MATR/train.sh at main · vl2g/MATR · GitHub

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#!/bin/bash

# Job Parameters
dset_type=mr
dset_name="actnet"
clip_length=2


gpu_id=0
num_workers=16

exp_id="actnet-clip-2"
model_id=MATR

bsz=50
eval_bsz=4
n_epoch=200
lr=1e-4
lr_drop=80
lr_warmup=10
wd=1e-4

input_dropout=0.5
dropout=0
droppath=0.1

eval_epoch=5
enc_layers=4
eval_mode=add
round_multiple=-1
hidden_dim=1024

b_loss_coef=1
g_loss_coef=1
eos_coef=0.1
f_loss_coef=1
align_l=1
s_loss_intra_coef=0
s_loss_inter_coef=0


main_metric=MR-full-mAP-key
nms_thd=0.7
max_before_nms=1000

ctx_mode=video_tef
v_feat_types=clip
t_feat_type=clip
use_cache=-1
easy_negative_only=-1

resume="checkpoint path for resuming training"


# Data Paths
train_path="data/${dset_name}/metadata/train.jsonl"
eval_path="data/${dset_name}/metadata/val.jsonl"
eval_split_name=val
feat_root=data/${dset_name}

# Video Features
v_feat_dim=0
v_feat_dirs=()
if [[ ${v_feat_types} == *"slowfast"* ]]; then
  v_feat_dirs+=(${feat_root}/vid_slowfast)
  (( v_feat_dim += 2304 ))
fi
if [[ ${v_feat_types} == *"i3d"* ]]; then
  v_feat_dirs+=(${feat_root}/vid_i3d)
  (( v_feat_dim += 1024 ))
fi
if [[ ${v_feat_types} == *"c3d"* ]]; then
  v_feat_dirs+=(${feat_root}/vid_c3d)
  (( v_feat_dim += 500 ))
fi
if [[ ${v_feat_types} == *"clip"* ]]; then
  v_feat_dirs+=(${feat_root}/vid_clip)
  (( v_feat_dim += 512 ))
fi

# Text Features
if [[ ${t_feat_type} == "clip" ]]; then
  t_feat_dir=${feat_root}/vid_clip_query
  t_feat_dim=512
else
  echo "Wrong arg for t_feat_type."
  exit 1
fi

# Run Training
python3 ./main/train.py \
--dset_type ${dset_type} \
--dset_name ${dset_name} \
--clip_length ${clip_length} \
--exp_id ${exp_id} \
--gpu_id ${gpu_id} \
--model_id ${model_id} \
--v_feat_types ${v_feat_types} \
--t_feat_type ${t_feat_type} \
--ctx_mode ${ctx_mode} \
--train_path ${train_path} \
--eval_path ${eval_path} \
--eval_split_name ${eval_split_name} \
--eval_epoch ${eval_epoch} \
--v_feat_dirs ${v_feat_dirs[@]} \
--v_feat_dim ${v_feat_dim} \
--t_feat_dir ${t_feat_dir} \
--t_feat_dim ${t_feat_dim} \
--input_dropout ${input_dropout} \
--dropout ${dropout} \
--droppath ${droppath} \
--bsz ${bsz} \
--eval_bsz ${eval_bsz} \
--n_epoch ${n_epoch} \
--num_workers ${num_workers} \
--lr ${lr} \
--lr_drop ${lr_drop} \
--lr_warmup ${lr_warmup} \
--wd ${wd} \
--use_cache ${use_cache} \
--enc_layers ${enc_layers} \
--main_metric ${main_metric} \
--nms_thd ${nms_thd} \
--easy_negative_only ${easy_negative_only} \
--max_before_nms ${max_before_nms} \
--b_loss_coef ${b_loss_coef} \
--g_loss_coef ${g_loss_coef} \
--eos_coef ${eos_coef} \
--f_loss_coef ${f_loss_coef} \
--s_loss_intra_coef ${s_loss_intra_coef} \
--s_loss_inter_coef ${s_loss_inter_coef} \
--eval_mode ${eval_mode} \
--round_multiple ${round_multiple} \
--hidden_dim ${hidden_dim} \
--eval_init ${@:1} \
# --resume ${resume}