@@ -847,8 +847,6 @@ def do_sample(
847847 force_cond_zero_embeddings = force_cond_zero_embeddings ,
848848 )
849849 unload_module_gpu (model .conditioner )
850- print ("anchor_after_condition {}" .format (torch .cuda .memory_reserved () / (1024 ** 3 )))
851- # torch.cuda.empty_cache()
852850
853851 for k in c :
854852 if not k == "crossattn" :
@@ -893,8 +891,6 @@ def denoiser(input, sigma, c):
893891 samples_z = sampler (denoiser , randn , cond = c , uc = uc )
894892 unload_module_gpu (model .model )
895893 unload_module_gpu (model .denoiser )
896- print ("anchor_after_denoiser {}" .format (torch .cuda .memory_reserved () / (1024 ** 3 )))
897- # torch.cuda.empty_cache()
898894 load_module_gpu (model .first_stage_model )
899895 model .en_and_decode_n_samples_a_time = decoding_t
900896 if isinstance (model .first_stage_model .decoder , VideoDecoder ):
@@ -910,7 +906,6 @@ def denoiser(input, sigma, c):
910906
911907 if return_latents :
912908 return samples , samples_z
913- # torch.cuda.empty_cache()
914909 return samples
915910
916911
@@ -950,7 +945,6 @@ def prepare_sampling_(
950945 force_uc_zero_embeddings = force_uc_zero_embeddings ,
951946 force_cond_zero_embeddings = force_cond_zero_embeddings ,
952947 )
953- print ("dense_after_condition {}" .format (torch .cuda .memory_reserved () / (1024 ** 3 )))
954948 for k in c :
955949 if not k == "crossattn" :
956950 c [k ], uc [k ] = map (
@@ -1022,7 +1016,6 @@ def denoiser(input, sigma, c):
10221016 uc ,
10231017 gamma ,
10241018 )
1025- print ("dense_after_sampling {}" .format (torch .cuda .memory_reserved () / (1024 ** 3 )))
10261019 return samples_z
10271020
10281021
0 commit comments