Detailed description

我看论文中在lateral connections中采用的是1X1卷积,但是看代码中实现的是3X3 kernel大小。是否这样实现的性能更高，就是单纯的求问一下哈

Then at each stage, a 1 × 1 convolutional layer is taken to rearrange the features and adjust the channel dimension

lateral_layer 代码

https://github.com/ShiqiYu/OpenGait/blob/6a469fcd8d0fbe23262ec3d751cf74ec341f17b6/lib/modeling/models/gln.py#L54-L59

用笔记本测试的，只有一块显卡所以用的CUDA_VISIBLE_DEVICES=0 python -m torch.distributed.launch --nproc_per_node=1 lib/main.py --cfgs ./config/gaitset.yaml --phase train。报错Traceback (most recent call last): File "lib/main.py", line 66, in run_model(cfgs, training) File "lib/main.py", line 49, in run_model Model.run_train(model) File "/home/yq/OpenGait/lib/modeling/base_model.py", line 371, in run_train model.train_step(loss_sum) File "/home/yq/OpenGait/lib/modeling/base_model.py", line 307, in train_step self.Scaler.scale(loss_sum).backward() File "/home/yq/anaconda3/envs/pt14/lib/python3.7/site-packages/torch/tensor.py", line 185, in backward torch.autograd.backward(self, gradient, retain_graph, create_graph) File "/home/yq/anaconda3/envs/pt14/lib/python3.7/site-packages/torch/autograd/init.py", line 127, in backward allow_unreachable=True) # allow_unreachable flag RuntimeError: Unable to find a valid cuDNN algorithm to run convolution Exception raised from try_all at /pytorch/aten/src/ATen/native/cudnn/Conv.cpp:692 (most recent call first): 请问是怎么回事啊

In the inference of the GaitEdge , why it still need silhouette as input ? Can't it get silhouette from the output of the Segmentation U-Net? Also ,I don't understand why it need to input ratios . Isn't the end to end network just an RGB image input?

def forward(self, inputs):
        ipts, labs, _, _, seqL = inputs

        ratios = ipts[0]
        rgbs = ipts[1]
        sils = ipts[2]

        n, s, c, h, w = rgbs.size()
        rgbs = rgbs.view(n*s, c, h, w)
        sils = sils.view(n*s, 1, h, w)
        logis = self.Backbone(rgbs)  # [n, s, c, h, w]
        logits = torch.sigmoid(logis)
        mask = torch.round(logits).float()
        if self.is_edge:
            edge_mask, eroded_mask = self.preprocess(sils)

            # Gait Synthesis
            new_logits = edge_mask*logits+eroded_mask*sils

            if self.align:
                cropped_logits = self.gait_align(
                    new_logits, sils, ratios)
            else:
                cropped_logits = self.resize(new_logits)
        else:
            if self.align:
                cropped_logits = self.gait_align(
                    logits, mask, ratios)
            else:
                cropped_logits = self.resize(logits)
        _, c, H, W = cropped_logits.size()
        cropped_logits = cropped_logits.view(n, s, H, W)
        retval = super(GaitEdge, self).forward(
            [[cropped_logits], labs, None, None, seqL])
        retval['training_feat']['bce'] = {'logits': logits, 'labels': sils}
        retval['visual_summary']['image/roi'] = cropped_logits.view(
            n*s, 1, H, W)

        return retval

System information (version)

• Pytorch = 1.6.0
• Operating System / Platform = Windows 11
• Cuda = 10.1.243

Detailed description

The problem shows when I run into my computer with the above system information. I create a new conda env and clone this code in the env. But I cannot run the code and the problems are below: (opengait) C:\Users\Lenovo\OpenGait>set CUDA_VISIBLE_DEVICES=1 & python -m torch.distributed.launch --nproc_per_node=2 lib/main.py --cfgs ./config/baseline.yaml --phase train

Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed.

