请求的数组在 1 维后具有不均匀的形状。检测到的形状是 (33,) + 不均匀部分

Question

我卡在了将列表转换为 numpy 的过程中。转换列表大小为 (33, n, 428)。 N 是随机差异，我不知道数字是如何组成的。这是错误。

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
C:\Users\HILAB_~1\AppData\Local\Temp/ipykernel_22960/872733971.py in <module>
----> 1 X_train = np.array(X_train, dtype=np.float64)
      2 
      3 for epoch in range(EPOCH):
      4     X_train_ten, y_train_ten = Variable(torch.from_numpy(X_train)), Variable(torch.tensor(y_train, dtype=torch.float32, requires_grad=True))
      5     print(X_train_ten.size())

ValueError: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (33,) + inhomogeneous part.

问题代码在这里。

X_train, X_test, y_train, y_test = train_test_split(
    X, y, test_size=0.3, random_state=42, shuffle=True
)

print("[SIZE]\t\tTrain X size : {}, Train y size : {}\n\t\tTest X size : {}, Test y size : {}"\
        .format(len(X_train), len(y_train), len(X_test), len(y_test)))

train_dataloadloader = DataLoader(X_train)
test_dataloader = DataLoader(X_test)

X_train = np.array(X_train, dtype=np.float64)

我不明白错误是什么意思。请帮忙。谢谢 :D

Answer 1

意思是X无论包含什么序列，它们的长度都不一样。您可以检查{len(e) for e in X)；这是在 X.

中找到的所有不同长度的集合

考虑以下示例：

>>> import numpy as np
>>> x = [[1, 2], [2, 3, 4]]
>>> np.array(x, dtype=np.float64)
[...]
ValueError: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (2,) + inhomogeneous part.

此处，列表 x 包含另外两个列表，一个长度为 2，另一个长度为 3。它们不能组合成一个数组，因为“列”维度不匹配。

请求的数组在 1 维后具有不均匀的形状。检测到的形状是 (33,) + 不均匀部分

The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (33,) + inhomogeneous part

python

numpy