numpy arrary has no attribute 'permute'
时间: 2023-08-05 14:07:26 浏览: 330
回答: 错误信息表明numpy数组没有'permute'属性。要使用'permute'函数,你需要将numpy数组转换为PyTorch张量。你可以使用torch.from_numpy()函数将numpy数组转换为张量,然后再使用'permute'函数。例如,你可以这样做:
```
import torchimport numpy as np# 假设你有一个numpy数组arrarr = np.array([[1,2,3], [4,5,6]])
# 将numpy数组转换为张量tensor = torch.from_numpy(arr)
# 使用'permute'函数对张量进行维度重排permuted_tensor = tensor.permute(1,0)
# 打印结果print(permuted_tensor)
```
这样,你就可以在PyTorch中使用'permute'函数对张量进行维度重排了。希望对你有帮助!
相关问题
module 'numpy' has no attribute 'permute'
The error message suggests that you are trying to use the `permute` function from NumPy, but NumPy doesn't have an attribute with that name. In fact, NumPy doesn't have a `permute` function, but rather a similar function called `transpose`.
Here's an example of how to use `transpose` in NumPy:
```python
import numpy as np
# create a 3-dimensional array
arr = np.array([
[[1, 2, 3], [4, 5, 6]],
[[7, 8, 9], [10, 11, 12]]
])
# transpose the array
arr_transposed = np.transpose(arr, (0, 2, 1))
print(arr_transposed)
```
The `transpose` function takes the array to be transposed as its first argument, and a tuple specifying the new order of the dimensions as its second argument. In this example, we're transposing the array from shape `(2, 2, 3)` to `(2, 3, 2)` by swapping the second and third dimensions.
module 'numpy' has no attribute 'int'. module 'numpy' has no attribute 'int'.
您好!对于您的问题,您可能遇到了一个常见的错误。在 numpy 模块中,没有名为 'int' 的属性。numpy 模块中的常见数据类型包括 int、float、bool 等,但它们并不是作为属性出现在 numpy 模块中。
如果您想创建一个 numpy 数组,您可以使用 numpy 提供的函数,如 numpy.array(),并指定所需的数据类型。例如,您可以使用以下代码创建一个整数类型的 numpy 数组:
```python
import numpy as np
arr = np.array([1, 2, 3], dtype=int)
```
请注意,我假设您已经正确安装了 numpy 模块。如果您没有安装 numpy,请使用以下命令进行安装:
```
pip install numpy
```
希望这可以帮助到您!如果您还有其他问题,请随时提问。
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