only one element tensors can be converted to python scalars
def Log(A):
    '''
    theta = arccos((tr(A)-1)/2)
    K=1/(2sin(theta))(A-A^T)
    log(A)=theta K
    '''
    theta=torch.acos(torch.tensor((torch.trace(A)-1)/2))
    K=(1/(2*torch.sin(theta)))*(torch.add(A,-torch.transpose(A,0,1)))
    
    return theta*K

def tensor_Log(A):
    blah=[[Log(A[i,j]) for j in range(A.shape[1])] for i in range(A.shape[0])]
    new=torch.tensor(blah)
    
    return new

ValueError: only one element tensors can be converted to Python scalars

during training to get the outputs of my network, the above function is producing the following error, it is called inside a custom layer and I do not know what it is referencing, any thoughts?

The issue in your list comprehension as blah is a list of list of tensors.
I would create a flat list of tensors by looping on A.shape[0] and A.shape[1] and then stack everything into a single tensor.
R = torch.stack([Log(A[i,j]) for i in range(A.shape[0]) for j in range(A.shape[1])])

You can then recover the desired format with reshape or view:
R.reshape(A.shape)

