功能和标签大小崩溃（tflearn）

Question

我正在使用pokemon kaggle数据集的tflearn。 我试图把口袋妖怪的名字作为word2vec，其余作为普通矩阵。 我正在尝试预处理数据。

我所做的是使用TF学习将名称更改为向量

word_processor = VocabularyProcessor(100)
trainX = newDF.loc[:, ["Total","HP","Attack","Defense","Sp. Atk", "Sp. Def","Speed","Generation"]].as_matrix()
trainY = np.array(list(word_processor.fit_transform(newDF["Name"])))
trainY[None : 0]
print('shape trainX: ',trainX.shape)
print('shape train Y: ',trainY.shape)

打印声明显示 shape trainX: (800, 8) shape train Y: (800, 100) 所以我认为这是问题所在，因为当我试图将这些数据提供给我的神经网络时，它会显示出来。

---------------------------------------------------------------------------
IndexError                                Traceback (most recent call last)
<ipython-input-53-78ce72c15f14> in <module>()
      3 # Start training (apply gradient descent algorithm)
      4 # Training
----> 5 model.fit(trainX, trainY, validation_set=0.1, show_metric=True, batch_size=100, n_epoch=8)

/anaconda/envs/MLHardCore/lib/python3.5/site-packages/tflearn/models/dnn.py in fit(self, X_inputs, Y_targets, n_epoch, validation_set, show_metric, batch_size, shuffle, snapshot_epoch, snapshot_step, excl_trainops, validation_batch_size, run_id, callbacks)
    181         # TODO: check memory impact for large data and multiple optimizers
    182         feed_dict = feed_dict_builder(X_inputs, Y_targets, self.inputs,
--> 183                                       self.targets)
    184         feed_dicts = [feed_dict for i in self.train_ops]
    185         val_feed_dicts = None

/anaconda/envs/MLHardCore/lib/python3.5/site-packages/tflearn/utils.py in feed_dict_builder(X, Y, net_inputs, net_targets)
    281                 X = [X]
    282             for i, x in enumerate(X):
--> 283                 feed_dict[net_inputs[i]] = x
    284         else:
    285             # If a dict is provided

IndexError: list index out of range

这是神经网络刚刚加入

def NN():
    net = tflearn.input_data(shape=[None, 8])
    net = tflearn.fully_connected(net, 32)
    net = tflearn.fully_connected(net, 32)
    net = tflearn.fully_connected(net, 2, activation='softmax')
    net = tflearn.regression(net)
    model = tflearn.DNN(net)
    return model

model = NN()

model.fit(trainX, trainY, validation_set=0.1, show_metric=True, batch_size=100, n_epoch=8)

我重新启动python之后的另一个新错误。

Exception in thread Thread-6:
 line 187, in slice_array
    return X[start]
IndexError: index 359 is out of bounds for axis 0 with size 100

Answer 1

尝试重新启动内核并清除输出并再次运行。 我也遇到过这个问题，这个解决方案对我有用。