BrokenPipeError occurs with wandb option
Thx for the great work.
I was running the toy_experiment with the lego data, expect that I ran colmap and then the data generation scripts on a dataset which I've downloaded long time ago for NeRF. So the data I used might be different from the one provided in this repo.
The toy experiment rans well, although the background remains. Issue occurs when I tried using the --wandb option. Data loaded, the communication with wandb website was fine too. Everything went fine until the 4th epoch of training. An error rised with "BrokenPipeError: [Errno 32] Broken Pipe". It tracked back to the torch.distributed.elastic.multiprocessing.error.ChildFailedError.
Does anyone have the same issue?
Hi @ZirongChan could you post the full error log? Thanks!
Hi @ZirongChan could you post the full error log? Thanks!
thx for your reply, @chenhsuanlin
Of course, the following is the log output in terminal: torchrun --nproc_per_node=1 train.py --logdir=logs/nerf_synthesis/lego_wandb --config=projects/neuralangelo/configs/custom/lego.yaml --show_pbar --wandb Training with 1 GPUs. Using random seed 0 Make folder logs/nerf_synthesis/lego_wandb
-
checkpoint:
- save_epoch: 9999999999
- save_iter: 20000
- save_latest_iter: 9999999999
- save_period: 9999999999
- strict_resume: True
-
cudnn:
- benchmark: True
- deterministic: False
-
data:
- name: dummy
- num_images: None
- num_workers: 4
- preload: True
- readjust:
- center: [0.0, 0.0, 0.0]
- scale: 1.0
- root: ./dataset/nerf_synthesis/lego
- train:
- batch_size: 2
- image_size: [800, 800]
- subset: None
- type: projects.neuralangelo.data
- use_multi_epoch_loader: True
- val:
- batch_size: 2
- image_size: [300, 300]
- max_viz_samples: 16
- subset: 4
-
image_save_iter: 9999999999
-
inference_args:
-
local_rank: 0
-
logdir: logs/nerf_synthesis/lego_wandb
-
logging_iter: 9999999999999
-
max_epoch: 9999999999
-
max_iter: 500000
-
metrics_epoch: None
-
metrics_iter: None
-
model:
- appear_embed:
- dim: 8
- enabled: False
- background:
- enabled: True
- encoding:
- levels: 10
- type: fourier
- encoding_view:
- levels: 3
- type: spherical
- mlp:
- activ: relu
- activ_density: softplus
- activ_density_params:
- activ_params:
- hidden_dim: 256
- hidden_dim_rgb: 128
- num_layers: 8
- num_layers_rgb: 2
- skip: [4]
- skip_rgb: []
- view_dep: True
- white: False
- object:
- rgb:
- encoding_view:
- levels: 3
- type: spherical
- mlp:
- activ: relu_
- activ_params:
- hidden_dim: 256
- num_layers: 4
- skip: []
- weight_norm: True
- mode: idr
- encoding_view:
- s_var:
- anneal_end: 0.1
- init_val: 3.0
- sdf:
- encoding:
- coarse2fine:
- enabled: True
- init_active_level: 4
- step: 5000
- hashgrid:
- dict_size: 22
- dim: 8
- max_logres: 11
- min_logres: 5
- range: [-2, 2]
- levels: 16
- type: hashgrid
- coarse2fine:
- gradient:
- mode: numerical
- taps: 4
- mlp:
- activ: softplus
- activ_params:
- beta: 100
- geometric_init: True
- hidden_dim: 256
- inside_out: False
- num_layers: 1
- out_bias: 0.5
- skip: []
- weight_norm: True
- encoding:
- rgb:
- render:
- num_sample_hierarchy: 4
- num_samples:
- background: 32
- coarse: 64
- fine: 16
- rand_rays: 512
- stratified: True
- type: projects.neuralangelo.model
- appear_embed:
-
nvtx_profile: False
-
optim:
- fused_opt: False
- params:
- lr: 0.001
- weight_decay: 0.01
- sched:
- gamma: 10.0
- iteration_mode: True
- step_size: 9999999999
- two_steps: [300000, 400000]
- type: two_steps_with_warmup
- warm_up_end: 5000
- type: AdamW
-
pretrained_weight: None
-
source_filename: projects/neuralangelo/configs/custom/lego.yaml
-
speed_benchmark: False
-
test_data:
- name: dummy
- num_workers: 0
- test:
- batch_size: 1
- is_lmdb: False
- roots: None
- type: imaginaire.datasets.images
-
timeout_period: 9999999
