问无法从检查点正确加载PyTorch闪电模型

EN

    class LSTMClassifier(pl.LightningModule):
    def __init__(self, n_features, hidden_size, batch_size, num_layers, dropout, learning_rate):
        super(LSTMClassifier, self).__init__()
        self.save_hyperparameters()

        # Params
        self.n_features = n_features
        self.hidden_size = hidden_size
        self.batch_size = batch_size
        self.num_layers = num_layers
        self.dropout = dropout
        self.learning_rate = learning_rate

        # Architecture Baseline
        self.lstm = nn.LSTM(input_size=n_features,
                            hidden_size=hidden_size,
                            num_layers=num_layers,
                            dropout=dropout,
                            batch_first=True)
        self.relu = nn.ReLU()
        self.fc = nn.Linear(hidden_size, 2)
        self.sigmoid = nn.Sigmoid()

    # Init PyTorch model
    model = LSTMClassifier(
         n_features=p['n_features'],
         hidden_size=p['hidden_size'],
         batch_size=p['batch_size'],
         num_layers=p['num_layers'],
         dropout=p['dropout'],
         learning_rate=p['learning_rate']
    )

    model_checkpoint = ModelCheckpoint(
        filename='[PATH.ckpt]'
    )

    # Trainer GPU
    trainer = Trainer(max_epochs=p['max_epochs'], callbacks=[model_checkpoint], gpus=int(GPU))

    trainer.fit(model, dm)

    trainer.test(model, test_dataloaders=dm.test_dataloader())

    model_checkpoint = ModelCheckpoint(
        filename='LSTM-batch-{batch_size}-epoch-{max_epochs}-hidden-{hidden_size}-layers-{'
                 'num_layers}-dropout-{dropout}-lr-{learning_rate}'.format(**p)
    )

    # Trainer GPU
    trainer = Trainer(max_epochs=p['max_epochs'], callbacks=[model_checkpoint], gpus=int(GPU))

    model = LSTMClassifier.load_from_checkpoint([PATH TO CHECKPOINT])
    model.eval()

    trainer.test(model, test_dataloaders=dm.test_dataloader())