Fix for GPU Diag issue #1679

[kmp5VT]

Description

This is a generic Fix for the outer product of two diag tensors (i.e. outer product of two vectors blas ger function.) This uses Julia a .* b' feature from julia and seems to work on CPU and GPU with no indexing problem.
I added a unit tests to check in the NDTensors/diag test

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diff --git a/NDTensors/test/test_diag.jl b/NDTensors/test/test_diag.jl
index ac54e023f..86640c254 100644
--- a/NDTensors/test/test_diag.jl
+++ b/NDTensors/test/test_diag.jl
@@ -123,10 +123,10 @@ end
 
     ## Test dot on GPU
     @test dot(t, A) ≈ dot(dev(array(t)), array(A)) rtol = sqrt(eps(elt))
-    
-    NDTensors.outer!(A, t,t);
+
+    NDTensors.outer!(A, t, t)
     for i in NDTensors.cpu(A)
-       @test i == one(elt)
+        @test i == one(elt)
     end
 end
 nothing

[mtfishman]

It looks like there are a few issues with this proposal:

1. t2' will complex conjugate the elements, while outer[!] isn't supposed to conjugate the elements. Maybe transpose could be used as an alternative.
2. t1 * transpose(t2) when t1 and t2 are vectors will output a matrix whose length this the product of the lengths of the diagonals of T1 and T2, I don't understand how the shapes of this operation work out since R in general is a tensor whose length is the product of the total lengths of T1 and T2 (not just the lengths of their diagonals). I think maybe you want to do something like t1 * transpose(t2) and reshape it into a vector (or relatedly, something like kron(t1, t2), which has an in-place counterpart kron!) and use that to write into the diagonal values of R.

It looks like you'll need to investigate this more to make sure it really does the correct operation.