config1.prototxt

# directory where saving the output files
workspace: "deephi/miniVggNet/pruning"

gpu: "0"

# the number of iterations to run in test phase.
# Max num =validation set / batch_size = 9000 / 50
test_iter: 180

# the accuracy name of the model output you care about
#acc_name: "top-5"
acc_name: "top-1"

model:   "deephi/miniVggNet/pruning/train_val.prototxt"

#first run
#weights: "deephi/miniVggNet/pruning/float.caffemodel"
weights: "deephi/miniVggNet/pruning/regular_rate_0/snapshots/_iter_40000.caffemodel"

# solver used for fine tuning
solver:  "deephi/miniVggNet/pruning/solver.prototxt"

# expected compression ratio: 0.1 means 10%
rate: 0.1 


#compression method used (only REGULAR is available)
pruner { method: REGULAR }