train.py index 1 is out of bounds for dimension 1 with size 1

This error message suggests that the index being accessed in the second dimension of a tensor is out of bounds. Specifically, the size of the second dimension is 1, but the index being accessed is 1 or greater.

To fix this error, you should check the code where the tensor is being accessed and make sure that the index being used is within the bounds of the tensor's dimensions. You may need to modify the values being used for the index or the size of the tensor to ensure that the index is valid.

相关问题

IndexError: index 7200 is out of bounds for dimension 1 with size 7200

这个错误是IndexError: index 7200 is out of bounds for dimension 1 with size 7200。这个错误通常是由于数组索引超出了数组的维度范围导致的。
一种可能的原因是，在代码中使用了一个数组索引值，该值大于数组的大小。例如，在一个维度为7200的数组中，如果尝试访问索引为7200的位置，就会出现这个错误。
要解决这个问题，你可以检查代码中的索引值，并确保它们在数组的有效范围内。你还可以使用条件语句来处理可能的索引越界情况，以避免出现这个错误。另外，还可以使用try-except语句来捕获并处理IndexError错误，以提供更好的错误处理和用户友好的提示信息。<span class="em">1</span><span class="em">2</span><span class="em">3</span>
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IndexError: index 4 is out of bounds for dimension 1 with size 3

This error message indicates that you are trying to access an element in an array or list using an index that is outside the range of valid indices for that array or list. In this case, the array or list has a size of 3 in the second dimension, but you are trying to access an element at index 4, which is out of bounds.

For example, if you have an array like this:

my_array = [[1,2,3],[4,5,6],[7,8,9]]

And you try to access an element using an out-of-bounds index like this:

print(my_array[1][4])

You will get the IndexError message:

IndexError: index 4 is out of bounds for dimension 1 with size 3

To fix this error, make sure that you are using valid indices when accessing elements in your arrays or lists.