OpenMotionLab/MotionGPT

1NAME: Webui # Experiment name2DEBUG: False # Debug mode3ACCELERATOR: 'cpu' # Devices optioncal: “cpu”, “gpu”, “tpu”, “ipu”, “hpu”, “mps, “auto”4DEVICE: [0] # Index of gpus eg. [0] or [0,1,2,3]5 6# Training configuration7TRAIN:8  #---------------------------------9  STAGE: lm_instruct10  DATASETS: ['humanml3d'] # Training datasets11  NUM_WORKERS: 32 # Number of workers12  BATCH_SIZE: 16 # Size of batches13  START_EPOCH: 0 # Start epochMMOTIONENCODER14  END_EPOCH: 99999 # End epoch15  ABLATION:16    pkeep: 0.517  OPTIM:18    TYPE: AdamW # Optimizer type19    LR: 2e-4 # Learning rate20    WEIGHT_DECAY: 0.021    LR_SCHEDULER: [100, 200, 300, 400]22    GAMMA: 0.823 24# Evaluating Configuration25EVAL:26  DATASETS: ['humanml3d'] # Evaluating datasets27  BATCH_SIZE: 32 # Evaluating Batch size28  SPLIT: test29 30# Test Configuration31TEST:32  CHECKPOINTS: checkpoints/MotionGPT-base/motiongpt_s3_h3d.ckpt33  DATASETS: ['humanml3d'] # training datasets34  SPLIT: test35  BATCH_SIZE: 32 # training Batch size36  MEAN: False37  NUM_SAMPLES: 138  FACT: 139 40# Datasets Configuration41DATASET:42  JOINT_TYPE: 'humanml3d' # join type43  CODE_PATH: 'VQBEST'44METRIC:45  TYPE: ['TM2TMetrics']46# Losses Configuration47LOSS:48  TYPE: t2mgpt # Losses type49  LAMBDA_FEATURE: 1.050  LAMBDA_VELOCITY: 0.551  LAMBDA_COMMIT: 0.0252  LAMBDA_CLS: 1.053  LAMBDA_M2T2M: 1.054  LAMBDA_T2M2T: 10.055  ABLATION:56    RECONS_LOSS: 'l1_smooth'57 58# Model Configuration59model:60  target: mGPT.models.mgpt.MotionGPT61  params:62    condition: 'text'63    task: 't2m'64    lm: ${lm.default}65    motion_vae: ${vq.default}66 67# Logger configuration68LOGGER:69  LOG_EVERY_STEPS: 570  VAL_EVERY_STEPS: 1071  TENSORBOARD: True72  wandb:73    params:74      project: null75