_i can be of a different, arbitrary shape. log_softmax是PyTorch提供的用于计算log(softmax)的函数，通常用于多分类任务和计算交叉熵损失，可以提高数值稳定性并防止数值溢出。比softmax+log更稳定，更高效。在分类任务中，cross_entropy已包含log_softmax，无需额外计算。在强化学习、VAE等任务中，log_softmax也是常用的概率计算方法。 Run PyTorch locally or get started quickly with one of the supported cloud platforms. The last layer could be logosftmax or softmax. I couldn’t get the existing APIs working because of the smoothed labels. LogSoftmax (dim: Optional[int] dim – A dimension along which LogSoftmax will be computed. Now, after you pass your input through your two linear layers, the tensor you get and to which you apply LogSoftmax has dimensions 178 x 3. log_softmax(x) # Using NLLLoss with LogSoftmax criterion = nn. 函数解释 1. 文章浏览阅读960次。PyTorch 中的一个层，用于在对数空间中计算 Softmax 激活函数。它通常用于多类别分类任务中，以提高数值稳定性。其输入是 logits，即未归一化的得分，输出是这些得分在对数空间中的 Softmax。_nn. softmax を計算する次元(軸)は. Although the documentation (http Hi, I am trying to train an existing neural network from a published paper, using custom dataset. a Tensor of the same dimension and shape as the input with values in the range [-inf, 0) Return type. As of version 1. In my case where logits and labels have shape [2,3,4], I currently use following function - def softmax_and_cross_entropy(logits, labels): return -(labels * nn. softmax takes two parameters: input and dim. CrossEntropyLoss时，目标变量不需要one-hot编码 机器学习中的分类问题常用到交叉熵作为损失函数，那么Pytorch中如何使用交叉熵损失函数呢？这就涉及到torch. 1w次，点赞12次，收藏40次。目录一、函数解释二、代码示例三、整体代码一、函数解释1. class Softmax(Module): r"""Applies the Softmax function to an n-dimensional input The dim parameter is new and will be in the next release. step()を呼び出す。 Netクラスのforwardメソッドで、return xではなくreturn log_softmax(x)とする。; コードの冒頭に、import torchとimport torch. log_softmax. 用法: class torch. log_softmax。 这些函数虽然都实现了softmax算法，但在使用方式和应用场景上存在一些差异。 首先，torch. BCEWithLogitsLoss (or nn. 2k次，点赞3次，收藏11次。本文详细解析了Pytorch中nn. size() the output is torch. 操作：用于多分类过程中，它将多个神经元的输出，映射到（0,1）区间内，而这些值的累和为1（满足概率的性质），可以看成概率来理解，从而来进行多分类，当使用Softmax函数作为输出节点的激活函数的时候， 文章浏览阅读1. NLLLoss expects log probabilities, so you should just apply F. logsoftmax torch. LogSoftmax(dim=1)) you can either use positive dimension indexing starting with 0 for the first dimension, 1 for the second etc. org/docs/2. log_softmax (input, dim = None, _stacklevel = 3, dtype = None) [source] [source] ¶ Apply a softmax followed by a logarithm. (think like, labels from 0 to C are from one set and labels from C+1 to N are from another set) My network calculates 2 diferent logits for each set with different LogSoftmax class torch. © 2024， PyTorch 贡献者 PyTorch 具有 BSD 风格的许可证，如在 LICENSE 文件中所见。 https://pytorch. The output of this function should be a list of tensors PyTorch Code Implementation. Could someone please explain, or give an example of how to use this layer instead of a regular LogSoftmax layer? Thanks! 这个api实现的功能简单，就是把softmax的结果再进行log计算一遍。先来看一下它和tf. 文章浏览阅读1k次。1. The LogSoftmax formulation can be simplified as: Run PyTorch locally or get started quickly with one of the supported cloud platforms. CrossEntropyLoss 注意，使用这个类时最好要指定dim，即沿着tensor的哪一个维度做softmax Recipe Objective. 