main/model/cfg_sampler.py

import numpy as np
import torch
import torch.nn as nn
from copy import deepcopy

# A wrapper model for Classifier-free guidance **SAMPLING** only
# https://arxiv.org/abs/2207.12598
class ClassifierFreeSampleModel(nn.Module):

 def __init__(self, model):
 super().__init__()
 self.model = model # model is the actual model to run

 assert self.model.cond_mask_prob > 0, 'Cannot run a guided diffusion on a model that has not been trained with no conditions'

 # pointers to inner model
 self.rot2xyz = self.model.rot2xyz
 self.translation = self.model.translation
 self.njoints = self.model.njoints
 self.nfeats = self.model.nfeats
 self.data_rep = self.model.data_rep
 self.cond_mode = self.model.cond_mode

 def forward(self, x, timesteps, y=None):
 cond_mode = self.model.cond_mode
 assert cond_mode in ['text', 'action']
 y_uncond = deepcopy(y)
 y_uncond['uncond'] = True
 out = self.model(x, timesteps, y)
 out_uncond = self.model(x, timesteps, y_uncond)
 return out_uncond + (y['scale'].view(-1, 1, 1, 1) * (out - out_uncond))