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fix: original airbert

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This commit is contained in:
Ting-Jun Wang 2023-12-31 18:19:57 +08:00
parent d65a71e033
commit 7fab347934
Signed by: snsd0805
GPG Key ID: 48D331A3D6160354
7 changed files with 34 additions and 28 deletions
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12
reverie_src/agent.py
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@ -245,9 +245,11 @@ class Seq2SeqAgent(BaseAgent):
"""
def take_action(i, idx, name):
if type(name) is int: # Go to the next view
self.env.env.sims[idx].makeAction(name, 0, 0)
self.env.env.sims[idx].makeAction([name], [0], [0])
else: # Adjust
self.env.env.sims[idx].makeAction(*self.env_actions[name])
action_params = self.env_actions[name]
self.env.env.sims[idx].makeAction([action_params[0]], [action_params[1]], [action_params[2]])
if perm_idx is None:
perm_idx = range(len(perm_obs))
@ -266,13 +268,13 @@ class Seq2SeqAgent(BaseAgent):
while src_level > trg_level: # Tune down
take_action(i, idx, 'down')
src_level -= 1
while self.env.env.sims[idx].getState().viewIndex != trg_point: # Turn right until the target
while self.env.env.sims[idx].getState()[0].viewIndex != trg_point: # Turn right until the target
take_action(i, idx, 'right')
assert select_candidate['viewpointId'] == \
self.env.env.sims[idx].getState().navigableLocations[select_candidate['idx']].viewpointId
self.env.env.sims[idx].getState()[0].navigableLocations[select_candidate['idx']].viewpointId
take_action(i, idx, select_candidate['idx'])
state = self.env.env.sims[idx].getState()
state = self.env.env.sims[idx].getState()[0]
if traj is not None:
traj[i]['path'].append((state.location.viewpointId, state.heading, state.elevation))

20
reverie_src/env.py
View File

@ -50,15 +50,15 @@ class EnvBatch():
sim.setDiscretizedViewingAngles(True) # Set increment/decrement to 30 degree. (otherwise by radians)
sim.setCameraResolution(self.image_w, self.image_h)
sim.setCameraVFOV(math.radians(self.vfov))
sim.init()
sim.initialize()
self.sims.append(sim)
def _make_id(self, scanId, viewpointId):
return scanId + '_' + viewpointId
def newEpisodes(self, scanIds, viewpointIds, headings):
for i, (scanId, viewpointId, heading) in enumerate(zip(scanIds, viewpointIds, headings)):
self.sims[i].newEpisode(scanId, viewpointId, heading, 0)
for i, (scanId, viewpointId, heading) in enumerate(zip(scanIds[0], viewpointIds[0], headings[0])):
self.sims[i].newEpisode([scanId], [viewpointId], [heading], [0])
def getStates(self):
"""
@ -69,7 +69,7 @@ class EnvBatch():
"""
feature_states = []
for i, sim in enumerate(self.sims):
state = sim.getState()
state = sim.getState()[0]
long_id = self._make_id(state.scanId, state.location.viewpointId)
if self.features:
@ -83,7 +83,7 @@ class EnvBatch():
''' Take an action using the full state dependent action interface (with batched input).
Every action element should be an (index, heading, elevation) tuple. '''
for i, (index, heading, elevation) in enumerate(actions):
self.sims[i].makeAction(index, heading, elevation)
self.sims[i].makeAction([index], [heading], [elevation])
class R2RBatch():
@ -231,13 +231,13 @@ class R2RBatch():
if long_id not in self.buffered_state_dict:
for ix in range(36):
if ix == 0:
self.sim.newEpisode(scanId, viewpointId, 0, math.radians(-30))
self.sim.newEpisode([scanId], [viewpointId], [0], [math.radians(-30)])
elif ix % 12 == 0:
self.sim.makeAction(0, 1.0, 1.0)
self.sim.makeAction([0], [1.0], [1.0])
else:
self.sim.makeAction(0, 1.0, 0)
self.sim.makeAction([0], [1.0], [0])
state = self.sim.getState()
state = self.sim.getState()[0]
assert state.viewIndex == ix
# Heading and elevation for the viewpoint center
@ -360,7 +360,7 @@ class R2RBatch():
scanIds = [item['scan'] for item in self.batch]
viewpointIds = [item['path'][0] for item in self.batch]
headings = [item['heading'] for item in self.batch]
self.env.newEpisodes(scanIds, viewpointIds, headings)
self.env.newEpisodes([scanIds], [viewpointIds], [headings])
return self._get_obs()
def step(self, actions):

