NAME: Webui # Experiment name
DEBUG: False # Debug mode
ACCELERATOR: 'cpu' # Devices optioncal: “cpu”, “gpu”, “tpu”, “ipu”, “hpu”, “mps, “auto”
DEVICE: [0] # Index of gpus eg. [0] or [0,1,2,3]

# Training configuration
TRAIN:
  #---------------------------------
  STAGE: lm_instruct
  DATASETS: ['humanml3d'] # Training datasets
  NUM_WORKERS: 32 # Number of workers
  BATCH_SIZE: 16 # Size of batches
  START_EPOCH: 0 # Start epochMMOTIONENCODER
  END_EPOCH: 99999 # End epoch
  ABLATION:
    pkeep: 0.5
  OPTIM:
    TYPE: AdamW # Optimizer type
    LR: 2e-4 # Learning rate
    WEIGHT_DECAY: 0.0
    LR_SCHEDULER: [100, 200, 300, 400]
    GAMMA: 0.8

# Evaluating Configuration
EVAL:
  DATASETS: ['humanml3d'] # Evaluating datasets
  BATCH_SIZE: 32 # Evaluating Batch size
  SPLIT: test

# Test Configuration
TEST:
  CHECKPOINTS: checkpoints/MotionGPT-base/motiongpt_s3_h3d.ckpt
  DATASETS: ['humanml3d'] # training datasets
  SPLIT: test
  BATCH_SIZE: 32 # training Batch size
  MEAN: False
  NUM_SAMPLES: 1
  FACT: 1

# Datasets Configuration
DATASET:
  JOINT_TYPE: 'humanml3d' # join type
  CODE_PATH: 'VQBEST'
METRIC:
  TYPE: ['TM2TMetrics']
# Losses Configuration
LOSS:
  TYPE: t2mgpt # Losses type
  LAMBDA_FEATURE: 1.0
  LAMBDA_VELOCITY: 0.5
  LAMBDA_COMMIT: 0.02
  LAMBDA_CLS: 1.0
  LAMBDA_M2T2M: 1.0
  LAMBDA_T2M2T: 10.0
  ABLATION:
    RECONS_LOSS: 'l1_smooth'

# Model Configuration
model:
  target: mGPT.models.mgpt.MotionGPT
  params:
    condition: 'text'
    task: 't2m'
    lm: ${lm.default}
    motion_vae: ${vq.default}

# Logger configuration
LOGGER:
  LOG_EVERY_STEPS: 5
  VAL_EVERY_STEPS: 10
  TENSORBOARD: True
  wandb:
    params:
      project: null