milvlg / mmnas Goto Github PK
View Code? Open in Web Editor NEWDeep Multimodal Neural Architecture Search
License: Apache License 2.0
Deep Multimodal Neural Architecture Search
License: Apache License 2.0
requirements.txt 缺失
还怎么pip install -r requirements.txt
As I follow the README, but there is no requirements.txt
.
Maybe you just ignore that.
And maybe it is the reason for the issue #4 .
The error is as the following:
========== Answer token vocab size (occur more than 8 times): 3129
========== Answer token vocab size (occur more than 8 times): 3129
========== Answer token vocab size (occur more than 8 times): 3129
========== Answer token vocab size (occur more than 8 times): 3129
Traceback (most recent call last):
File "search_vqa.py", line 615, in <module>
join=True
File "/home/zhouxx/anaconda3/envs/py36-t12-cu100/lib/python3.6/site-packages/torch/multiprocessing/spawn.py", line 171, in spawn
while not spawn_context.join():
File "/home/zhouxx/anaconda3/envs/py36-t12-cu100/lib/python3.6/site-packages/torch/multiprocessing/spawn.py", line 118, in join
raise Exception(msg)
Exception:
-- Process 3 terminated with the following error:
Traceback (most recent call last):
File "/home/zhouxx/anaconda3/envs/py36-t12-cu100/lib/python3.6/site-packages/torch/multiprocessing/spawn.py", line 19, in _wrap
fn(i, *args)
File "/home/zhouxx/gprojects/mmnas/search_vqa.py", line 607, in mp_entrance
exec.run()
File "/home/zhouxx/gprojects/mmnas/search_vqa.py", line 585, in run
self.search(train_loader, eval_loader)
File "/home/zhouxx/gprojects/mmnas/search_vqa.py", line 268, in search
for step, step_load in enumerate(train_loader):
File "/home/zhouxx/anaconda3/envs/py36-t12-cu100/lib/python3.6/site-packages/torch/utils/data/dataloader.py", line 819, in __next__
return self._process_data(data)
File "/home/zhouxx/anaconda3/envs/py36-t12-cu100/lib/python3.6/site-packages/torch/utils/data/dataloader.py", line 846, in _process_data
data.reraise()
File "/home/zhouxx/anaconda3/envs/py36-t12-cu100/lib/python3.6/site-packages/torch/_utils.py", line 369, in reraise
raise self.exc_type(msg)
KeyError: Caught KeyError in DataLoader worker process 0.
Original Traceback (most recent call last):
File "/home/zhouxx/anaconda3/envs/py36-t12-cu100/lib/python3.6/site-packages/torch/utils/data/_utils/worker.py", line 178, in _worker_loop
data = fetcher.fetch(index)
File "/home/zhouxx/anaconda3/envs/py36-t12-cu100/lib/python3.6/site-packages/torch/utils/data/_utils/fetch.py", line 44, in fetch
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/home/zhouxx/anaconda3/envs/py36-t12-cu100/lib/python3.6/site-packages/torch/utils/data/_utils/fetch.py", line 44, in <listcomp>
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/home/zhouxx/gprojects/mmnas/mmnas/loader/load_data_vqa.py", line 224, in __getitem__
frcn_feat = np.load(self.iid_to_frcn_feat_path[iid])
KeyError: '463620'
Why calculate the gradient of alpha_probs
like this?
probs = self.probs_over_ops.data
for i in range(self.n_choices):
for j in range(self.n_choices):
self.alpha_prob.grad.data[i] += binary_grads[j] * probs[j] * (self.delta_ij(i, j) - probs[i])
Code In MixedOp.set_arch_param_grad()
.
run search_itm.py
is stucked at epoch10. No errors occur and the program does not terminate itself.
