pytorch_quant_tool

An experimental neural network quantization environment in Pytorch.

Post Training Quantization

• NOTE: Fuse the well-trained model before operating Post Training Quantization.

fuse_model(model, rules, inplace=True):

Fuse the model with a list of rules.

• Args:
  • model: A nn.Module to be fused.
  • rules: A list of rule object functions as FuseRule.
  • inplace: Bool. If True, the model object will be modified.
• Return:
  • A new fused model, if inplace is False.

post_training_quant

Quant a trained model (int8).

• Args:
  • model: A fused nn.Module to be quanted.
  • data_loader: A data loader provides input data iterations.
  • batches: The limitation of iteration(batch) number. *inplace: Bool. If True, the model object will be modified.
• Return: A new quanted model, if inplace is False.