MODEL:
  META_ARCHITECTURE: "GeneralizedVLRCNN"
  WEIGHT: "swin_tiny_patch4_window7_224.pth"
  RPN_ONLY: True
  RPN_ARCHITECTURE: "VLDYHEAD"

  BACKBONE:
    CONV_BODY: "SWINT-FPN-RETINANET"
    OUT_CHANNELS: 256
    FREEZE_CONV_BODY_AT: -1

  LANGUAGE_BACKBONE:
    FREEZE: False
    MODEL_TYPE: "bert-base-uncased" # "roberta-base", "clip"
    MASK_SPECIAL: False

  RPN:
    USE_FPN: True
    ANCHOR_SIZES: (64, 128, 256, 512, 1024)
    ANCHOR_STRIDE: (8, 16, 32, 64, 128)
    ASPECT_RATIOS: (1.0,)
    SCALES_PER_OCTAVE: 1

  DYHEAD:
    CHANNELS: 256
    NUM_CONVS: 6
    USE_GN: True
    USE_DYRELU: True
    USE_DFCONV: True
    USE_DYFUSE: True
    TOPK: 9 # topk for selecting candidate positive samples from each level
    SCORE_AGG: "MEAN"
    LOG_SCALE: 0.0

    FUSE_CONFIG:
      EARLY_FUSE_ON: True
      TYPE: "MHA-B"
      USE_CLASSIFICATION_LOSS: False
      USE_TOKEN_LOSS: False
      USE_CONTRASTIVE_ALIGN_LOSS: False
      CONTRASTIVE_HIDDEN_DIM: 64
      USE_DOT_PRODUCT_TOKEN_LOSS: True
      USE_FUSED_FEATURES_DOT_PRODUCT: True
      USE_LAYER_SCALE: True
      CLAMP_MIN_FOR_UNDERFLOW: True
      CLAMP_MAX_FOR_OVERFLOW: True
      CLAMP_BERTATTN_MIN_FOR_UNDERFLOW: True
      CLAMP_BERTATTN_MAX_FOR_OVERFLOW: True
      CLAMP_DOT_PRODUCT: True
           
    USE_CHECKPOINT: True

TEST:
  DURING_TRAINING: False
  IMS_PER_BATCH: 64

# use for grounding model
DATASETS:
  TRAIN: ("object365_dt_train", )
  TEST: ("coco_2017_val", )
  DISABLE_SHUFFLE: False
  ADD_DET_PROMPT: False
  RANDOM_SAMPLE_NEG: 85
  CONTROL_PROB: (0.0, 0.0, 0.5, 0.0)

  DESCRIPTION_FILE: "DATASET/Objects365/descriptions/o365.description.v1.json"

  SEPARATION_TOKENS: ". "

INPUT:
  PIXEL_MEAN: [ 103.530, 116.280, 123.675 ]
  PIXEL_STD: [ 57.375, 57.120, 58.395 ]
  MIN_SIZE_TRAIN: 800
  MAX_SIZE_TRAIN: 1333
  MIN_SIZE_TEST: 800
  MAX_SIZE_TEST: 1333

AUGMENT:
  MULT_MIN_SIZE_TRAIN: (480,560,640,720,800)

DATALOADER:
  SIZE_DIVISIBILITY: 32

SOLVER:
  OPTIMIZER: ADAMW
  BASE_LR: 0.0001
  LANG_LR: 0.00001
  WEIGHT_DECAY: 0.0001
  STEPS: (0.67, 0.89)
  MAX_EPOCH: 30
  IMS_PER_BATCH: 64
  WARMUP_ITERS: 2000
  WARMUP_FACTOR: 0.001
  USE_AMP: True
  MODEL_EMA: 0.999
  FIND_UNUSED_PARAMETERS: False

  CLIP_GRADIENTS:
    ENABLED: True
    CLIP_TYPE: "full_model"
    CLIP_VALUE: 1.0
    NORM_TYPE: 2.0