Project scenario:

Today, I saw the code of an RNN instance. I want to try to pass in RNN with my own data, but I can report an error.

Problem Description:

The error is runtimeerror: expected scalar type long but found float

Cause analysis:

The wrong input is as follows:

input=torch.tensor([ 0,  0,  0,  0,  0,  0,  0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
         0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,
         0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,
         0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,
         0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,
         0,  0,  0,  0,  0,  0])

The input in the example is as follows:

input=torch.tensor([[0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0.,0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,0.]])

The reason is that I set dtype = torch.long when generating input

Solution:

Input = torch. Tensor (input, dtype = torch. Float)
specify dtype = torch. Float when generating the input tensor, and the resulting input will be of the following types

input=torch.tensor([[0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0.,0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,0.]])

If it meets the requirements, no error will be reported
I didn’t expect to solve this problem. I spent most of the night. I really haven’t started yet. I don’t have enough skills.