Implement RMSProp Solver

Implement RMSProp solver and cleaned up to adjust to new solver interface that uses
accumulated gradients and refactored regularization.

2 files changed, 30 insertions, 0 deletions

diff --git a/examples/mnist/lenet_solver_rmsprop.prototxt b/examples/mnist/lenet_solver_rmsprop.prototxt
new file mode 100644
index 00000000..74dadc51
--- /dev/null
+++ b/examples/mnist/lenet_solver_rmsprop.prototxt
@@ -0,0 +1,27 @@
+# The train/test net protocol buffer definition
+net: "examples/mnist/lenet_train_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: 0.0
+weight_decay: 0.0005
+# The learning rate policy
+lr_policy: "inv"
+gamma: 0.0001
+power: 0.75
+# Display every 100 iterations
+display: 100
+# The maximum number of iterations
+max_iter: 10000
+# snapshot intermediate results
+snapshot: 5000
+snapshot_prefix: "examples/mnist/lenet_rmsprop"
+# solver mode: CPU or GPU
+solver_mode: GPU
+solver_type: RMSPROP
+rms_decay: 0.98
diff --git a/examples/mnist/train_lenet_rmsprop.sh b/examples/mnist/train_lenet_rmsprop.sh
new file mode 100755
index 00000000..621cab23
--- /dev/null
+++ b/examples/mnist/train_lenet_rmsprop.sh
@@ -0,0 +1,3 @@
+#!/usr/bin/env sh
+
+./build/tools/caffe train --solver=examples/mnist/lenet_solver_rmsprop.prototxt