断言错误：传入的张量形状必须是4D

Question

我试着做一个分类器，我一直得到这个错误，这让我很困惑。因为我对机器学习还不太熟悉，所以我在网上找不到任何东西。在

错误

AssertionError: Incoming Tensor shape must be 4-D

编码

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如果我给convnet = input_data(shape=[None,IMG_SIZE,IMG_SIZE,1],name='input') 它给了我这个错误

Exception in thread Thread-3:

Traceback (most recent call last):
  File "C:\Users\zeele\Miniconda3\lib\threading.py", line 916, in _bootstrap_inner
    self.run()
  File "C:\Users\zeele\Miniconda3\lib\threading.py", line 864, in run
    self._target(*self._args, **self._kwargs)
  File "C:\Users\zeele\Miniconda3\lib\site-packages\tflearn\data_flow.py", line 187, in fill_feed_dict_queue
    data = self.retrieve_data(batch_ids)
  File "C:\Users\zeele\Miniconda3\lib\site-packages\tflearn\data_flow.py", line 222, in retrieve_data
    utils.slice_array(self.feed_dict[key], batch_ids)
  File "C:\Users\zeele\Miniconda3\lib\site-packages\tflearn\utils.py", line 187, in slice_array
    return X[start]
TypeError: 'generator' object is not subscriptable

Answer 1

编辑：错误是由于这个

train = training_data[:-5000]
test = testing_data[-5000:]

X_train = np.array([i[0] for i in train]).reshape(-1, IMG_SIZE, IMG_SIZE, 3)
#The error was here
y_train = (i[1] for i in train)

X_test = np.array([i[0] for i in test]).reshape(-1, IMG_SIZE, IMG_SIZE, 3)
#The error was here
y_test = (i[1] for i in test)

在你列了一个单子后，它开始工作，如下所示。在

^{pr2}$