vita-epfl / social-nce Goto Github PK

hello, thanks for you available code.
i met error like this when i run "python imitate.py --contrast_weight=2.0 --contrast_sampling='local' --gpu" in crowd_nav path, the error information is:
RuntimeError: CUDA error: CUBLAS_STATUS_INVALID_VALUE when calling cublasSgemm( handle, opa, opb, m, n, k, &alpha, a, lda, b, ldb, &beta, c, ldc)
it seems that the attention's linear operation got the wrong shapes, what should i do?
thanks :)

Thank you for your hard work.
in the file "crowd_nav/utils/demonstrate.py"

   from crowd_nav.utils.frames import FrameStack
  from crowd_nav.utils.trainer import Imitator
  from crowd_nav.utils.memory import ReplayMemory

I cannot find "Imitator" in crowd_nav.utils.trainer.
will you help me ?

I tried to run the test.py script with visualize option python test.py --policy='sail' --circle --model_file=data/output/imitate-event-data-0.50-weight-2.0-horizon-4-temperature-0.20-nboundary-0/policy_net.pth --visualize and got an error below

Traceback (most recent call last):
  File "test.py", line 126, in <module>
    main()
  File "test.py", line 105, in main
    action = robot.act(ob)
  File "/home/vale/github/mpc-nav/social-nce/crowd_sim/envs/utils/robot.py", line 13, in act
    action = self.policy.predict(state)
  File "/home/vale/github/mpc-nav/social-nce/crowd_nav/policy/sail.py", line 122, in predict
    self.last_state = self.transform(state)
  File "/home/vale/github/mpc-nav/social-nce/crowd_nav/policy/sail.py", line 134, in transform
    num_human = len(state.human_states)
TypeError: object of type 'ObservableState' has no len()

Can anyone help me with that issue?

Hi I am about to try your code on the Trajnet++.

I am trying to get the FDE score of 1.14 .

Did you train on the whole (with cff) training dataset?
How many epochs?
And with which parameters?

If I reach your performance I will delete the submission if desired.

Thanks in advance
Many greetings

Hello,

I tried to train a social NCE with GPU option using python imitate.py --contrast_weight=2.0 --contrast_sampling='event' --gpu, and I got an error below

RuntimeError: Expected all tensors to be on the same device, but found at least two devices, cuda:0 and cpu! (when checking argument for argument mask in method wrapper__masked_select)

Does anyone help me to fix this issue? Thanks in advance.

Hello, me and my team are trying to analyze your works(both of crowdnav and social-nce) as term project.
While I run test.py I face two problems.
1st. In square scenario, there is too large decreasing of performance. WHY?

!python test.py --policy='sail' --square --model_file=data/output/imitate-event-data-0.50-weight-2.0-horizon-4-temperature-0.20-nboundary-0/policy_net.pth
(skip)
2021-12-05 08:55:59, INFO: TEST success: 0.58, collision: 0.41, nav time: 10.43, reward: 0.1095 +- 0.2644
2021-12-05 08:55:59, INFO: Frequency of being in danger: 1.23

2nd. In mixed scenario, (I add argument in parser), error is occur
Traceback (most recent call last):

File "test.py", line 129, in
main()
File "test.py", line 126, in main
explorer.run_k_episodes(env.case_size[args.phase], args.phase, print_failure=False)
File "/content/drive/My Drive/ColabFiles/robotvision/social-nce/crowd_nav/utils/explorer.py", line 60, in run_k_episodes
action = self.robot.act(ob)
File "/content/drive/My Drive/ColabFiles/robotvision/social-nce/crowd_sim/envs/utils/robot.py", line 13, in act
action = self.policy.predict(state)
File "/content/drive/My Drive/ColabFiles/robotvision/social-nce/crowd_nav/policy/sail.py", line 123, in predict
action = self.model(self.last_state[0], self.last_state[1])[0].squeeze()
File "/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "/content/drive/My Drive/ColabFiles/robotvision/social-nce/crowd_nav/policy/sail.py", line 73, in forward
human_state = self.transform.transform_frame(crowd_obsv)
File "/content/drive/My Drive/ColabFiles/robotvision/social-nce/crowd_nav/utils/transform.py", line 14, in transform_frame
state = torch.cat([frame, relative], axis=2)
RuntimeError: Sizes of tensors must match except in dimension 2. Expected size 1 but got size 5 for tensor number 1 in the list.

If you already have knew about those problem, please share the answers. Thank you for reading

Thanks for your great work!

why?

Thanks for your wonderful repo!
May I ask what does SAIL policy refer to?
Based on the paper I only find SARL but not SAIL. Is SAIL an upgrade version of SARL?
Thanks!