1 # mean and standard . it is a generalization of logistic function used in logistic regression, with softmax() it is called multinomial logistic regression. m = torch. LogSoftmax(dim=1)(pred1[:, :10]), dim=-1, When using the LogSoftmax & NLLLoss pair, why doesn’t a “one hot” input of the correct category produce a loss of zero? I suspect I’m missing something. sum(dim=2) I would like to know if Run PyTorch locally or get started quickly with one of the supported cloud platforms. Softmax lets you convert the output from a Linear layer into a categorical probability distribution. None Few important notes about softmax():. Softmax(dim=1) or self. While mathematically equivalent to The function torch. Here’s what it says in master, if you build from source: In [5]: ?torch. Forums. Aquí nos gustaría mostrarte una descripción, pero el sitio web que estás mirando no lo permite. logsoftmax(dim=-1) I am building a binary classification where the class I want to predict is present only <2% of times. LogSoftmaxOptions (int64_t dim) ¶ inline auto dim (const int64_t & new_dim)-> decltype (* this) 機械学習フレームワーク PyTorch を使ってモデルを作成する際、softmax レイヤーを使う場合は注意が必要. Softmax做什么的：将Softmax函数应用于n维输入张量，重新缩放它们，以便n维输出张量的元素位于[0，1]范围内，并且总和为1。注意事项：需要指定按照行和为1还是列和为1，参数设置dim=1表示行和为1，dim=0表示列和为1。计算公式：难点：看到公式，手动该如何计算？ 在本地运行 PyTorch 或通过一种支持的云平台快速入门. Thanks again to all for the explanations. According to its documentation, the softmax operation is applied to all slices of input along the specified dim, and w 文章浏览阅读2. NLLLoss print (nll_loss (x_log, y)) # tensor(2. I was checking the C code for LogSoftmax, then I came to this line, Now LogSoftmax can be expressed as, x_i - log( exp(x). sum(torch. LogSoftmax(dim=2)(logits)). I do not want to apply the log_softmax function to each t_i separately, but to all of them as if they were part of the same unique tensor. I want to get surprisal values from logit outputs from PyTorch, using log base 2. Softmax and nn. 9 and 1. Use `LogSoftmax` instead (it's faster and has better numerical properties). Alternatively, you can use negative dimension indexing to start from the last dimension to the first: -1 indicate the last dimension, -2 the second from last AdaptiveLogSoftmaxWithLoss¶ class torch. entropy1 = -torch. 通过我们引人入胜的 YouTube 教程系列掌握 PyTorch 基础知识 针对高维张量，务必指定softmax计算的维度，否则结果按照默认维度会有问题，这也是新版本PyTorch的警告。我们来模拟一个批量求解多个向量的概率分布的情况，代码如下，显然这是一个shape为(2,7)的张量，我们需要在 7 这个维度 Pytorch中Softmax和LogSoftmax的使用详解 一. , a list [t_1, t_2, , t_n] where each t_i is of type torch. LogSoftmax module:. LogSoftmax (dim = 1) >>> loss_fn = nn. torch. 学习基础知识. oasjd7 (oasjd7) January 17, 2020, 6:03pm 1. in which dimension the class logits are located. The ground-truth is always one label from one of the sets. poisson. In case of the Softmax Function, it is applied to an n-dim input tensor in which it will be rescaling them so that the elements of the output n-dim tensor lie in the range [0,1] and sum to 1. Learn about PyTorch’s features and capabilities. LogSoftmax() and nn. softmax(x / temperature, dim=1) 文章浏览阅读2. I am confused about the exact meaning of “logits” because many call them “unnormalized log-probabilities”. nn. randn(2, 3) >>> output = m(input) What are criteria for choosing “dim=0 or 1” for nn. Share Improve this answer Hi! I am trying to compute softmax_cross_entropy_with_logits in PyTorch. 通过我们引人入胜的 YouTube 教程系列掌握 PyTorch 基础知识 As far as I know, CrossEntropy() equals to torch. What is the difference between softmax and logsoftmax in pytorch?. Skip to main content. Learn the Basics. Thus, when I had two logsoftmax, the logsoftmax of logsoftmax would give you the same result, thus the model was actually performing correctly, but when I switched to just softmax, then it was messing up the numbers. LogSoftmax(dim=1) as indicated in the docs but got TypeError: __init__() got an unexpected keyword argument 'dim' I'm Run PyTorch locally or get started quickly with one of the supported cloud platforms. PyTorch Forums How to choose "dim =0/1" for softmax or logsoftmax. 今回は以下の配列を例にやってみる。 Why then in PyTorch documentation such example:. Applies the log Returns cosine similarity between x 1 x_1 x 1 and x 2 x_2 x 2 , computed along dim. logsoftmax(dim=1)是一个PyTorch中的函数，用于计算输入张量在指定维度上的log softmax值。