Traceback (most recent call last): Traceback (most recent call last): File "lib/main.py", line 58, in File "lib/main.py", line 58, in torch.distributed.init_process_group('nccl', init_method='env://') torch.distributed.init_process_group('nccl', init_method='env://') AttributeError: module 'torch.distributed' has no attribute 'init_process_group' AttributeError: module 'torch.distributed' has no attribute 'init_process_group' Traceback (most recent call last): File "C:\Users\Lenovo\anaconda3\envs\opengait\lib\runpy.py", line 194, in _run_module_as_main return _run_code(code, main_globals, None, File "C:\Users\Lenovo\anaconda3\envs\opengait\lib\runpy.py", line 87, in _run_code exec(code, run_globals) File "C:\Users\Lenovo\anaconda3\envs\opengait\lib\site-packages\torch\distributed\launch.py", line 261, in main() File "C:\Users\Lenovo\anaconda3\envs\opengait\lib\site-packages\torch\distributed\launch.py", line 256, in main raise subprocess.CalledProcessError(returncode=process.returncode, subprocess.CalledProcessError: Command '['C:\Users\Lenovo\anaconda3\envs\opengait\python.exe', '-u', 'lib/main.py', '--local_rank=1', '--cfgs', './config/baseline.yaml', '--phase', 'train']' returned non-zero exit status 1.

System information (version)

Detailed description

[2022-02-17 12:42:57] [INFO]: {'dataset_name': 'CASIA-B', 'dataset_root': './dataset_output', 'num_workers': 1, 'dataset_partition': './misc/partitions/CASIA-B_include_005.json', 'remove_no_gallery': False, 'cache': False, 'test_dataset_name': 'CASIA-B'} [2022-02-17 12:42:57] [INFO]: -------- Test Pid List -------- [2022-02-17 12:42:57] [INFO]: ['075'] [2022-02-17 12:43:00] [INFO]: Restore Parameters from output/CASIA-B/Baseline/Baseline/checkpoints/Baseline-60000.pt !!! [2022-02-17 12:43:00] [INFO]: Parameters Count: 3.77914M [2022-02-17 12:43:00] [INFO]: Model Initialization Finished! Transforming: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 110/110 [00:01<00:00, 76.67it/s] Traceback (most recent call last): File "lib/main.py", line 70, in run_model(cfgs, training) File "lib/main.py", line 55, in run_model Model.run_test(model) File "/home/lalaland/PycharmProjects/OpenGait_/lib/modeling/base_model.py", line 470, in run_test return eval_func(info_dict, dataset_name, **valid_args) File "/home/lalaland/PycharmProjects/OpenGait_/lib/utils/evaluation.py", line 79, in identification 0) * 100 / dist.shape[0], 2) ValueError: could not broadcast input array from shape (4,) into shape (5,) ERROR:torch.distributed.elastic.multiprocessing.api:failed (exitcode: 1) local_rank: 0 (pid: 10590) of binary: /home/lalaland/anaconda3/envs/torch/bin/python Traceback (most recent call last): File "/home/lalaland/anaconda3/envs/torch/lib/python3.7/runpy.py", line 193, in _run_module_as_main "main", mod_spec) File "/home/lalaland/anaconda3/envs/torch/lib/python3.7/runpy.py", line 85, in _run_code exec(code, run_globals) File "/home/lalaland/anaconda3/envs/torch/lib/python3.7/site-packages/torch/distributed/launch.py", line 193, in main() File "/home/lalaland/anaconda3/envs/torch/lib/python3.7/site-packages/torch/distributed/launch.py", line 189, in main launch(args) File "/home/lalaland/anaconda3/envs/torch/lib/python3.7/site-packages/torch/distributed/launch.py", line 174, in launch run(args) File "/home/lalaland/anaconda3/envs/torch/lib/python3.7/site-packages/torch/distributed/run.py", line 713, in run )(*cmd_args) File "/home/lalaland/anaconda3/envs/torch/lib/python3.7/site-packages/torch/distributed/launcher/api.py", line 131, in call return launch_agent(self._config, self._entrypoint, list(args)) File "/home/lalaland/anaconda3/envs/torch/lib/python3.7/site-packages/torch/distributed/launcher/api.py", line 261, in launch_agent failures=result.failures, torch.distributed.elastic.multiprocessing.errors.ChildFailedError:

