from easydict import EasyDict as edict

config = edict({
# 50 GB
'lmdb_map_size': 50 * (1024**3),
'nets': {
    'caffenet_1000': {
        'max_activation_dbname': 'data/caffenet_1000_max_act_lmdb',
        'spec_wdata': 'specs/caffenet_1000_val.prototxt',
        'spec_nodata': 'specs/caffenet_1000_deploy.prototxt',
        'model_param': 'caffe/models/bvlc_reference_caffenet/bvlc_reference_caffenet.caffemodel',
        'batch_size': 20,
        'num_examples': 1000,
        'mean_fname': 'caffe/data/ilsvrc12/imagenet_mean.binaryproto',
        'img_blob_name': 'data',
    }
}
})


@@ -1,8 +1,45 @@
+import caffe.proto.caffe_pb2 as cpb%0A%0A
 from eas
@@ -70,16 +70,169 @@
  edict%0A%0A
+relu_backward_types = edict(dict(cpb.ReLUParameter.BackpropType.items()))%0Arelu_backward_types_inv = %7B v: k for k, v in relu_backward_types.iteritems()%7D%0A%0A
 config =
@@ -327,65 +327,46 @@
    '
-max_activation_dbname': 'data/caffenet_1000_max_act_lmdb'
+relu_type': relu_backward_types.GUIDED
 ,%0A  
@@ -741,16 +741,187 @@
 'data',%0A
+        'blob_multipliers': %7B%0A            'conv1': 1.0,%0A            'conv2': 2.0,%0A            'conv3': 4.0,%0A            'conv4': 8.0,%0A            'conv5': 16.0,%0A        %7D%0A
     %7D%0A%7D%0A
@@ -922,10 +922,196 @@
   %7D%0A%7D%0A%7D)
+ 
 %0A%0A
+for net in config.nets.values():%0A    relu_type = relu_backward_types_inv%5Bnet.relu_type%5D%0A    net.max_activation_dbname = %5C%0A        'data/caffenet_1000_max_act_lmdb_%7B%7D'.format(relu_type)%0A

add config options for relu type