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### General settings
name: FGT_train
use_tb_logger: true
outputdir: /myData/ret/experiments
datadir: /myData
record_iter: 16
### Calling definition
model: model
datasetName_train: train_dataset
network: network
### datasets
datasets:
train:
name: youtubevos
type: video
mode: train
dataInfo_config: ./config/data_info.yaml
use_shuffle: True
n_workers: 0
batch_size: 2
val:
name: youtubevos
type: video
mode: val
use_shuffle: False
n_workers: 1
batch_size: 1
val_config: ./config/valid_config.yaml
### train settings
train:
lr: 0.0001
lr_decay: 0.1
manual_seed: 10
BETA1: 0.9
BETA2: 0.999
MAX_ITERS: 500000
UPDATE_INTERVAL: 300000 # 400000 is also OK
WARMUP: ~
val_freq: 1 # Set to 1 is for debug, you can enlarge it to 50 in regular training
TEMPORAL_GAN: ~ # without temporal GAN
### logger
logger:
PRINT_FREQ: 16
SAVE_CHECKPOINT_FREQ: 4000 # 100 is for debug consideration
### Data related parameters
flow2rgb: 1
flow_direction: for
num_frames: 5
sample: random
max_val: 0.01
### Model related parameters
res_h: 240
res_w: 432
in_channel: 4
cnum: 64
flow_inChannel: 2
flow_cnum: 64
dist_cnum: 32
frame_hidden: 512
flow_hidden: 256
PASSMASK: 1
num_blocks: 8
kernel_size_w: 7
kernel_size_h: 7
stride_h: 3
stride_w: 3
num_head: 4
conv_type: vanilla
norm: None
use_bias: 1
ape: 1
pos_mode: single
mlp_ratio: 40
drop: 0
init_weights: 1
tw: 2
sw: 8
gd: 4
### Loss weights
L1M: 1
L1V: 1
adv: 0.01
### inference parameters
ref_length: 10