Remove logs

SUPIR/models/SUPIR_model.py

@@ -47,29 +47,18 @@ class SUPIRModel(DiffusionEngine):
 
     @torch.no_grad()
     def encode_first_stage_with_denoise(self, x, use_sample=True, is_stage1=False):
-        print('encode_first_stage_with_denoise 1')
         with torch.autocast("cuda", dtype=self.ae_dtype):
-            print('encode_first_stage_with_denoise 2')
             if is_stage1:
-                print('encode_first_stage_with_denoise 3')
                 h = self.first_stage_model.denoise_encoder_s1(x)
             else:
-                print('encode_first_stage_with_denoise 4')
                 h = self.first_stage_model.denoise_encoder(x)
-            print('encode_first_stage_with_denoise 5')
             moments = self.first_stage_model.quant_conv(h)
-            print('encode_first_stage_with_denoise 6')
             posterior = DiagonalGaussianDistribution(moments)
-            print('encode_first_stage_with_denoise 7')
             if use_sample:
-                print('encode_first_stage_with_denoise 8')
                 z = posterior.sample()
             else:
-                print('encode_first_stage_with_denoise 9')
                 z = posterior.mode()
-            print('encode_first_stage_with_denoise 10')
         z = self.scale_factor * z
-        print('encode_first_stage_with_denoise 11')
         return z
 
     @torch.no_grad()