diff --git a/codes/models/archs/srflow_orig/FlowActNorms.py b/codes/models/archs/srflow_orig/FlowActNorms.py
index e92dc642..d1e993ab 100644
--- a/codes/models/archs/srflow_orig/FlowActNorms.py
+++ b/codes/models/archs/srflow_orig/FlowActNorms.py
@@ -22,6 +22,7 @@ class _ActNorm(nn.Module):
         self.num_features = num_features
         self.scale = float(scale)
         self.inited = False
+        self.force_initialization = False
 
     def _check_input_dim(self, input):
         return NotImplemented
@@ -76,7 +77,7 @@ class _ActNorm(nn.Module):
         return input, logdet
 
     def forward(self, input, logdet=None, reverse=False, offset_mask=None, logs_offset=None, bias_offset=None):
-        if not self.inited:
+        if self.force_initialization or not self.inited:
             self.initialize_parameters(input)
         self._check_input_dim(input)
 
diff --git a/codes/models/archs/srflow_orig/SRFlowNet_arch.py b/codes/models/archs/srflow_orig/SRFlowNet_arch.py
index 5cb9d4b4..02ca4aac 100644
--- a/codes/models/archs/srflow_orig/SRFlowNet_arch.py
+++ b/codes/models/archs/srflow_orig/SRFlowNet_arch.py
@@ -31,6 +31,8 @@ class SRFlowNet(nn.Module):
         self.flowUpsamplerNet = \
             FlowUpsamplerNet((160, 160, 3), hidden_channels, K,
                              flow_coupling=opt['networks']['generator']['flow']['coupling'], opt=opt)
+        self.force_act_norm_init_until = opt_get(self.opt, ['networks', 'generator', 'flow', 'act_norm_start_step'])
+        self.act_norm_always_init = False
         self.i = 0
 
     def get_random_z(self, heat, seed=None, batch_size=1, lr_shape=None, device='cuda'):
@@ -52,6 +54,23 @@ class SRFlowNet(nn.Module):
             z = torch.normal(mean=0, std=heat, size=(batch_size, 3 * 8 * 8 * fac * fac, z_size, z_size))
         return z.to(device)
 
+    def update_for_step(self, step, experiments_path='.'):
+        if self.act_norm_always_init and step > self.force_act_norm_init_until:
+            set_act_norm_always_init = True
+            set_value = False
+            self.act_norm_always_init = False
+        elif not self.act_norm_always_init and step < self.force_act_norm_init_until:
+            set_act_norm_always_init = True
+            set_value = True
+            self.act_norm_always_init = True
+        else:
+            set_act_norm_always_init = False
+        if set_act_norm_always_init:
+            for m in self.modules():
+                from models.archs.srflow_orig.FlowActNorms import _ActNorm
+                if isinstance(m, _ActNorm):
+                    m.force_initialization = set_value
+
     def forward(self, gt=None, lr=None, z=None, eps_std=None, reverse=False, epses=None, reverse_with_grad=False,
                 lr_enc=None,
                 add_gt_noise=True, step=None, y_label=None):