config.yaml

TRAIN:
  ENABLE: True
  DATASET: kinetics
  BATCH_SIZE: 8
  EVAL_PERIOD: 10
  CHECKPOINT_PERIOD: 10
  AUTO_RESUME: True
DATA:
  USE_OFFSET_SAMPLING: True
  DECODING_BACKEND: decord
  NUM_FRAMES: 16
  SAMPLING_RATE: 4
  TRAIN_JITTER_SCALES: [256, 320]
  TRAIN_CROP_SIZE: 224
  TEST_CROP_SIZE: 256
  INPUT_CHANNEL_NUM: [3]
  # PATH_TO_DATA_DIR: path-to-imagenet-dir
  TRAIN_JITTER_SCALES_RELATIVE: [0.08, 1.0]
  TRAIN_JITTER_ASPECT_RELATIVE: [0.75, 1.3333]
UNIFORMER:
  EMBED_DIM: [64, 128, 320, 512]
  DEPTH: [3, 4, 8, 3]
  HEAD_DIM: 64
  MLP_RATIO: 4
  DROPOUT_RATE: 0
  ATTENTION_DROPOUT_RATE: 0
  DROP_DEPTH_RATE: 0.1
  SPLIT: False
  PRETRAIN_NAME: 'uniformer_small_in1k'
AUG:
  NUM_SAMPLE: 2
  ENABLE: True
  COLOR_JITTER: 0.4
  AA_TYPE: rand-m7-n4-mstd0.5-inc1
  INTERPOLATION: bicubic
  RE_PROB: 0.25
  RE_MODE: pixel
  RE_COUNT: 1
  RE_SPLIT: False
MIXUP:
  ENABLE: True
  ALPHA: 0.8
  CUTMIX_ALPHA: 1.0
  PROB: 1.0
  SWITCH_PROB: 0.5
  LABEL_SMOOTH_VALUE: 0.1
BN:
  USE_PRECISE_STATS: False
  NUM_BATCHES_PRECISE: 200
SOLVER:
  ZERO_WD_1D_PARAM: True
  BASE_LR_SCALE_NUM_SHARDS: True
  BASE_LR: 0.0001
  COSINE_AFTER_WARMUP: True
  COSINE_END_LR: 1e-6
  WARMUP_START_LR: 1e-6
  WARMUP_EPOCHS: 30.0
  LR_POLICY: cosine
  MAX_EPOCH: 200
  MOMENTUM: 0.9
  WEIGHT_DECAY: 0.05
  OPTIMIZING_METHOD: adamw
  COSINE_AFTER_WARMUP: True
MODEL:
  NUM_CLASSES: 400
  ARCH: uniformer
  MODEL_NAME: Uniformer
  LOSS_FUNC: soft_cross_entropy
  DROPOUT_RATE: 0.5
TEST:
  ENABLE: True
  DATASET: kinetics
  BATCH_SIZE: 64
  NUM_SPATIAL_CROPS: 1
DATA_LOADER:
  NUM_WORKERS: 8
  PIN_MEMORY: True
TENSORBOARD:
  ENABLE: True
NUM_GPUS: 8
NUM_SHARDS: 1
RNG_SEED: 0
OUTPUT_DIR: .