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example/ImageNet/ImageNet.conf

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+# Configuration for ImageNet  
+# Acknowledgement:
+#  Ref: http://www.cs.toronto.edu/~fritz/absps/imagenet.pdf
+#  The scheduling parameters is adapted from Caffe(http://caffe.berkeleyvision.org/)
+
+data = train
+iter = imgbin
+  image_list = "../../NameList.train"
+  image_bin  = "../../TRAIN.BIN"
+  image_root = "../../data/resize256/"
+  image_mean = "models/image_net_mean.bin"
+  rand_crop=1
+  rand_mirror=1
+iter = threadbuffer
+iter = end
+
+eval = test
+iter = imgbin
+  image_list = "../../NameList.test"
+  image_bin = "../../TEST.BIN"
+  image_root = "../../data/resize256/"
+  image_mean = "models/image_net_mean.bin"
+# no random crop and mirror in test
+iter = end
+
+netconfig=start
+layer[0->1] = conv
+  kernel_size = 11
+  stride = 4
+  nchannel = 96
+layer[1->2] = relu
+layer[2->3] = max_pooling
+  kernel_size = 3
+  stride = 2
+layer[3->4] = lrn
+  local_size = 5
+  alpha = 0.001
+  beta = 0.75
+  knorm = 1
+###############
+layer[4->5] = conv
+  ngroup = 2
+  nchannel = 256
+  kernel_size = 5
+  pad = 2
+layer[5->6] = relu
+layer[6->7] = max_pooling
+  kernel_size = 3
+  stride = 2
+layer[7->8] = lrn
+  local_size = 5
+  alpha = 0.001
+  beta = 0.75
+  knorm = 1
+#############
+layer[8->9] = conv
+  nchannel = 384
+  kernel_size = 3
+  pad = 1
+layer[9->10]= relu
+layer[10->11] = conv
+  nchannel = 384
+  ngroup = 2
+  kernel_size = 3
+  pad = 1
+layer[11->12] = relu
+layer[12->13] = conv
+  nchannel = 256
+  ngroup = 2
+  kernel_size = 3
+  pad = 1
+  init_bias = 1.0
+layer[13->14] = relu
+layer[14->15] = max_pooling
+  kernel_size = 3
+  stride = 2
+layer[15->16] = flatten
+layer[16->17] = fullc
+  nhidden = 4096
+  init_sigma = 0.005
+  init_bias = 1.0
+layer[17->18] = relu
+layer[18->18] = dropout
+  threshold = 0.5
+layer[18->19] = fullc
+  nhidden = 4096
+  init_sigma = 0.005
+  init_bias = 1.0
+layer[19->20] = relu
+layer[20->20] = dropout
+  threshold = 0.5
+layer[20->21] = fullc
+  nhidden = 1000
+layer[21->21] = softmax
+netconfig=end
+
+# evaluation metric
+metric = error
+metric = rec@1
+metric = rec@5
+
+max_round = 45
+num_round = 45
+
+# input shape not including batch
+input_shape = 3,227,227
+
+batch_size = 256
+
+# global parameters in any sectiion outside netconfig, and iter
+momentum = 0.9
+wmat:lr  = 0.01
+wmat:wd  = 0.0005
+
+bias:wd  = 0.000
+bias:lr  = 0.02
+
+# all the learning rate schedule starts with lr
+lr:schedule = expdecay
+lr:gamma = 0.1
+lr:step = 100000
+
+save_model=1
+model_dir=models
+
+# random config
+random_type = gaussian
+init_sigma = 0.01
+
+# new line