属性错误：“优化”对象没有属性“火车”。当尝试实现多元时间序列时

Question

我正在尝试使用 pytorch 实现多元时间序列。在这里，我仅给出出现错误的代码部分，但我已将所有提到的类包含在我的完整代码中。该代码已引用自https://towardsdatascience.com/building-rnn-lstm-and-gru-for-time-series-using-pytorch-a46e5b094e7b

class Optimization:
    def __init__(self, model, loss_fn, optimizer):
        self.model = model
        self.loss_fn = loss_fn
        self.optimizer = optimizer
        self.train_losses = []
        self.val_losses = []
    
    def train_step(self, x, y):
        # Sets model to train mode
        self.model.train()

        # Makes predictions
        yhat = self.model(x)

        # Computes loss
        loss = self.loss_fn(y, yhat)

        # Computes gradients
        loss.backward()

        # Updates parameters and zeroes gradients
        self.optimizer.step()
        self.optimizer.zero_grad()

        # Returns the loss
        return loss.item() 

导入 torch.optim 作为 optim def get_model(模型, model_params): 型号={ “rnn”：RNN模型， “lstm”：LSTM模型， “gru”：GRU模型， } 返回 models.get(model.lower())(**model_params)

input_dim = len(X_train.columns)
output_dim = 1
hidden_dim = 64
layer_dim = 3
batch_size = 64
dropout = 0.2
n_epochs = 100
learning_rate = 1e-3
weight_decay = 1e-6

model_params = {'input_dim': input_dim,
                'hidden_dim' : hidden_dim,
                'layer_dim' : layer_dim,
                'output_dim' : output_dim,
                'dropout_prob' : dropout}

model = get_model('lstm', model_params)

loss_fn = nn.MSELoss(reduction="mean")
optimizer = optim.Adam(model.parameters(), lr=learning_rate, weight_decay=weight_decay)

opt = Optimization(model=model, loss_fn=loss_fn, optimizer=optimizer)

opt.train(train_loader, val_loader, batch_size=batch_size,
          n_epochs=n_epochs, n_features=input_dim)
opt.plot_losses()

predictions, values = opt.evaluate(test_loader_one, batch_size=1, n_features=input_dim)

我收到此错误：

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
e:\codefolder\multivar.ipynb Cell 21 in <cell line: 25>()
     22 optimizer = optim.Adam(model.parameters(), lr=learning_rate, weight_decay=weight_decay)
     24 opt = Optimization(model=model, loss_fn=loss_fn, optimizer=optimizer)
---> 25 opt.train(train_loader, val_loader, batch_size=batch_size, n_epochs=n_epochs, n_features=input_dim)
     26 opt.plot_losses()
     28 predictions, values = opt.evaluate(test_loader_one, batch_size=1, n_features=input_dim)

AttributeError: 'Optimization' object has no attribute 'train'

附注我已将所有类和代码包含在我引用的文章中给出的代码中。由于代码的空间和长度，我只包含了出现错误的主要代码。

Answer 1

你已经写了

opt = Optimization(...)

无需导入或定义该类。 Python 告诉你它无法识别该对象或其方法

我找到了

torch.optim.Optimizer

这里，这可能就是你要找的吗？