diff --git a/codes/models/archs/SwitchedResidualGenerator_arch.py b/codes/models/archs/SwitchedResidualGenerator_arch.py
index 76feccd2..6aa44df2 100644
--- a/codes/models/archs/SwitchedResidualGenerator_arch.py
+++ b/codes/models/archs/SwitchedResidualGenerator_arch.py
@@ -100,7 +100,9 @@ class SwitchComputer(nn.Module):
 
 
 class ConfigurableSwitchedResidualGenerator(nn.Module):
-    def __init__(self, switch_filters, switch_reductions, switch_processing_layers, trans_counts, trans_kernel_sizes, trans_layers, trans_filters_mid, initial_temp=20, final_temperature_step=50000):
+    def __init__(self, switch_filters, switch_reductions, switch_processing_layers, trans_counts, trans_kernel_sizes,
+                 trans_layers, trans_filters_mid, initial_temp=20, final_temperature_step=50000, heightened_temp_min=1,
+                 heightened_final_step=50000):
         super(ConfigurableSwitchedResidualGenerator, self).__init__()
         switches = []
         for filters, sw_reduce, sw_proc, trans_count, kernel, layers, mid_filters in zip(switch_filters, switch_reductions, switch_processing_layers, trans_counts, trans_kernel_sizes, trans_layers, trans_filters_mid):
@@ -112,6 +114,8 @@ class ConfigurableSwitchedResidualGenerator(nn.Module):
         self.transformation_counts = trans_counts
         self.init_temperature = initial_temp
         self.final_temperature_step = final_temperature_step
+        self.heightened_temp_min = heightened_temp_min
+        self.heightened_final_step = heightened_final_step
         self.attentions = None
 
     def forward(self, x):
@@ -128,8 +132,14 @@ class ConfigurableSwitchedResidualGenerator(nn.Module):
     def update_for_step(self, step, experiments_path='.'):
         if self.attentions:
             temp = max(1, int(self.init_temperature * (self.final_temperature_step - step) / self.final_temperature_step))
+            if temp == 1:
+                # Enter the linear function regime between self.final_temperature_step and self.heightened_final_step
+                h_steps_total = self.heightened_final_step - self.final_temperature_step
+                h_steps_current = min(step - self.final_temperature_step, h_steps_total)
+                h_gap = 1 - self.heightened_temp_min
+                temp = 1 - h_gap * h_steps_current / h_steps_total
             self.set_temperature(temp)
-            if step % 250 == 0:
+            if step % 50 == 0:
                 [save_attention_to_image(experiments_path, self.attentions[i], self.transformation_counts[i], step, "a%i" % (i+1,), l_mult=float(self.transformation_counts[i]/4)) for i in range(len(self.switches))]
 
     def get_debug_values(self, step):
diff --git a/codes/models/networks.py b/codes/models/networks.py
index e5cccbcf..abcc98cd 100644
--- a/codes/models/networks.py
+++ b/codes/models/networks.py
@@ -67,7 +67,8 @@ def define_G(opt, net_key='network_G'):
                                                                       switch_processing_layers=opt_net['switch_processing_layers'], trans_counts=opt_net['trans_counts'],
                                                                       trans_kernel_sizes=opt_net['trans_kernel_sizes'], trans_layers=opt_net['trans_layers'],
                                                                       trans_filters_mid=opt_net['trans_filters_mid'],
-                                                                      initial_temp=opt_net['temperature'], final_temperature_step=opt_net['temperature_final_step'])
+                                                                      initial_temp=opt_net['temperature'], final_temperature_step=opt_net['temperature_final_step'],
+                                                                      heightened_temp_min=opt_net['heightened_temp_min'], heightened_final_step=opt_net['heightened_final_step'])
 
     # image corruption
     elif which_model == 'HighToLowResNet':