Is it possible to use ProcessPoolExecutor to accelerate the for loop in the forward method in QApproximating_EN.ipynb

[DS-Liu]

Since the forward method in the example Quantum Neural Network Approximating Functions uses a for loop, it's quite slow when the depth of the circuit is large. I want to use ProcessPoolExecutor to replace the for loop.

While using ProcessPoolExecutor with paddle, this error cannot pickle 'Tensor' object always occurs. I also meet another error cannot pickle 'ParamBase' object. I'm wondering whether it's possible to accelerate the for loop. Can anyone provide a parallelized version of the example Quantum Neural Network Approximating Functions?

[gxli2017]

Are you asking about parallel computation for batches? This feature will be available in the future. If you would like to use it now, you can message me privately at [email protected].