其中，dim参数表示指定的维度。具体来说，对于输入张量x，log softmax的计算公式为： log softmax(x) = log(exp(x) / sum I’m trying to calculate the log_softmax function of a list of tensors, i. log_softmax Signature: torch. pytorch中常用的损失函数列举: pytorch中的nn模块提供了很多可以直接使用的loss函数, 比如MSELoss(), CrossEntropyLoss(), NLLLoss() 等官方链接:https: _nn. F. crossentropy dim (python:int) – A dimension along which Softmax will be computed (so every slice along dim will sum to 1). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. In a classification task where the input can only belong to one class, the softmax function is naturally used as the final activation function, taking in “logits” (often from a preceeding linear layer) and outputting proper probabilities. Currently I am unable to do so. Options for the LogSoftmax module. It should be possible to use softmax with arbitrary dimensions without the use of hacky workarounds by the user. randn (2, 3) 改善点. Intro to PyTorch - YouTube Series The shape of out is expected to be [batch_size, nb_classes], while yours seems to be only [batch_size]. However, why trainng this I am getting NAN as my predictions even before completeing the first batch of training (batch 本文介绍了Pytorch中关于log_softmax隐式维度选择的UserWarning警告信息。我们探讨了该警告的原因和影响，并提供了解决方案和示例说明。通过显式地指定log_softmax函数的dim参数，我们可以避免意外的错误结果，并更好地使用Pytorch的log_softmax函数。 LogSoftmax class torch. Softmax(dim=1)来处理序列 利用爬虫获取 1688 商品详情：高效的数据采集方法 1738 参考平面的宽度-信号与电源完整性分析 64 基于 mcp 协议的接口测试：发送请求与响应断言，测试工程师看过来 633 混合式研修中教师数字素养发展的关键影响因素及提升策略——基于结构方程模型的验证 For those looking to take their Softmax game to the next level, here are a few advanced techniques: Temperature Scaling: You can adjust the “temperature” of the Softmax function to make the output distribution sharper or smoother. Examples:: >>> m = nn. nn. 易于理解、随时可用的 PyTorch 代码示例. softmax(logits, dim = 2) surprisals = -torch. Run PyTorch locally or get started quickly with one of the supported cloud platforms. PyTorch Recipes. CrossEntropyLoss则结合两者，直接用于分类问题的损失计算。在使用nn. 딥러닝 학습시, softmax 함수를 이용하면 Vanishing Gradients(기울기 손실) 문제가 발생하기 쉬운데, 이 문제를 해결하기 위해 사용하는 것이 LogSoftmax 이다. vision. Tutorials. About; Products It covers basics of image classification with pytorch on a real dataset and its a very short tutorial. 0, head_bias = False, device = None, dtype = None) [source] [source] ¶. 0): return nn. NLLLoss计算负对数似然损失，而nn. 返回：. As far as I know, I am building a binary classification where the class I want to predict is present only <2% of times. Size([1, 10]) which is the nn. Github; Table of Contents. This code : %reset -f import torch. . The LogSoftmax formulation can be simplified as: As you can see, there is usually a flag that defines whether or not softmax will be computed using the log. softmax的异同，以及实现代码，然后再讨论一下为什么会有这个api的存在。 Learn how to implement and optimize softmax in PyTorch. PyTorch 教程的新内容. LogSoftmax(dim = 1) def forward (self, x): x = self. log_softmax(input, dim=None, _stacklevel=3) Docstring: Applies a softmax followed by a logarithm. From basics to advanced techniques, improve your deep learning models with this comprehensive guide. 教程. 1k次。这篇博客介绍了PyTorch中Softmax和LogSoftmax函数的使用方法。通过示例展示了如何对矩阵的行或列进行Softmax运算，以及LogSoftmax是Softmax的对数形式。文章还验证了Softmax运算后每一行元素之和为1，以及LogSoftmax确实是对Softmax取对数 torch. I tried ls = torch. I understand that PyTorch's LogSoftmax function is basically just a more numerically stable way to compute Log(Softmax(x)). dtype, optional) – the desired data type of returned tensor. sum(F. As you can see, both activation functions are the same, only with a log. import torch import torch. Compare the documentation for CrossEntropyLoss in versions 1. The pytorch documentation says that CrossEntropyLoss combines nn. 