desco / configs /refcocoplus.yaml
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MODEL:
META_ARCHITECTURE: "GeneralizedVLRCNN"
WEIGHT: "swin_base_patch4_window12_384_22k.pth"
RPN_ONLY: True
RPN_ARCHITECTURE: "VLDYHEAD"
ATSS:
PRE_NMS_TOP_N: 3000
DETECTIONS_PER_IMG: 100
INFERENCE_TH: 0.0
SWINT:
VERSION: "fusion"
EMBED_DIM: 128
DEPTHS: (2, 2, 18, 2)
NUM_HEADS: (4, 8, 16, 32)
WINDOW_SIZE: 12
OUT_CHANNELS: (128, 256, 512, 1024)
DROP_PATH_RATE: 0.4
BACKBONE:
FUSION_VERSION: "v3"
CONV_BODY: "SWINT-FPN-RETINANET"
OUT_CHANNELS: 256
USE_CHECKPOINT: True
FREEZE_CONV_BODY_AT: -1
LANGUAGE_BACKBONE:
FREEZE: False
MODEL_TYPE: "roberta-fused-v2"
TOKENIZER_TYPE: "roberta-base"
LANG_DIM: 768
MASK_SPECIAL: False
USE_CHECKPOINT: 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
SCORE_AGG: "MEAN"
LOG_SCALE: 0.0
USE_CHECKPOINT: True
FUSE_CONFIG:
EARLY_FUSE_ON: False
TYPE: "NONE" # "MHA-B", "MHA-S", "FILM", "SCAN", "NONE"
USE_CLASSIFICATION_LOSS: False
USE_TOKEN_LOSS: False
USE_CONTRASTIVE_ALIGN_LOSS: False
CONTRASTIVE_HIDDEN_DIM: 64
USE_DOT_PRODUCT_TOKEN_LOSS: 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 for grounding model
DATASETS:
TRAIN: ("refcoco+_train", )
TEST: ("refcoco+_val",)
DISABLE_SHUFFLE: True
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)
FLIP_PROB_TRAIN: 0.0 # Important for refcoco esp
DATALOADER:
SIZE_DIVISIBILITY: 32
SOLVER:
OPTIMIZER: ADAMW
BASE_LR: 0.00001
LANG_LR: 0.00001
WEIGHT_DECAY: 0.0001
STEPS: (0.67, 0.89)
MAX_EPOCH: 20
IMS_PER_BATCH: 16
WARMUP_ITERS: 2000
WARMUP_FACTOR: 0.001
TEST_WITH_INFERENCE: True
FIND_UNUSED_PARAMETERS: False
USE_AMP: True
MODEL_EMA: 0.999
CLIP_GRADIENTS:
ENABLED: False
CLIP_TYPE: "full_model"
CLIP_VALUE: 1.0
NORM_TYPE: 2.0
TEST:
DURING_TRAINING: True
EVAL_TASK: "grounding"
IMS_PER_BATCH: 16