lib/main.py FAILED

Failures: <NO_OTHER_FAILURES>

Root Cause (first observed failure): [0]: time : 2022-02-17_12:43:06 host : lalaland-Predator-PH317-55 rank : 0 (local_rank: 0) exitcode : 1 (pid: 10590) error_file: <N/A> traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html

https://github.com/ShiqiYu/OpenGait/blob/49cbc44069878210e11117697be507921db1e3fa/lib/modeling/modules.py#L34 这个函数的最后 return x.view(*_)是不是相当于 return x.view(n, s, c, h ,w)？ 如果这么说的话，这个函数没有改变什么?到底发挥了什么作用？没有看懂，望指点

I try GaitGL on OUMVLP dataset, 6000 id for training and rest for teting, using deafault config with Tesla v100*8, it's cost 165 seconds for each 100 iters. if I want 10 epochs, time = 10(epoch) x 130000(seqs) / 8(bs) / 100 * 165 = 3.1 days.

I guess computing triplet loss cost might cost lot of time, I'm tring to modify the train procedure to, triplet loss on take effect at latter epochs, while early epochs only compute id loss, namely softmaxloss.

Is there any other methods to speed up?

thxs

System information (version)

• Pytorch => 1.11
• Operating System / Platform => Ubuntu 20.04
• Cuda => 11.3

Detailed description

I'm trying to run GREW pretreatment code but it generates no GREW-pkl folder at the end of the process. I debugged myself and checked if the --dataset flag is set properly and the to_pickle list size before saving the pickle file. The flag is well set but the size of the list is always 0.

I downloaded the GREW dataset from the link you guys sent me and made de GREW-rearranged folder using the code provided. I'll keep investigating what is causing such an error and if I find I'll set a fixing PR.

Issue submission checklist

• [x] I checked the problem with documentation, FAQ, issues, and have not found solution.

Hi, https://github.com/ShiqiYu/OpenGait/blob/49cbc44069878210e11117697be507921db1e3fa/lib/modeling/modules.py#L61 I guess it means the length of the sequence .What is theseqL[0] means? By the way, what is the shape of the seqL? What does the each dimension of the seqL correspond to?

我的运行命令没有反应 CUDA_VISIBLE_DEVICES=0 python -m torch.distributed.launch --nproc_per_node=1 lib/main.py --cfgs ./config/baseline.yaml --phase train 请问baseline.yaml该怎么配置

System information (version)

• Pytorch => :grey_question:
• Operating System / Platform => :grey_question:
• Cuda => :grey_question:

Detailed description

Steps to reproduce

Issue submission checklist

• [ ] I checked the problem with documentation, FAQ, issues, and have not found solution.

1. new config files brought by Gait3D have some typos
2. The old LossAggregator is a basic python class that cannot register parameters to the base_model. It is inconvenient to train models with those losses that require parameters, such as center loss.
   Therefore, it seems a better way that registers LossAggregator as an nn.Module and uses nn.ModuleDict to organize all losses. In this new version, LossAggregator can be indexed like a regular Python dictionary (keep it the same as the current version), but the modules it contains are properly registered and will be visible by all Module methods. All parameters registered in losses can be accessed by the method 'self.parameters()', enabling they can be trained properly.

After training GaitGL for 80000 epochs, I test GaitGL by running "CUDA_VISIBLE_DEVICES=0 python -m torch.distributed.launch --master_port 12345 --nproc_per_node=1 opengait/main.py --cfgs ./config/gaitgl/gaitgl.yaml --phase test", but get "ValueError: The input size of each GPU must be 1 in testing mode, but got 4!"

System information (version)

• Pytorch => :grey_question:
• Operating System / Platform => :grey_question:
• Cuda => :grey_question:

Detailed description

Steps to reproduce

Issue submission checklist

• [ ] I checked the problem with documentation, FAQ, issues, and have not found solution.