简短、随时可部署的 PyTorch 代码示例. As you might already know, the result of softmax are probabilities between 0 and 1. dim (int) – A dimension along which LogSoftmax will be computed. softmax PyTorch Forums nn. 1/generated/torch. LogSoftmax(input), dim=1)) How can I express nn. 与输入具有相同维度和形状的张量，其值在 [-inf, 0) 范围内 PyTorch layers accept batched inputs where often the dimensions represent [batch_size, features, ]. Accidentally I had two logsoftmax - one was in my loss function ( in cross entropy). log_softmax(predictions, dim=1): Calculates the logarithm of the softmax probabilities. Why it use dim=0 here? https: 2. mean(torch. One way to do this, given a logits tensor, is: probs = nn. inline auto dim (int64_t & & new_dim) Suppose I have an n-dimensional tensor and would like to apply LogSoftmax on a given dimension. Join the PyTorch developer community to contribute, learn, and get your questions answered. N L L L o s s NLLLoss N L L L o s s function은 l o g log l o g 를 취해주지 않는다! [PyTorch] Autograd-02 : LogSoftmax and Negative Log-Likelihood Loss. dim1 is therefore used to represent the number of classes in a classification use case. ; softmax() probabilities for all the inputs should add to 1 calculating log_softmax()is numerically stable comparing the calculating log() after softmax(); logsoftmax vs. BCELoss, if you already applied sigmoid on your output). AdaptiveLogSoftmaxWithLoss. LogSoftmax(dim: Optional[int] = None) [source] Applies the log ⁡ (Softmax (x)) \log(\text{Softmax}(x)) function to an n-dimensional input Tensor. softmax(pred1[:, :10], dim=1) * nn. Have a look at this small example dim (int) – A dimension along which Softmax will be computed (so every slice along dim will sum to 1). PyTorch 入门 - YouTube 系列. dtype (torch. 首先，先看官方定义 dim: A dimension along which Softmax will be computed (so every slice along dim will sum to 1) 具体解释为： 当 dim=0 时，是对每一维度相同位置的数值进行softmax运算； 当 dim=1 时，是对某一维度的 The following are 30 code examples of torch. Motivation pytorch 1. LogSoftmax、nn. sum() ) But what is the significance of adding maxinput with log( exp(x). softmax = nn. Softmax クラスのインスタンスを作成する際、引数dimで軸を指定すればよい。 やってみよう. This is something useful for us to understand. There’ve been other questions on this forum asking about LogSoftmax vs Softmax. softmax(input, dim=None, *, dtype torch. 7. 로그 소프트맥스는 소프트맥스에 log함수를 취한 것으로(log(softmax)), softmax 함수를 보완하는 역할을 한다. nn中的三个类：nn. LogSoftmax(dim=1) my questions I should use softmax as it will provide outputs that sum up to 1 and I can check performance for various prob thresholds. In a nutshell, I have 2 types of sets for labels. nn as nn import numpy as np import torch my_softmax = nn. PyTorch 代码示例集. LogSoftmax(). Torch NN module in pytorch has predefined and ready-to-use loss functions out of the box that you can use to train your neural network. , LogSoftMax instead of SoftMax. softmax(x,dim = -1)中的参数dim是指维度的意思，设置这个参数时会遇到0,1，2，-1等情况，特别是对2和-1不熟悉，细究了一下这个问题查了一下API手册，是指最后一行的意思。 Ah, sorry for the confusion, as I can see the misunderstanding now. dim – A dimension along which LogSoftmax will be computed. NLLLoss() in one single class. NLLLoss() # input is of size N x C = 3 x 5 input = torch. Softmax. Developer Resources. LogSoftmax 的用法。. 1438) # Case 3 nll_loss = torch. I'm trying to use the torch. 文章浏览阅读1. 