Added Multistep, Poly and Sigmoid learning rate decay policies

Conflicts:
	include/caffe/solver.hpp
	src/caffe/proto/caffe.proto
	src/caffe/solver.cpp

2 files changed, 61 insertions, 0 deletions

diff --git a/examples/lenet/lenet_multistep_solver.prototxt b/examples/lenet/lenet_multistep_solver.prototxt
new file mode 100644
index 00000000..fadd7c90
--- /dev/null
+++ b/examples/lenet/lenet_multistep_solver.prototxt
@@ -0,0 +1,33 @@
+# The training protocol buffer definition
+train_net: "lenet_train.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: "multistep"
+gamma: 0.9
+stepvalue: 1000
+stepvalue: 2000
+stepvalue: 2500
+stepvalue: 3000
+stepvalue: 3500
+stepvalue: 4000
+# Display every 100 iterations
+display: 100
+# 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
+device_id: 1
diff --git a/examples/lenet/lenet_stepearly_solver.prototxt b/examples/lenet/lenet_stepearly_solver.prototxt
new file mode 100644
index 00000000..efc6a335
--- /dev/null
+++ b/examples/lenet/lenet_stepearly_solver.prototxt
@@ -0,0 +1,28 @@
+# The training protocol buffer definition
+train_net: "lenet_train.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: "stepearly"
+gamma: 0.9
+stepearly: 1
+# Display every 100 iterations
+display: 100
+# 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
+device_id: 1