config_files/self_play_qgen_vdst_oracle_vilbert.yaml [16:82]:
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  dataroot: "data"
  features_path: 
    qgen:
      train: "data/rcnn/from_rcnn/"
      valid: "data/rcnn/from_rcnn/"
      test: "data/rcnn/from_rcnn/"
    oracle:
      train: "data/vilbert/coco/features_100/COCO_trainval_resnext152_faster_rcnn_genome.lmdb"
      valid: "data/vilbert/coco/features_100/COCO_trainval_resnext152_faster_rcnn_genome.lmdb"
      test: "data/vilbert/coco/features_100/COCO_trainval_resnext152_faster_rcnn_genome.lmdb"
  features_path_gt: 
    "train": "data/rcnn/from_gt_gw_xyxy_scale/"
    "valid": "data/rcnn/from_gt_gw_xyxy_scale/"
    "test": "data/rcnn/from_gt_gw_xyxy_scale/"


model:
  qgen:
    pretrained_path: "ckpt/qgen_vdst-sd0/best.pth"
    wrd_embed_size: 512
    obj_feat_size: 2056
    lstm_hidden_size: 512
    num_bboxs: 36
    num_glimpses: 2

  oracle:
    pretrained_path: "ckpt/oracle_vilbert-sd0/epoch-3.pth"
    spatial_size: 5
    num_cats: 100              # Number of catergories: 91 (actually)
    cat_embed_size: 512
    cat_pad_id: 0              # 1-91 is used
    mlp_hidden: 512
    num_classes: 3
    dropout_prob: 0.1
    fusion_method: "mul"
    vilbert_config:
      pretrained_path: "vilbert-pretrained-model/multi_task_model.bin"
      attention_probs_dropout_prob: 0.1
      hidden_act: "gelu"
      hidden_dropout_prob: 0.1
      hidden_size: 768
      initializer_range: 0.02
      intermediate_size: 3072
      max_position_embeddings: 512
      num_attention_heads: 12
      num_hidden_layers: 12
      type_vocab_size: 2
      vocab_size: 30522
      v_feature_size: 2048
      v_target_size: 1601
      v_hidden_size: 1024
      v_num_hidden_layers: 6
      v_num_attention_heads: 8
      v_intermediate_size: 1024
      bi_hidden_size: 1024
      bi_num_attention_heads: 8
      bi_intermediate_size: 1024
      bi_attention_type: 1
      v_attention_probs_dropout_prob: 0.1
      v_hidden_act: "gelu"
      v_hidden_dropout_prob: 0.1
      v_initializer_range: 0.02
      v_biattention_id: [0, 1, 2, 3, 4, 5]
      t_biattention_id: [6, 7, 8, 9, 10, 11]
      pooling_method: "mul"

  guesser:
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config_files/self_play_qgen_vdst_oracle_vilbert_guesser_vilbert.yaml [16:82]:
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  dataroot: "data"
  features_path: 
    qgen:
      train: "data/rcnn/from_rcnn/"
      valid: "data/rcnn/from_rcnn/"
      test: "data/rcnn/from_rcnn/"
    oracle:
      train: "data/vilbert/coco/features_100/COCO_trainval_resnext152_faster_rcnn_genome.lmdb"
      valid: "data/vilbert/coco/features_100/COCO_trainval_resnext152_faster_rcnn_genome.lmdb"
      test: "data/vilbert/coco/features_100/COCO_trainval_resnext152_faster_rcnn_genome.lmdb"
  features_path_gt: 
    "train": "data/rcnn/from_gt_gw_xyxy_scale/"
    "valid": "data/rcnn/from_gt_gw_xyxy_scale/"
    "test": "data/rcnn/from_gt_gw_xyxy_scale/"


model:
  qgen:
    pretrained_path: "ckpt/qgen_vdst-sd0/best.pth"
    wrd_embed_size: 512
    obj_feat_size: 2056
    lstm_hidden_size: 512
    num_bboxs: 36
    num_glimpses: 2

  oracle:
    pretrained_path: "ckpt/oracle_vilbert-sd0/epoch-3.pth"
    spatial_size: 5
    num_cats: 100              # Number of catergories: 91 (actually)
    cat_embed_size: 512
    cat_pad_id: 0              # 1-91 is used
    mlp_hidden: 512
    num_classes: 3
    dropout_prob: 0.1
    fusion_method: "mul"
    vilbert_config:
      pretrained_path: "vilbert-pretrained-model/multi_task_model.bin"
      attention_probs_dropout_prob: 0.1
      hidden_act: "gelu"
      hidden_dropout_prob: 0.1
      hidden_size: 768
      initializer_range: 0.02
      intermediate_size: 3072
      max_position_embeddings: 512
      num_attention_heads: 12
      num_hidden_layers: 12
      type_vocab_size: 2
      vocab_size: 30522
      v_feature_size: 2048
      v_target_size: 1601
      v_hidden_size: 1024
      v_num_hidden_layers: 6
      v_num_attention_heads: 8
      v_intermediate_size: 1024
      bi_hidden_size: 1024
      bi_num_attention_heads: 8
      bi_intermediate_size: 1024
      bi_attention_type: 1
      v_attention_probs_dropout_prob: 0.1
      v_hidden_act: "gelu"
      v_hidden_dropout_prob: 0.1
      v_initializer_range: 0.02
      v_biattention_id: [0, 1, 2, 3, 4, 5]
      t_biattention_id: [6, 7, 8, 9, 10, 11]
      pooling_method: "mul"

  guesser:
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