Create network with 1024 instead of 4096 FC outputs
Drop size of both FC layers to 256
Num output = 2
Draw layer sizes on edges for convolution, inner product and data layers
Horizontal plot with slightly more compact labels
Drop size of both FC layers to 64
Create network with drop fc7, small fc6
Ignore pycharm files
Created network with drop fc7, fc6 size 16
Created network with many fewer image maps per conv layer

Most map counts divided by 16 except for first conv layer, divided by 4

Also dropped fc7 and much smaller fc6 (16 vs 4096)
Created network with double number of maps/outputs as previous
Create network with double map sizes
Create network with half map sizes from AlexNet

* First conv layer map size is the same as AlexNet
* fc7 missing
* fc6 size is half AlexNet
Use dict instead of list for clarity
Upload log to s3
Web page to auto refresh latest caffe image
New net: conv5 half maps, fc6 size=64, no fc7
New net: half conv4
New Net: half conv3
Rename remote log file