pmg_v2_resnet50.yml

EXP_NAME: "PMG_V2_ResNet50"

RESUME_WEIGHT: ~

WEIGHT:
  NAME: "pmg_v2_resnet50.pth"
  SAVE_DIR: "/mnt/sdb/data/wangxinran/model/fgvclib/"

LOGGER: 
  NAME: "txt_logger"

DATASET:
  NAME: "CUB_200_2011"
  ROOT: "/mnt/sdb/data/wangxinran/dataset/"
  TRAIN: 
    BATCH_SIZE: 16
    POSITIVE: 1
    PIN_MEMORY: True
    SHUFFLE: True
    NUM_WORKERS: 4
  TEST: 
    BATCH_SIZE: 16
    POSITIVE: 0
    PIN_MEMORY: False
    SHUFFLE: False
    NUM_WORKERS: 4

MODEL:
  NAME: "PMG_V2"
  CLASS_NUM: 200
  ARGS: 
    - outputs_num: 3
    - BLOCKS: 
      - [8, 8, 0, 0]
      - [4, 4, 4, 0]
      - [2, 2, 2, 2]
    - alpha: 
      - 0.01
      - 0.05
      - 0.1
  CRITERIONS: 
    - name: "cross_entropy_loss"
      args: []
      w: ~
    - name: "mean_square_error_loss"
      args: []
      w: ~
  BACKBONE:
    NAME: "resnet50_bc"
    ARGS: 
      - pretrained: True
      - del_keys: []
  ENCODER:
    NAME: "global_max_pooling"
  NECKS:
    NAME: "multi_scale_conv"
    ARGS:
      - scale_num: 3
      - in_dim: 
        - 512
        - 1024
        - 2048
      - hid_dim:
        - 512
        - 512
        - 512
      - out_dim:
        - 1024
        - 1024
        - 1024
  HEADS:
    NAME: "classifier_2fc"
    ARGS:
      - in_dim: 
        - 1024
        - 1024
        - 1024
      - hid_dim: 512

TRANSFORMS: 
  TRAIN: 
    - name: "resize"
      size: 
        - 600
        - 600
    - name: "random_crop"
      size: 448
      padding: 8
    - name: "random_horizontal_flip"
      prob: 0.5
    - name: "to_tensor"
    - name: "normalize"
      mean: 
         - 0.5
         - 0.5
         - 0.5
      std: 
        - 0.5
        - 0.5
        - 0.5
  TEST:
    - name: "resize"
      size: 
        - 600
        - 600
    - name: "center_crop"
      size: 448
    - name: "to_tensor"
    - name: "normalize"
      mean: 
         - 0.5
         - 0.5
         - 0.5
      std: 
        - 0.5
        - 0.5
        - 0.5

OPTIMIZER:
  NAME: "SGD"
  ARGS: 
    - momentum: 0.9
    - weight_decay: 0.0005
  LR: 
    base: 0.0005 
    backbone: 0.0005
    encoder: ~
    necks: 0.005
    heads: 0.005

ITERATION_NUM: ~
EPOCH_NUM: 10
START_EPOCH: 0
UPDATE_STRATEGY: "progressive_updating_consistency_constraint"

# Validation details
PER_ITERATION: ~
PER_EPOCH: ~
METRICS: 
  - name: "accuracy(topk=1)"
    metric: "accuracy"
    top_k: 1
    threshold: ~
  - name: "accuracy(topk=5)"
    metric: "accuracy"
    top_k: 5
    threshold: ~
  - name: "recall(threshold=0.5)"
    metric: "recall"
    top_k: ~
    threshold: 0.5
  - name: "precision(threshold=0.5)"
    metric: "precision"
    top_k: ~
    threshold: 0.5