Fixed "sqrt_matrix" to working in tensorflow graph mode

[vinayak19th]

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Context:
When using qml.math.fidelity, it calls the "sqrt_matrix" function. This function has a cast call when not using an abstract vector. However, this causes issues when running in a tensorflow graph mode.

When executing in graph mode with tensorflow, the multiply operation

vecs @ sqrt_evs @ qml.math.conj(qml.math.transpose(vecs, (0, 2, 1)))

causes a type error as both the eigenvectors are of type "complex" and the sqrt values are "float". This seems to be specific to the broadcast case.

Description of the Change:

Added a typecast call to fix this issue:

sqrt_evs = qml.math.expand_dims(qml.math.sqrt(evs), 1) * i
+ sqrt_evs = qml.math.cast_like(sqrt_evs, vecs)
- return vecs @ sqrt_evs @ qml.math.conj(qml.math.transpose(vecs, (0, 2, 1)))
+ return qml.math.real(vecs @ sqrt_evs @ qml.math.conj(qml.math.transpose(vecs, (0, 2, 1))))

Also added a qml.real to handle typecast warnings when converting from complex -> float. As the product is guaranteed to be real, this will not cause any problems.

Benefits:
The fidelity function can now be used with batched tensors in graph mode.

Possible Drawbacks:
None

Related GitHub Issues: