GPytorch Runtime Error has different input types
I am following the simple regression tutorial on gpytorch and get the following error when trying to use 2 dimensional input space during a call to the loss function.
RuntimeError: !(has_different_input_dtypes &amp;&amp; !config.promote_inputs_to_common_dtype_ &amp;&amp; (has_undefined_outputs || config.enforce_safe_casting_to_output_ || config.cast_common_dtype_to_outputs_)) INTERNAL ASSERT FAILED at &quot;../aten/src/ATen/TensorIterator.cpp&quot;:405, please report a bug to PyTorch. 

I am not quite sure what it means. Everything but the training data is still: https://github.com/cornellius-gp/gpytorch/blob/master/examples/01_Exact_GPs/Simple_GP_Regression.ipynb

The issue was my conversion of torch tensor.
I used: torch.from_numpy(array)
Instead I should use: torch.tensor(array)
This is weird, but no issues now.
