[utils] added docstrings

bob/learn/pytorch/architectures/utils.py

@@ -3,14 +3,30 @@ import torch.nn as nn
 
 
 def make_conv_layers(cfg, input_c = 3):
-    layers = []
-    in_channels = input_c
-    for v in cfg:
-        if v == 'M':
-            layers += [nn.MaxPool2d(kernel_size=2, stride=2)]
-        else:
-            conv2d = nn.Conv2d(in_channels, v, kernel_size=3, padding=1)
-            layers += [conv2d, nn.ReLU()]
-            in_channels = v
-    return nn.Sequential(*layers)
+  """ builds the convolution / max pool layers
+
+  The network architecture is provided as a list, containing the
+  number of feature maps, or a 'M' for a MaxPooling layer.
+
+  Example for Casia-Net: 
+  [32, 64, 'M', 64, 128, 'M', 96, 192, 'M', 128, 256, 'M', 160, 320]
+
+  Parameters
+  ----------
+  cfg: list
+    Configuration for the network (see above)
+  input_c: int
+    The number of channels in the input (1 -> gray, 3 -> rgb)
+
+  """
+  layers = []
+  in_channels = input_c
+  for v in cfg:
+    if v == 'M':
+      layers += [nn.MaxPool2d(kernel_size=2, stride=2)]
+    else:
+      conv2d = nn.Conv2d(in_channels, v, kernel_size=3, padding=1)
+      layers += [conv2d, nn.ReLU()]
+      in_channels = v
+  return nn.Sequential(*layers)