RuntimeError: mean(): input dtype should be either floating point or complex dtypes. Got Long instead
I wrote below code using pytorch and ran into a runtime error:
tns = torch.tensor([1,0,1])
tns.mean()
---------------------------------------------------------------------------
RuntimeError                              Traceback (most recent call last)
&lt;ipython-input-666-194e5ab56931&gt; in &lt;module&gt;
----&gt; 1 tns.mean()

RuntimeError: mean(): input dtype should be either floating point or complex dtypes. Got Long instead.

However, if I change the tensor to float, the error goes away:
tns = torch.tensor([1.,0,1])
tns.mean()
---------------------------------------------------------------------------
tensor(0.6667)

My question is why the error happens. The data type of the first tenor is int64 instead of Long, why does PyTorch take it as Long?

This is because torch.int64 and torch.long both refer to the same data type, of 64-bit signed integers. See here for an overview of all data types.
