X-Git-Url: https://git.ti.com/gitweb?p=jacinto-ai%2Fcaffe-jacinto.git;a=blobdiff_plain;f=data%2Flenet_solver.prototxt;h=d0edc0f0c874530d03ca36721c9026b254dc5b6f;hp=d58255b9e31368c87b0445722a51228e36f347db;hb=ca3e042863e59e9a8a8edd7e78ffe9b2431aea8f;hpb=524e0956ef58d0f1fac0bf302de341c9eff882e0;ds=sidebyside

diff --git a/data/lenet_solver.prototxt b/data/lenet_solver.prototxt
index d58255b9..d0edc0f0 100644
--- a/data/lenet_solver.prototxt
+++ b/data/lenet_solver.prototxt
@@ -1,12 +1,27 @@
-train_net: "data/lenet.prototxt"
-test_net: "data/lenet_test.prototxt"
+# The training protocol buffer definition
+train_net: "lenet.prototxt"
+# The testing protocol buffer definition
+test_net: "lenet_test.prototxt"
+# test_iter specifies how many forward passes the test should carry out.
+# In the case of MNIST, we have test batch size 100 and 100 test iterations,
+# covering the full 10,000 testing images.
+test_iter: 100
+# Carry out testing every 500 training iterations.
+test_interval: 500
+# The base learning rate, momentum and the weight decay of the network.
 base_lr: 0.01
+momentum: 0.9
+weight_decay: 0.0005
+# The learning rate policy
 lr_policy: "inv"
 gamma: 0.0001
 power: 0.75
+# Display every 100 iterations
 display: 100
-max_iter: 5000
-momentum: 0.9
-weight_decay: 0.0005
-test_iter: 100
-test_interval: 500
\ No newline at end of file
+# The maximum number of iterations
+max_iter: 10000
+# snapshot intermediate results
+snapshot: 5000
+snapshot_prefix: "lenet"
+# solver mode: 0 for CPU and 1 for GPU
+solver_mode: 1