diff --git a/.DS_Store b/.DS_Store
index 22942f911..fad07c5b4 100644
Binary files a/.DS_Store and b/.DS_Store differ
diff --git a/audio_data.py b/audio_data.py
index e79ca35be..77272a8a9 100644
--- a/audio_data.py
+++ b/audio_data.py
@@ -185,7 +185,7 @@ def __init__(self, *args, **kwargs):
         self.conditioning_channels = conditioning_channels
 
         print("Conditioning captures time scales ranging from " + str(self.min_conditioning_breadth) + " to " \
-              + str(self.min_conditioning_breadth * self.conditioning_channels) + " seconds")
+              + str(self.min_conditioning_breadth * self.conditioning_channels // 2) + " seconds")
 
         super().__init__(*args, **kwargs)
 
@@ -199,8 +199,10 @@ def conditioning(self, file_index, position_in_file, item_length):
         x = np.linspace(phase_start, phase_start + phase_length, num=conditioning_count)
         conditioning = np.zeros((self.conditioning_channels, conditioning_count))
 
-        for c in range(self.conditioning_channels):
-            conditioning[c, :] = np.cos(x * ((c + 1) / self.conditioning_channels))
+        frequency_count = self.conditioning_channels // 2
+        for c in range(frequency_count):
+            conditioning[2 * c, :] = np.cos(x * ((c + 1) / frequency_count))
+            conditioning[2 * c + 1, :] = np.sin(x * ((c + 1) / frequency_count))
 
         file_encoding = np.zeros((len(self.files), conditioning_count))
         file_encoding[file_index, :] = 1.
diff --git a/wavenet_model.py b/wavenet_model.py
index 0d033326e..eacfae25a 100644
--- a/wavenet_model.py
+++ b/wavenet_model.py
@@ -383,7 +383,7 @@ def __init__(self, args_dict):
             self.file_encoding_layers.append(nn.Conv1d(in_channels=self.file_encoding_channels[i],
                                                        out_channels=self.file_encoding_channels[i + 1],
                                                        kernel_size=1,
-                                                       bias=False))
+                                                       bias=self.use_bias))
 
         self.conditioning_layers = nn.ModuleList()
         self.file_conditioning_cross_layers = nn.ModuleList()
@@ -396,7 +396,7 @@ def __init__(self, args_dict):
                 self.file_conditioning_cross_layers.append(nn.Conv1d(in_channels=self.file_encoding_channels[-1],
                                                                      out_channels=self.conditioning_channels[i],
                                                                      kernel_size=1,
-                                                                     bias=False))
+                                                                     bias=self.use_bias))
 
     def activation_unit_init(self):
         super().activation_unit_init()