0; 軸の指定方法. tensor([[1, Run PyTorch locally or get started quickly with one of the supported cloud platforms. LogSoftmax(dim=1) loss = nn. PyTorch 教程的新增内容. Models (Beta) LogSoftmax (dim = None) [source] Once you have PyTorch up and running, here’s how you can add loss functions in PyTorch. Example: LogSoftmax model (LogSoftmaxOptions (1)); Public Functions. Stack Overflow. I am using pytorch. nn library. Let’s do a simple code walk-through that will guide you on how to add a loss function in PyTorch using a torch. 1438) Keypoint 1. As described in Efficient softmax approximation for GPUs by Edouard Grave, Armand Joulin, Moustapha Cissé, David Grangier, and Hervé Jégou. thank a lot for your answer, sir. LogSoftmax(dim=None) 参数：. According to its documentation, the softmax operation is applied to all slices of input along the specified dim, The dim argument defines which dimension should be used to calculate the log softmax, i. g. Applying a log_softmax on this dimension transforms logits to log probabilities and normalizes them over the class dimension. self. html Softmax vs LogSoftmax. LogSoftmax equals to torch. This module doesn’t work directly with NLLLoss, which expects the Log to be computed Applies the \log (\text {Softmax} (x)) log(Softmax(x)) function to an n-dimensional input Tensor. Whats new in PyTorch tutorials. Applies the \log (\text {Softmax} (x)) log(Softmax(x)) function to an n-dimensional input Tensor. Dimension along which LogSoftmax will be computed. The LogSoftmax formulation can be simplified as: dim (int) – A dimension along which LogSoftmax will be computed. 損失計算の後に、optimizer. Softmax」モジュールは、ニューラルネットワークの出力層で確率分布を表現するために使用されます。本チュートリアルでは、以下の内容を Hi all, I have a multiclass classification problem and my network structure is a bit complex than usual. The LogSoftmax formulation can be simplified as: dim (int) – A dimension along which Applying a log_softmax on this dimension transforms logits to log probabilities and normalizes them over the class dimension. Softmax」モジュールの詳細な解説を行います。「torch. PairwiseDistance. 熟悉 PyTorch 概念和模块. Softmax和torch. LogSoftmax用于计算softmax并取对数，nn. The formula posted in my previous post is, how the loss can be calculated, but you shouldn’t worry about the minus sign, as it will be applied internally for you. From the documentation, dim (int) – A dimension along which Softmax will be computed (so every slice along dim will sum to 1). a Tensor of the same dimension and shape as the input with values in the range [-inf, 0) When specifying a tensor's dimension as an argument for a function (e. Yet they are different from applying このチュートリアルでは、PyTorchにおけるニューラルネットワークと「torch. NLLLoss和nn. Bite-size, ready-to-deploy PyTorch code examples. zero_grad()とoptimizer. 熟悉 PyTorch 的概念和模块. LogSoftmax(dim=1) my questions. @ptrblck I found PyTorch official example use dim=0 for muiticlass classification. (2)dim=1:对每一行的所有元素进行softmax运算,并使得每一行所有元素和为1. AdaptiveLogSoftmaxWithLoss (in_features, n_classes, cutoffs, div_value = 4. LogSoftmax module and I want to specify the dim. Find resources and get questions answered. LogSoftmax in equation? nn. A place to discuss PyTorch code, issues, install, research. log2(probs) However, PyTorch provides a function that combines log and softmax, which is faster than the above: 🚀 Feature Right now, it is not possible to export a softmax function that doesn't use dim=-1. torch. LogSoftmax(dim=None) Applies PyTorchは、確率分布を扱うためのモジュール「torch. PyTorch で input データを作成するときは、以下のように配列の次元が増えていく CLASS torch. Softmax函数常用的用法是 指定参数 dim 就可以： （1） dim=0 ：对 每一列 的所有元素进行softmax运算，并使得每一列所有元素 和为1 。 （2） dim=1 ：对 每一行 的所有元素进行softmax运算，并使得每一行所有元素 和为1 。 The function torch. LogSoftmax() equation. nn as nn m = nn. NLLLoss、nn. log_softmax torch. dim() - 将沿其计算LogSoftmax 的维度。. functional. Returns. icqe haer zydswvor emadx qpfnv vbon jqdn ewmv zcnbk ewrjaf kvsq vtcbjaut ftbfn toia vwpt