Resolve "No need to have macOS builds" + updated documentation

Closes #1 (closed)

Started updated the documentation

bob/learn/pytorch/architectures/CASIANet.py

 import torch
-import torch.nn as nn
-import torch.nn.functional as F
-
 from .utils import make_conv_layers
 
 CASIA_CONFIG = [32, 64, 'M', 64, 128, 'M', 96, 192, 'M', 128, 256, 'M', 160, 320] 
 
-class CASIANet(nn.Module):
+class CASIANet(torch.nn.Module):
   """ The class defining the CASIA-Net CNN model.
 
-  This class implements the CNN described here:
-
-  @Misc{yi-arxiv-2014,
-    Author         = {Yi, D. and Lei, Z. and Liao, S. and Li, S.Z.},
-    Title          = {Learning {F}ace {R}epresentation {F}rom {S}cratch},
-    eprint         = {arXiv:1411.7923},
-    year           = 2014
-  }
+  This class implements the CNN described in:
+  "Learning Face Representation From Scratch", D. Yi, Z. Lei, S. Liao and S.z. Li, 2014
 
   Attributes
   ----------
@@ -49,8 +40,8 @@ class CASIANet(nn.Module):
     self.num_classes = num_cls
     self.drop_rate = float(drop_rate)
     self.conv = make_conv_layers(CASIA_CONFIG)
-    self.avgpool = nn.AvgPool2d(8)
-    self.classifier = nn.Linear(320, self.num_classes)
+    self.avgpool = torch.nn.AvgPool2d(8)
+    self.classifier = torch.nn.Linear(320, self.num_classes)
 
   def forward(self, x):
     """ Propagate data through the network
@@ -70,6 +61,6 @@ class CASIANet(nn.Module):
     x = self.conv(x)
     x = self.avgpool(x)
     x = x.view(x.size(0), -1)
-    x = F.dropout(x, p = self.drop_rate, training=self.training)
+    x = torch.nn.functional.dropout(x, p = self.drop_rate, training=self.training)
     out = self.classifier(x)
     return out, x # x for feature