8
reverie_src/train.py
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@ -55,7 +55,7 @@ def train(train_env, tok, n_iters, log_every=2000, val_envs={}, aug_env=None):
start = time.time()
print('\nListener training starts, start iteration: %s' % str(start_iter))
best_val = {'val_unseen': {"spl": 0., "sr": 0., "state":"", 'update':False}}
best_val = {'val_unseen': {"spl": 0., "sr": 0., "sspl": 0. ,"state":"", 'update':False}}
for idx in range(start_iter, start_iter+n_iters, log_every):
listner.logs = defaultdict(list)
@ -214,7 +214,7 @@ def train_val(test_only=False):
val_env_names = ['val_train_seen']
else:
featurized_scans = set([key.split("_")[0] for key in list(feat_dict.keys())])
val_env_names = ['val_train_seen', 'val_seen', 'val_unseen']
val_env_names = ['val_seen', 'val_unseen']
train_env = R2RBatch(feat_dict, obj_feats, batch_size=args.batchSize, splits=['train'], tokenizer=tok)
from collections import OrderedDict
@ -252,6 +252,7 @@ def train_val_augment(test_only=False):
# Load the env img features
feat_dict = read_img_features(features, test_only=test_only)
# load object feature
with open('data/REVERIE/BBoxS/REVERIE_obj_feats.pkl', 'rb') as f_obj:
obj_feats = pkl.load(f_obj)
@ -261,7 +262,8 @@ def train_val_augment(test_only=False):
val_env_names = ['val_train_seen']
else:
featurized_scans = set([key.split("_")[0] for key in list(feat_dict.keys())])
val_env_names = ['val_train_seen', 'val_seen', 'val_unseen']
val_env_names = ['val_seen', 'val_unseen']
# val_env_names = ['val_train_seen', 'val_seen', 'val_unseen']
# Load the augmentation data
aug_path = args.aug

12
reverie_src/utils.py
View File

@ -346,7 +346,7 @@ def new_simulator():
sim.setCameraResolution(WIDTH, HEIGHT)
sim.setCameraVFOV(math.radians(VFOV))
sim.setDiscretizedViewingAngles(True)
sim.init()
sim.initialize()
return sim
@ -357,13 +357,13 @@ def get_point_angle_feature(baseViewId=0):
base_heading = (baseViewId % 12) * math.radians(30)
for ix in range(36):
if ix == 0:
sim.newEpisode('ZMojNkEp431', '2f4d90acd4024c269fb0efe49a8ac540', 0, math.radians(-30))
sim.newEpisode(['ZMojNkEp431'], ['2f4d90acd4024c269fb0efe49a8ac540'], [0], [math.radians(-30)])
elif ix % 12 == 0:
sim.makeAction(0, 1.0, 1.0)
sim.makeAction([0], [1.0], [1.0])
else:
sim.makeAction(0, 1.0, 0)
sim.makeAction([0], [1.0], [0])
state = sim.getState()
state = sim.getState()[0]
assert state.viewIndex == ix
heading = state.heading - base_heading
@ -567,7 +567,7 @@ def print_progress(iteration, total, prefix='', suffix='', decimals=1, bar_lengt
str_format = "{0:." + str(decimals) + "f}"
percents = str_format.format(100 * (iteration / float(total)))
filled_length = int(round(bar_length * iteration / float(total)))
bar = '█' * filled_length + '-' * (bar_length - filled_length)
bar = 'L' * filled_length + '-' * (bar_length - filled_length)
sys.stdout.write('\r%s |%s| %s%s %s' % (prefix, bar, percents, '%', suffix)),

2
reverie_src/vlnbert/vlnbert_init.py
View File

@ -1,7 +1,7 @@
import os
def get_tokenizer(args):
from transformers.pytorch_transformers import BertTokenizer
from pytorch_transformers import BertTokenizer
tokenizer_class = BertTokenizer

4
scripts/train_reverie_agent.sh
View File

@ -1,7 +1,7 @@
export AIRBERT_ROOT=$(pwd)
export PYTHONPATH=${PYTHONPATH}:${AIRBERT_ROOT}/build
name=REVERIE-RC-VLN-BERT/train-init.airbert
name=REVERIE-RC-VLN-BERT-original/train-init.airbert
flag="--vlnbert vilbert
@ -26,4 +26,4 @@ flag="--vlnbert vilbert
--dropout 0.5"
mkdir -p snap/$name
CUDA_VISIBLE_DEVICES=$1 python reverie_src/train.py $flag --name $name
CUDA_VISIBLE_DEVICES=$1 python3 reverie_src/train.py $flag --name $name

4
scripts/valid_reverie_agent.sh
View File

@ -1,6 +1,8 @@
export AIRBERT_ROOT=$(pwd)
export PYTHONPATH=${PYTHONPATH}:${AIRBERT_ROOT}/build
echo $PYTHONPATH
name=REVERIE-RC-VLN-BERT/init.airbert
flag="--vlnbert vilbert
@ -25,5 +27,5 @@ flag="--vlnbert vilbert
--featdropout 0.4
--dropout 0.5"
CUDA_VISIBLE_DEVICES=$1 python reverie_src/train.py $flag --name $name
CUDA_VISIBLE_DEVICES=$1 python3 reverie_src/train.py $flag --name $name