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我正在尝试使用 pylearn2 构建 MLP 模型。但是该手册并没有明确说明如何导入外部数据（所有教程都使用 MNSIT 数据）。

所以，我的数据是 CSV 文件：

0 0.129 -0.234 0.394 ... 
0 0.293 -0.394 0.234 ... 
1 0.192 -0.842 0.123 ...
...

所以它是一个矩阵，第一列是要预测的值，其他列是属性。我什至不知道这是否是正确的输入。

这是我的 YAML 文件：

!obj:pylearn2.train.Train {
    dataset: &train !obj:pylearn2.datasets.csv_dataset.CSVDataset {
        path: 'train.csv',
        task: 'regression',
        start: 0,
        stop: 53607,
        expect_headers: False,
        num_outputs: 1
    },
    model: !obj:pylearn2.models.mlp.MLP {
        layers : [
            !obj:pylearn2.models.mlp.Sigmoid {
                layer_name: 'h0',
                dim: 10,
                irange: .05
            },
            !obj:pylearn2.models.mlp.Softmax {
                layer_name: 'y',
                n_classes: 2,
                irange: 0.
            },
        ],
        nvis: 220,
    },
    algorithm: !obj:pylearn2.training_algorithms.bgd.BGD {
        batch_size: 1024,
        conjugate: 1,
        updates_per_batch: 10,
        monitoring_dataset:
            {
                'train' : *train,
                'valid' : !obj:pylearn2.datasets.csv_dataset.CSVDataset {
                    path: 'test.csv',
                    task: 'regression',
                    start: 0,
                    stop: 17868,
                    expect_headers: False,
                }
            },
        termination_criterion: !obj:pylearn2.termination_criteria.And {
            criteria: [
                !obj:pylearn2.termination_criteria.MonitorBased {
                    channel_name: "valid_y_misclass"
                },
                !obj:pylearn2.termination_criteria.EpochCounter {
                    max_epochs: 10000
                }
            ]
        }
    },
    extensions: [
        !obj:pylearn2.train_extensions.best_params.MonitorBasedSaveBest {
             channel_name: 'valid_y_missclass',
             save_path: "best.pkl"
        },
    ],
}

所以，有两个类，但如果你有一个矩阵而不是一个向量，它说这个任务是一个回归。

这是我运行“train.py training.yaml”时的输出错误

Traceback (most recent call last):
  File "train.py", line 261, in <module>
    args.verbose_logging, args.debug)
  File "train.py", line 206, in train
    train_obj = serial.load_train_file(config)
  File "/home/romain/Projet/long/pylearn2/pylearn2/utils/serial.py", line 430, in load_train_file
    return yaml_parse.load_path(config_file_path, environ=environ)
  File "/home/romain/Projet/long/pylearn2/pylearn2/config/yaml_parse.py", line 255, in load_path
    return load(content, instantiate=instantiate, environ=environ, **kwargs)
  File "/home/romain/Projet/long/pylearn2/pylearn2/config/yaml_parse.py", line 213, in load
    return _instantiate(proxy_graph)
  File "/home/romain/Projet/long/pylearn2/pylearn2/config/yaml_parse.py", line 156, in _instantiate
    return _instantiate_proxy_tuple(proxy, bindings)
  File "/home/romain/Projet/long/pylearn2/pylearn2/config/yaml_parse.py", line 121, in _instantiate_proxy_tuple
    for k, v in six.iteritems(proxy.keywords))
  File "/home/romain/Projet/long/pylearn2/pylearn2/config/yaml_parse.py", line 121, in <genexpr>
    for k, v in six.iteritems(proxy.keywords))
  File "/home/romain/Projet/long/pylearn2/pylearn2/config/yaml_parse.py", line 156, in _instantiate
    return _instantiate_proxy_tuple(proxy, bindings)
  File "/home/romain/Projet/long/pylearn2/pylearn2/config/yaml_parse.py", line 121, in _instantiate_proxy_tuple
    for k, v in six.iteritems(proxy.keywords))
  File "/home/romain/Projet/long/pylearn2/pylearn2/config/yaml_parse.py", line 121, in <genexpr>
    for k, v in six.iteritems(proxy.keywords))
  File "/home/romain/Projet/long/pylearn2/pylearn2/config/yaml_parse.py", line 161, in _instantiate
    for k, v in six.iteritems(proxy))
  File "/home/romain/Projet/long/pylearn2/pylearn2/config/yaml_parse.py", line 161, in <genexpr>
    for k, v in six.iteritems(proxy))
  File "/home/romain/Projet/long/pylearn2/pylearn2/config/yaml_parse.py", line 156, in _instantiate
    return _instantiate_proxy_tuple(proxy, bindings)
  File "/home/romain/Projet/long/pylearn2/pylearn2/config/yaml_parse.py", line 122, in _instantiate_proxy_tuple
    obj = checked_call(proxy.callable, kwargs)
  File "/home/romain/Projet/long/pylearn2/pylearn2/utils/call_check.py", line 99, in checked_call
    return to_call(**kwargs)
  File "/home/romain/Projet/long/pylearn2/pylearn2/datasets/csv_dataset.py", line 123, in __init__
    X, y = self._load_data()
  File "/home/romain/Projet/long/pylearn2/pylearn2/datasets/csv_dataset.py", line 149, in _load_data
    data = np.loadtxt(self.path, delimiter=self.delimiter)
  File "/usr/lib/python2.7/dist-packages/numpy/lib/npyio.py", line 856, in loadtxt
    X = np.array(X, dtype)

我从“pylearn/pylearn/scripts/train.py”复制了 train.py，CSV 文件位于实际文件夹中。

我的 YAML 文件有问题吗？我真的不明白错误的含义。

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