only Tensors of floating point and complex dtype can require gradients
时间: 2024-05-25 18:18:02 浏览: 11
This statement is not entirely accurate. While it is true that only tensors of floating point and complex dtype can require gradients in PyTorch, there are other ways to compute gradients in other data types. For example, in TensorFlow, integers and even boolean tensors can be used to compute gradients using the straight-through estimator. However, in PyTorch, only tensors of floating point and complex dtype can directly participate in the computation of gradients. This is because gradients are computed using numerical differentiation, which requires the ability to perform arithmetic operations on the tensor elements. Since integers and booleans are not continuous, there is no straightforward way to perform numerical differentiation on them, and hence they cannot be used to compute gradients directly.