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fix: for evaluate original REVERIE model on our dataset

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Ting-Jun Wang 2024-06-30 16:42:58 +08:00
parent 007e160b13
commit 0a533c0647
Signed by: snsd0805
GPG Key ID: 48D331A3D6160354
5 changed files with 20 additions and 19 deletions
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4
map_nav_src/r2r/data_utils.py
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@ -37,10 +37,10 @@ def construct_instrs(anno_dir, dataset, splits, tokenizer, max_instr_len=512, is
# Split multiple instructions into separate entries # Split multiple instructions into separate entries
for j, instr in enumerate(item['instructions']): for j, instr in enumerate(item['instructions']):
new_item = dict(item) new_item = dict(item)
new_item['instr_id'] = '%s_%d' % (item['path_id'], j) new_item['instr_id'] = '%s_%d' % (item['id'], j)
new_item['instruction'] = instr new_item['instruction'] = instr
new_item['instr_encoding'] = item['instr_encodings'][j][:max_instr_len] new_item['instr_encoding'] = item['instr_encodings'][j][:max_instr_len]
del new_item['instructions'] del new_item['instructions']
del new_item['instr_encodings'] del new_item['instr_encodings']
data.append(new_item) data.append(new_item)
return data return data

6
map_nav_src/r2r/main_nav.py
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@ -58,12 +58,12 @@ def build_dataset(args, rank=0, is_test=False):
) )
# val_env_names = ['val_train_seen'] # val_env_names = ['val_train_seen']
val_env_names = ['val_train_seen', 'val_seen', 'val_unseen'] val_env_names = ['val_seen', 'val_unseen']
if args.dataset == 'r4r' and (not args.test): if args.dataset == 'r4r' and (not args.test):
val_env_names[-1] == 'val_unseen_sampled' val_env_names[-1] == 'val_unseen_sampled'
if args.submit and args.dataset != 'r4r': # if args.submit and args.dataset != 'r4r':
val_env_names.append('test') # val_env_names.append('test')
val_envs = {} val_envs = {}
for split in val_env_names: for split in val_env_names:

4
map_nav_src/reverie/main_nav_obj.py
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@ -68,8 +68,8 @@ def build_dataset(args, rank=0):
# val_env_names = ['val_train_seen'] # val_env_names = ['val_train_seen']
val_env_names = ['val_seen', 'val_unseen'] val_env_names = ['val_seen', 'val_unseen']
if args.submit: # if args.submit:
val_env_names.append('test') # val_env_names.append('test')
val_envs = {} val_envs = {}
for split in val_env_names: for split in val_env_names:

12
map_nav_src/scripts/run_r2r.sh
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@ -10,7 +10,7 @@ obj_ft_dim=768
ngpus=1 ngpus=1
seed=0 seed=0
name=${train_alg}-${features} name=${train_alg}-${features}-reverie-glip-adversarial
name=${name}-seed.${seed} name=${name}-seed.${seed}
name=${name}-init.aug.45k name=${name}-init.aug.45k
@ -57,11 +57,11 @@ flag="--root_dir ${DATA_ROOT}
# train # train
CUDA_VISIBLE_DEVICES='0' python r2r/main_nav.py $flag \ CUDA_VISIBLE_DEVICES='0' python r2r/main_nav.py $flag \
--tokenizer bert \ --tokenizer bert \
--bert_ckpt_file 'put the pretrained model (see pretrain_src) here' \ --bert_ckpt_file '../datasets/REVERIE/exprs_map/pretrain/cmt-vitbase-mlm.mrc.sap.og-init.lxmert-aug.speaker/ckpts/model_step_100000.pt' \
--eval_first --eval_first
# test # test
CUDA_VISIBLE_DEVICES='0' python r2r/main_nav.py $flag \ # CUDA_VISIBLE_DEVICES='0' python r2r/main_nav.py $flag \
--tokenizer bert \ # --tokenizer bert \
--resume_file ../datasets/R2R/trained_models/best_val_unseen \ # --resume_file ../datasets/R2R/trained_models/best_val_unseen \
--test --submit # --test --submit

13
map_nav_src/scripts/run_reverie.sh
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@ -10,7 +10,7 @@ obj_ft_dim=768
ngpus=1 ngpus=1
seed=0 seed=0
name=${train_alg}-${features}-advanced_adversarial name=${train_alg}-${features}-adversarial-but-original-model-with-glip-filter
name=${name}-seed.${seed} #-${ngpus}gpus name=${name}-seed.${seed} #-${ngpus}gpus
outdir=${DATA_ROOT}/REVERIE/exprs_map/finetune/${name} outdir=${DATA_ROOT}/REVERIE/exprs_map/finetune/${name}
@ -59,13 +59,14 @@ flag="--root_dir ${DATA_ROOT}
--gamma 0." --gamma 0."
# train # train
CUDA_VISIBLE_DEVICES='0' python reverie/main_nav_obj.py $flag \ # CUDA_VISIBLE_DEVICES='0' python reverie/main_nav_obj.py $flag \
--tokenizer bert \ # --tokenizer bert \
--bert_ckpt_file '../datasets/REVERIE/exprs_map/pretrain/cmt-vitbase-mlm.mrc.sap.og-init.lxmert-aug.speaker/ckpts/model_step_100000.pt' \ # --resume_file ../datasets/REVERIE/exprs_map/finetune/dagger-vitbase-adversarial-but-original-model-with-glip-filter-seed.0/ckpts/best_val_unseen \
--eval_first # --bert_ckpt_file '../datasets/REVERIE/exprs_map/pretrain/cmt-vitbase-mlm.mrc.sap.og-init.lxmert-aug.speaker/ckpts/model_step_100000.pt' \
# --eval_first
# test # test
CUDA_VISIBLE_DEVICES='0' python reverie/main_nav_obj.py $flag \ CUDA_VISIBLE_DEVICES='0' python reverie/main_nav_obj.py $flag \
--tokenizer bert \ --tokenizer bert \
--resume_file ../datasets/REVERIE/trained_models/best_val_unseen \ --resume_file ../datasets/REVERIE/exprs_map/finetune/dagger-vitbase-adversarial-but-original-model-with-glip-filter-seed.0/ckpts/best_val_unseen \
--test --submit --test --submit