openpose_train/experimental_models/100_135AlmostSameBatchAllGPUs/training_results/pose_solver.prototxt at master · CMU-Perceptual-Computing-Lab/openpose_train · GitHub

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# Net Path Location
net: "pose_training.prototxt"
# Testing
# 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
# Solver Parameters - Base Learning Rate, Momentum and Weight Decay
type:"Adam"
base_lr: 0.000030
momentum: 0.9
momentum2: 0.999
weight_decay: 0.0005
# lr_policy: "step"   # The learning rate policy
lr_policy: "multistep"   # The learning rate policy
# gamma: 0.333
gamma: 0.5
# stepsize: 136106    # Previously: 29166 68053 136106 (previous one)
# stepvalue: 10000
# stepvalue: 20000
# stepvalue: 30000
# stepvalue: 40000
# stepvalue: 50000
# stepvalue: 60000
# stepvalue: 70000
# stepvalue: 80000
# stepvalue: 90000
# stepvalue: 100000
stepvalue: 200000
stepvalue: 300000
stepvalue: 360000
stepvalue: 420000
stepvalue: 480000
stepvalue: 540000
stepvalue: 600000
stepvalue: 700000
stepvalue: 800000
stepvalue: 900000
# Output - Model Saving and Loss Output
display: 20 # Previously: 5   # Display every X iterations
max_iter: 1000000   # Maximum number of iterations, previously: 600000
snapshot: 2000   # Snapshot intermediate results, previously: 2000. Mine: 10000?
snapshot_prefix: "/home/gines/devel/openpose_train/training_results/pose/model/pose"
solver_mode: GPU   # CPU or GPU