diff --git a/codes/models/gpt_voice/unet_diffusion_tts_experimental.py b/codes/models/gpt_voice/unet_diffusion_tts_experimental.py index aba7d926..5f229613 100644 --- a/codes/models/gpt_voice/unet_diffusion_tts_experimental.py +++ b/codes/models/gpt_voice/unet_diffusion_tts_experimental.py @@ -66,11 +66,6 @@ class ResBlock(TimestepBlock): :param emb: an [N x emb_channels] Tensor of timestep embeddings. :return: an [N x C x ...] Tensor of outputs. """ - return checkpoint( - self._forward, x, emb - ) - - def _forward(self, x, emb): h = self.in_layers(x) emb_out = self.emb_layers(emb).type(h.dtype) while len(emb_out.shape) < len(h.shape): @@ -318,12 +313,12 @@ class DiffusionTts(nn.Module): h_tok = F.interpolate(module(tokens).permute(0,2,1), size=(h.shape[-1]), mode='nearest') h = h + h_tok else: - h = module(h, emb) + h = checkpoint(module, h, emb) hs.append(h) - h = self.middle_block(h, emb) + h = checkpoint(self.middle_block, h, emb) for module in self.output_blocks: h = torch.cat([h, hs.pop()], dim=1) - h = module(h, emb) + h = checkpoint(module, h, emb) h = h.type(x.dtype) out = self.out(h) return out[:, :, :orig_x_shape] @@ -377,6 +372,8 @@ if __name__ == '__main__': model = DiffusionTts(64, channel_mult=[1,1.5,2, 3, 4, 6, 8, 8, 8, 8], num_res_blocks=[2, 2, 2, 2, 2, 2, 2, 4, 4, 4], token_conditioning_resolutions=[1,4,16,64], attention_resolutions=[256,512], num_heads=4, kernel_size=3, scale_factor=2, conditioning_inputs_provided=True, time_embed_dim_multiplier=4) + model(clip, ts, tok, cond) + """ p, r = model.benchmark(clip, ts, tok, cond) p = {k: v / 1000000000 for k, v in p.items()} p = sorted(p.items(), key=operator.itemgetter(1)) @@ -389,4 +386,5 @@ if __name__ == '__main__': r = sorted(r.items(), key=operator.itemgetter(1)) print(r) print(sum([j[1] for j in r])) + """ diff --git a/codes/train.py b/codes/train.py index d249b3cd..980c6ffc 100644 --- a/codes/train.py +++ b/codes/train.py @@ -300,7 +300,7 @@ class Trainer: if __name__ == '__main__': parser = argparse.ArgumentParser() - parser.add_argument('-opt', type=str, help='Path to option YAML file.', default='../options/train_diffusion_tts.yml') + parser.add_argument('-opt', type=str, help='Path to option YAML file.', default='../options/train_clip_cond_to_voice.yml') parser.add_argument('--launcher', choices=['none', 'pytorch'], default='none', help='job launcher') parser.add_argument('--local_rank', type=int, default=0) args = parser.parse_args()