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cfg.yaml
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cfg.yaml
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DATA:
# CHECKPOINT_MODULE_FILE_PATH: "./data/Ego4D/v1/lta_models/pretrained_models/long_term_anticipation/kinetics_slowfast8x8.ckpt"
PATH_TO_DATA_FILE: # Train on PRETRAIN data, and validate on USER-TRAIN SUBSET (which we use for hyperparam tuning)
TRAIN: "../../../data/EgoAdapt/usersplits/ego4d_LTA_pretrain_incl_nanusers_usersplit_148users.json"
VAL: "../../../data/EgoAdapt/usersplits/ego4d_LTA_train_usersplit_10users.json"
TEST: "" # No testing phase
NUM_FRAMES: 32
SAMPLING_RATE: 2
TRAIN_JITTER_SCALES: [ 256, 320 ]
TRAIN_CROP_SIZE: 224
TEST_CROP_SIZE: 256
INPUT_CHANNEL_NUM: [ 3, 3 ]
TASK: "classification"
TARGET_FPS: 30
TRAIN:
ENABLE: True
DATASET: Ego4dRecognition
BATCH_SIZE: 64
SLOWFAST:
ALPHA: 4
BETA_INV: 8
FUSION_CONV_CHANNEL_RATIO: 2
FUSION_KERNEL_SZ: 5
RESNET:
ZERO_INIT_FINAL_BN: True
WIDTH_PER_GROUP: 64
NUM_GROUPS: 1
DEPTH: 101
TRANS_FUNC: bottleneck_transform
STRIDE_1X1: False
NUM_BLOCK_TEMP_KERNEL: [ [ 3, 3 ], [ 4, 4 ], [ 23, 23 ], [ 3, 3 ] ]
SPATIAL_STRIDES: [ [ 1, 1 ], [ 2, 2 ], [ 2, 2 ], [ 2, 2 ] ]
SPATIAL_DILATIONS: [ [ 1, 1 ], [ 1, 1 ], [ 1, 1 ], [ 1, 1 ] ]
NONLOCAL:
LOCATION: [ [ [ ], [ ] ], [ [ ], [ ] ], [ [ ], [ ] ], [ [ ], [ ] ] ]
GROUP: [ [ 1, 1 ], [ 1, 1 ], [ 1, 1 ], [ 1, 1 ] ]
INSTANTIATION: softmax
BN:
USE_PRECISE_STATS: True
NUM_BATCHES_PRECISE: 20 # Originally 200 for full Ego4d, but have only 166 batches for subset
SOLVER:
BASE_LR: 1e-4 # Ego4d LR (also best in grid)
LR_POLICY: cosine # -> No linear warmup. Old: 'cosine_warmup'
MAX_EPOCH: 46
MOMENTUM: 0.9
OPTIMIZING_METHOD: sgd
WEIGHT_DECAY: 1e-4
MODEL:
NUM_CLASSES: [ 115, 478 ]
ARCH: slowfast
MODEL_NAME: MultiTaskSlowFast
LOSS_FUNC: cross_entropy
DROPOUT_RATE: 0.5
TEST:
ENABLE: False
DATASET: Ego4dRecognition
BATCH_SIZE: 64
DATA_LOADER:
NUM_WORKERS: 4
PIN_MEMORY: True
NUM_GPUS: 8
NUM_SHARDS: 1
RNG_SEED: 0
OUTPUT_DIR: .