The last output is as the following,
evaluate percent 45.2755905511811
evaluate percent 47.24409448818898
evaluate percent 49.21259842519685
evaluate percent 51.181102362204726
evaluate percent 53.14960629921261
evaluate percent 55.118110236220474
evaluate percent 57.08661417322835
evaluate percent 59.055118110236215
evaluate percent 61.023622047244096
evaluate percent 62.99212598425197
evaluate percent 64.96062992125984
evaluate percent 66.92913385826772
evaluate percent 68.89763779527559
evaluate percent 70.86614173228347
evaluate percent 72.83464566929135
evaluate percent 74.80314960629921
evaluate percent 76.77165354330708
evaluate percent 78.74015748031496
evaluate percent 80.70866141732283
evaluate percent 82.67716535433071
evaluate percent 84.64566929133859
evaluate percent 86.61417322834646
evaluate percent 88.58267716535433
evaluate percent 90.5511811023622
evaluate percent 92.51968503937007
evaluate percent 94.48818897637796
evaluate percent 96.45669291338582
evaluate percent 98.4251968503937
(1014, 5070)
i2t stat num: 1014
i2t results: 14.89 37.48 50.79 10.00 34.80
t2i stat num: 5070
t2i results: 12.31 36.31 51.50 10.00 29.36
reset negative captions ...
reset negative captions ...
reset negative captions ...
reset negative captions ...
And the output of nvidia-smi
is as the following all the time since the program is stucked.
Sat Feb 27 18:48:18 2021
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 440.64 Driver Version: 440.64 CUDA Version: 10.2 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
|===============================+======================+======================|
| 0 Tesla K40c On | 00000000:02:00.0 Off | 0 |
| 23% 37C P0 63W / 235W | 5573MiB / 11441MiB | 0% Default |
+-------------------------------+----------------------+----------------------+
| 1 Tesla K40c On | 00000000:03:00.0 Off | 0 |
| 23% 43C P0 69W / 235W | 9840MiB / 11441MiB | 100% Default |
+-------------------------------+----------------------+----------------------+
| 2 Tesla K40m On | 00000000:82:00.0 Off | 0 |
| N/A 33C P0 62W / 235W | 5573MiB / 11441MiB | 0% Default |
+-------------------------------+----------------------+----------------------+
| 3 Tesla K40m On | 00000000:83:00.0 Off | 0 |
| N/A 34C P0 68W / 235W | 9840MiB / 11441MiB | 100% Default |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: GPU Memory |
| GPU PID Type Process name Usage |
|=============================================================================|
| 0 24425 C ...naconda3/envs/py36-t101-cu90/bin/python 5562MiB |
| 1 24426 C ...naconda3/envs/py36-t101-cu90/bin/python 9827MiB |
| 2 24427 C ...naconda3/envs/py36-t101-cu90/bin/python 5562MiB |
| 3 24428 C ...naconda3/envs/py36-t101-cu90/bin/python 9827MiB |
+-----------------------------------------------------------------------------+
I have noticed that epoch10 is the NEG_START_EPOCH
, but I have no idea about what is wrong there.
I am following your work and running the code on VGD, with pertained features from dataset_setup.md But I failed to get the results mentioned in the paper: my test accuracy was often 2%~5% lower. Could you possibly provide more experimental details about the hyper-parameters such as CfgSearch
and Cfg
(e.g. ALPHA_START
, ALPHA_EVERY
, ALPHA_WEIGHT_DECAY
, NET_OPTIM_WARMUP
, NET_LR_DECAY_R
), and other potentially helpful tricks?
Thanks for your preeminent work and help.
Lines 285 to 288 in 552e29e
I have tried searching VQA with both MODE='full'
and MODE='two'
.
Searching with MODE='two'
holds less GPU memory, which is expected.
But it takes more time to search with MODE='two'
than with MODE='full'
, which confuses me.
Could anyone give some explanation? I'll appreciate it!
The warning is as the following:
lib/python3.6/site-packages/spacy/util.py:275: UserWarning: [W031] Model 'en_vectors_web_lg' (2.1.0) requires spaCy v2.1 and is incompatible with the current spaCy ver
sion (2.3.5). This may lead to unexpected results or runtime errors. To resolve this, download a newer compatible model or retrain your custom model with the current spaCy version. For more details and availabl
e updates, run: python -m spacy validate
warnings.warn(warn_msg)
Why does the warning occur? And is it necessary to fix it?
can't open ''https://scanproject.blob.core.windows.net/scan-data/data_no_feature.zip'' to downloaded f30k_precomp folder.
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.