I had to convert my  CLDNN model from Keras to Torch. for work reasons.
In order to restore the performance of the model on Keras, the model structure, hy-params,the initialization of weight and bias are still done addcording to my CLDNN model.
The current result is that the classifcation result of torch is 3% less than the result on keras. The performance degardation is fatal in terms of my work.
Keras saves it’s weighted as doubles while PyTorch saves its weights as floats and there is a small amount of truncation error 4
And my question how to set  save my model’s weights as double rather float?