When I download data, pip install gdown && gdown https://drive.google.com/uc?id=1D2guAxD_EgrKnJFMcLSBkf10SOagz0mr,
it occurs that:
Traceback (most recent call last):
File "/home/lyl/miniconda3/lib/python3.8/site-packages/urllib3/connection.py", line 169, in _new_conn
conn = connection.create_connection(
File "/home/lyl/miniconda3/lib/python3.8/site-packages/urllib3/util/connection.py", line 96, in create_connection
raise err
File "/home/lyl/miniconda3/lib/python3.8/site-packages/urllib3/util/connection.py", line 86, in create_connection
sock.connect(sa)
OSError: [Errno 101] Network is unreachable

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "/home/lyl/miniconda3/lib/python3.8/site-packages/urllib3/connectionpool.py", line 699, in urlopen
httplib_response = self._make_request(
File "/home/lyl/miniconda3/lib/python3.8/site-packages/urllib3/connectionpool.py", line 382, in _make_request
self._validate_conn(conn)
File "/home/lyl/miniconda3/lib/python3.8/site-packages/urllib3/connectionpool.py", line 1010, in _validate_conn
conn.connect()
File "/home/lyl/miniconda3/lib/python3.8/site-packages/urllib3/connection.py", line 353, in connect
conn = self._new_conn()
File "/home/lyl/miniconda3/lib/python3.8/site-packages/urllib3/connection.py", line 181, in _new_conn
raise NewConnectionError(
urllib3.exceptions.NewConnectionError: <urllib3.connection.HTTPSConnection object at 0x7f96a64c1100>: Failed to establish a new connection: [Errno 101] Network is unreachable

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "/home/lyl/miniconda3/lib/python3.8/site-packages/requests/adapters.py", line 439, in send
resp = conn.urlopen(
File "/home/lyl/miniconda3/lib/python3.8/site-packages/urllib3/connectionpool.py", line 755, in urlopen
retries = retries.increment(
File "/home/lyl/miniconda3/lib/python3.8/site-packages/urllib3/util/retry.py", line 573, in increment
raise MaxRetryError(_pool, url, error or ResponseError(cause))
urllib3.exceptions.MaxRetryError: HTTPSConnectionPool(host='drive.google.com', port=443): Max retries exceeded with url: /uc?id=1awXDsRQcmgacj7nUhPzwb5UMNZCJCjvu (Caused by NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x7f96a64c1100>: Failed to establish a new connection: [Errno 101] Network is unreachable'))

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "/home/lyl/miniconda3/bin/gdown", line 8, in
sys.exit(main())
File "/home/lyl/miniconda3/lib/python3.8/site-packages/gdown/cli.py", line 95, in main
download(
File "/home/lyl/miniconda3/lib/python3.8/site-packages/gdown/download.py", line 77, in download
res = sess.get(url, stream=True)
File "/home/lyl/miniconda3/lib/python3.8/site-packages/requests/sessions.py", line 555, in get
return self.request('GET', url, **kwargs)
File "/home/lyl/miniconda3/lib/python3.8/site-packages/requests/sessions.py", line 542, in request
resp = self.send(prep, **send_kwargs)
File "/home/lyl/miniconda3/lib/python3.8/site-packages/requests/sessions.py", line 655, in send
r = adapter.send(request, **kwargs)
File "/home/lyl/miniconda3/lib/python3.8/site-packages/requests/adapters.py", line 516, in send
raise ConnectionError(e, request=request)
requests.exceptions.ConnectionError: HTTPSConnectionPool(host='drive.google.com', port=443): Max retries exceeded with url: /uc?id=1awXDsRQcmgacj7nUhPzwb5UMNZCJCjvu (Caused by NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x7f96a64c1100>: Failed to establish a new connection: [Errno 101] Network is unreachable'))

Can you fix it?Thanks.

I have read your article（Social-NCE） carefully and am very interested in the part about offline reinforcement learning, but I don't seem to find the corresponding part in this code. Can you tell me how to get it? or can you give me some recommended codes?

Hello,

first of all, thank you for the publicly available code! I have 2 understanding questions regarding the training:

1. as far as I understand you determine the positive and negative samples based on the ground truth at time t, with the horizon of e.g. 5 time steps. What about the possible collisions before and after the one point?
2. What is the ground truth in reinforcement learning? Do you use here a linear model?

Best regards

Thanks for your hard work.

I have some questions about this code
for alpha in alpha_list:
sample_boundary.append(neg_seed * alpha + pos_seed.unsqueeze(2) * (1-alpha))
Looks like
α* neg_ seeds + (1- α)* pos_ seeds
What is the purpose of this code

from sampling.py

    # primary-neighbor boundary
    if self.num_boundary > 0:
        alpha_list = torch.linspace(self.ratio_boundary, 1.0, steps=self.num_boundary) #0.5-1 分成0-9份 参数决定
        sample_boundary = []
        for alpha in alpha_list:
            sample_boundary.append(neg_seed * alpha + pos_seed.unsqueeze(2) * (1-alpha))
        sample_boundary = torch.cat(sample_boundary, axis=2)
        sample_neg = torch.cat([sample_boundary, sample_territory], axis=2)
    else:
        sample_neg = sample_territory

Thanks!