Allow torch tensors and cupy arrays as input to quantum kernels

[zohimchandani]

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Describe the bug

Pytorch tensors and cupy arrays lie on GPU memory and we need to be able to input them into quantum kernels from GPU. Can we please add support for these?

The code snippet below works fine for numpy:

import cudaq 
from cudaq import spin 
import numpy as np 

n_samples = 5 
n_params = 2 

params = np.random.rand(n_samples, n_params)

@cudaq.kernel
def kernel(params: np.ndarray):
    
    qvector = cudaq.qvector(1)
    
    rx(params[0], qvector[0])
    ry(params[1], qvector[0])
                
result = cudaq.observe(kernel, spin.z(0), params)

result

It does not work for torch.Tensor inputs:

import cudaq 
from cudaq import spin 
import torch


n_samples = 5 
n_params = 2 

params = torch.rand(n_samples, n_params)

@cudaq.kernel
def kernel(params: torch.Tensor):
    
    qvector = cudaq.qvector(1)
    
    rx(params[0], qvector[0])
    ry(params[1], qvector[0])
                
result = cudaq.observe(kernel, spin.z(0), params)

result

CompilerError: 792851843.py:12: error: torch is not a supported type.
	 (offending source -> torch.Tensor)

and a similar error is shown for cupy arrays:

import cudaq 
from cudaq import spin 
import cupy as cp 

n_samples = 5 
n_params = 2 

params = cp.random.rand(n_samples, n_params)

@cudaq.kernel
def kernel(params: cp.ndarray):
    
    qvector = cudaq.qvector(1)
    
    rx(params[0], qvector[0])
    ry(params[1], qvector[0])
                
result = cudaq.observe(kernel, spin.z(0), params)

CompilerError: 1207908829.py:11: error: cp is not a supported type.
	 (offending source -> cp.ndarray)

Steps to reproduce the bug

NA

Expected behavior

NA

Is this a regression? If it is, put the last known working version (or commit) here.

Not a regression

Environment

• CUDA Quantum version:
• Python version:
• C++ compiler:
• Operating system:

Suggestions

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