尝试使用 pytorch 训练神经网络时，“AttributeError：classificadorFinal”对象没有属性“log_softmax”

Question

我正在学习使用 pytorch，但出现错误，无法继续编程。

我的代码：

import torch.nn as nn
from skorch import NeuralNetClassifier #integracao com sklearn
from sklearn.model_selection import cross_val_score,GridSearchCV
from sklearn.preprocessing import LabelEncoder, MinMaxScaler
import torch
import torch.nn.functional as F
from torch import nn,optim

class classificadorFinal(nn.Module):
    def __init__(self, activation=F.tanh, neurons=16, initializer=torch.nn.init.uniform_, dropout=0.3):
        ##from melhores_parametros
        super().__init__()
        self.dense0 = nn.Linear(4, neurons)
        initializer(self.dense0.weight)
        self.activation0 = activation
        self.dense1 = nn.Linear(neurons, neurons)
        initializer(self.dense1.weight)
        self.activation1 = activation
        self.dense2 = nn.Linear(neurons, 3)

        self.dropout = nn.Dropout(dropout)

    def forward(self, X):
        X = self.dense0(X)
        X = self.activation0(X)
        X = self.dropout(X)
        X = self.dense1(X)
        X = self.activation1(X)
        X = self.dropout(X)
        X = self.dense2(X)
        return X


criterion = nn.CrossEntropyLoss()
optimizer = optim.Adam(classificador.parameters(), lr = 0.001, weight_decay = 0.0001)


#treino
for epoch in range(200):##from melhores_parametros

    running_loss = 0.
    running_accuracy = 0.

    for data in train_loader:
        inputs, labels = data

        optimizer.zero_grad()        

        outputs = classificadorFinal(inputs)

        loss = criterion(outputs, labels)###erro
        loss.backward()

        optimizer.step()

        running_loss += loss.item()

        ps = F.softmax(outputs)

        top_p, top_class = ps.topk(k = 1, dim = 1)

        equals = top_class == labels.view(*top_class.shape)

        running_accuracy += torch.mean(equals.type(torch.float))

    print('Época {:3d}: perda {:3.5f} - precisão {:3.5f}'.format(epoch + 1, running_loss/len(train_loader), running_accuracy/len(train_loader)))

错误发生在loss = criterion(outputs, labels):

AttributeError: 'classificadorFinal' 对象没有属性 'log_softmax'

我发现这个错误是众所周知的，但我不明白建议的解决方案：

disable aux_logits模型创建时aux_logits=False.

请帮忙！

Answer 1

输出实际上不是模型的输出，而是模型本身。 classificadorFinal 是类，调用它会创建该类的对象/实例，inputs 将是__init__ 方法的第一个参数，即activation。

# Creates an instance of the model
outputs = classificadorFinal(inputs)

您首先必须创建模型（一个实例），这应该完成一次，然后使用inputs 调用该模型。看起来您之前已经创建了模型，因为您使用 classificador.parameters() 作为优化器，因此 classificador 可能是模型的实例。您需要调用 classificador（实例）而不是 classificadorFinal（类）来创建输出。

# Call the instance of the model, not the class 
outputs = classificador(inputs)