🐛 Bug

Tensor averaging not implemented for complex types

To Reproduce

>>> import torch
>>> x = torch.ones(4, dtype=torch.complex128).cuda()
>>> torch.mean(x)
---------------------------------------------------------------------------
RuntimeError                              Traceback (most recent call last)
<ipython-input-108-34af2dc3edea> in <module>
      1 impo

Description

Implement a YOLO model and add it to the DJL model zoo

References

• https://arxiv.org/abs/1506.02640

Issue to track tutorial requests:

• Deep Learning with PyTorch: A 60 Minute Blitz - #69

We do not permit specifying random generators in the poisson encoders. This should be allowed to ensure reproducibility.

• asarray : converts all array-likes to a numpy array; no copy for arrays
• astensor converts all array-likes to a mygrad tensor; returns tensors unchanged
• assert_almost_equal with various options to include checks of gradients and to include checks ac