-
trainer:
- amp_config:
- backoff_factor: 0.5
- enabled: False
- growth_factor: 2.0
- growth_interval: 2000
- init_scale: 65536.0
- ddp_config:
- find_unused_parameters: False
- static_graph: True
- depth_vis_scale: 0.5
- ema_config:
- beta: 0.9999
- enabled: False
- load_ema_checkpoint: False
- start_iteration: 0
- grad_accum_iter: 1
- image_to_tensorboard: False
- init:
- gain: None
- type: none
- loss_weight:
- curvature: 0.0005
- eikonal: 0.1
- render: 1.0
- type: projects.neuralangelo.trainer
- amp_config:
-
validation_iter: 5000
-
wandb_image_iter: 10000
-
wandb_scalar_iter: 100 cudnn benchmark: True cudnn deterministic: False Setup trainer. Using random seed 0 model parameter count: 366,702,732 Initialize model weights using type: none, gain: None Using random seed 0 Allow TensorFloat32 operations on supported devices Train dataset length: 61
Val dataset length: 4
Training from scratch. Initialize wandb wandb: Currently logged in as: chzirong. Usewandb login --reloginto force relogin wandb: wandb version 0.15.9 is available! To upgrade, please run: wandb: $ pip install wandb --upgrade wandb: Tracking run with wandb version 0.15.8 wandb: Run data is saved locally in logs/nerf_synthesis/lego_wandb/wandb/run-20230829_022555-ox3ubipj wandb: Runwandb offlineto turn off syncing. wandb: Syncing run lego_wandb wandb: ⭐ View project at https://wandb.ai/chzirong/default wandb: 🚀 View run at https://wandb.ai/chzirong/default/runs/ox3ubipj Evaluating with 4 samples.
Epoch: 1, total time: 3.859701.
Epoch: 2, total time: 3.737751.
Epoch: 3, total time: 3.760936.
Traceback (most recent call last):
File "/zhanghuaimin01/Workspace/neuralangelo/train.py", line 104, inmain() File "/zhanghuaimin01/Workspace/neuralangelo/train.py", line 93, in main trainer.train(cfg, File "/zhanghuaimin01/Workspace/neuralangelo/projects/neuralangelo/trainer.py", line 107, in train super().train(cfg, data_loader, single_gpu, profile, show_pbar) File "/zhanghuaimin01/Workspace/neuralangelo/projects/nerf/trainers/base.py", line 115, in train super().train(cfg, data_loader, single_gpu, profile, show_pbar) File "/zhanghuaimin01/Workspace/neuralangelo/imaginaire/trainers/base.py", line 512, in train self.end_of_iteration(data, current_epoch, current_iteration) File "/zhanghuaimin01/Workspace/neuralangelo/imaginaire/trainers/base.py", line 319, in end_of_iteration self._end_of_iteration(data, current_epoch, current_iteration) File "/zhanghuaimin01/Workspace/neuralangelo/projects/nerf/trainers/base.py", line 47, in _end_of_iteration self.log_wandb_scalars(data, mode="train") File "/zhanghuaimin01/Workspace/neuralangelo/imaginaire/utils/distributed.py", line 72, in wrapper return func(*args, **kwargs) File "/zhanghuaimin01/Workspace/neuralangelo/projects/neuralangelo/trainer.py", line 75, in log_wandb_scalars super().log_wandb_scalars(data, mode=mode) File "/zhanghuaimin01/Workspace/neuralangelo/imaginaire/utils/distributed.py", line 72, in wrapper return func(*args, **kwargs) File "/zhanghuaimin01/Workspace/neuralangelo/projects/nerf/trainers/base.py", line 84, in log_wandb_scalars wandb.log(scalars, step=self.current_iteration) File "/root/anaconda3/envs/neuralangelo/lib/python3.9/site-packages/wandb/sdk/wandb_run.py", line 390, in wrapper return func(self, *args, **kwargs) File "/root/anaconda3/envs/neuralangelo/lib/python3.9/site-packages/wandb/sdk/wandb_run.py", line 341, in wrapper_fn return func(self, *args, **kwargs) File "/root/anaconda3/envs/neuralangelo/lib/python3.9/site-packages/wandb/sdk/wandb_run.py", line 331, in wrapper return func(self, *args, **kwargs) File "/root/anaconda3/envs/neuralangelo/lib/python3.9/site-packages/wandb/sdk/wandb_run.py", line 1752, in log self._log(data=data, step=step, commit=commit) File "/root/anaconda3/envs/neuralangelo/lib/python3.9/site-packages/wandb/sdk/wandb_run.py", line 1527, in _log self._partial_history_callback(data, step, commit) File "/root/anaconda3/envs/neuralangelo/lib/python3.9/site-packages/wandb/sdk/wandb_run.py", line 1397, in _partial_history_callback self._backend.interface.publish_partial_history( File "/root/anaconda3/envs/neuralangelo/lib/python3.9/site-packages/wandb/sdk/interface/interface.py", line 653, in publish_partial_history self._publish_partial_history(partial_history) File "/root/anaconda3/envs/neuralangelo/lib/python3.9/site-packages/wandb/sdk/interface/interface_shared.py", line 89, in _publish_partial_history self._publish(rec) File "/root/anaconda3/envs/neuralangelo/lib/python3.9/site-packages/wandb/sdk/interface/interface_sock.py", line 51, in _publish self._sock_client.send_record_publish(record) File "/root/anaconda3/envs/neuralangelo/lib/python3.9/site-packages/wandb/sdk/lib/sock_client.py", line 221, in send_record_publish self.send_server_request(server_req) File "/root/anaconda3/envs/neuralangelo/lib/python3.9/site-packages/wandb/sdk/lib/sock_client.py", line 155, in send_server_request self._send_message(msg) File "/root/anaconda3/envs/neuralangelo/lib/python3.9/site-packages/wandb/sdk/lib/sock_client.py", line 152, in _send_message self._sendall_with_error_handle(header + data) File "/root/anaconda3/envs/neuralangelo/lib/python3.9/site-packages/wandb/sdk/lib/sock_client.py", line 130, in _sendall_with_error_handle sent = self._sock.send(data) BrokenPipeError: [Errno 32] Broken pipe wandb: While tearing down the service manager. The following error has occurred: [Errno 32] Broken pipe Exception in thread ChkStopThr: Traceback (most recent call last): File "/root/anaconda3/envs/neuralangelo/lib/python3.9/threading.py", line 980, in _bootstrap_inner self.run() File "/root/anaconda3/envs/neuralangelo/lib/python3.9/threading.py", line 917, in run self._target(*self._args, **self._kwargs) File "/root/anaconda3/envs/neuralangelo/lib/python3.9/site-packages/wandb/sdk/wandb_run.py", line 274, in check_stop_status self._loop_check_status( File "/root/anaconda3/envs/neuralangelo/lib/python3.9/site-packages/wandb/sdk/wandb_run.py", line 212, in _loop_check_status local_handle = request() File "/root/anaconda3/envs/neuralangelo/lib/python3.9/site-packages/wandb/sdk/interface/interface.py", line 856, in deliver_stop_status Exception in thread return self._deliver_stop_status(status) File "/root/anaconda3/envs/neuralangelo/lib/python3.9/site-packages/wandb/sdk/interface/interface_shared.py", line 594, in _deliver_stop_status NetStatThr: return self._deliver_record(record) File "/root/anaconda3/envs/neuralangelo/lib/python3.9/site-packages/wandb/sdk/interface/interface_shared.py", line 569, in _deliver_record Traceback (most recent call last): handle = mailbox._deliver_record(record, interface=self) File "/root/anaconda3/envs/neuralangelo/lib/python3.9/site-packages/wandb/sdk/lib/mailbox.py", line 455, in _deliver_record File "/root/anaconda3/envs/neuralangelo/lib/python3.9/threading.py", line 980, in _bootstrap_inner interface._publish(record) File "/root/anaconda3/envs/neuralangelo/lib/python3.9/site-packages/wandb/sdk/interface/interface_sock.py", line 51, in _publish self.run() File "/root/anaconda3/envs/neuralangelo/lib/python3.9/threading.py", line 917, in run self._sock_client.send_record_publish(record) File "/root/anaconda3/envs/neuralangelo/lib/python3.9/site-packages/wandb/sdk/lib/sock_client.py", line 221, in send_record_publish self._target(*self._args, **self._kwargs) File "/root/anaconda3/envs/neuralangelo/lib/python3.9/site-packages/wandb/sdk/wandb_run.py", line 256, in check_network_status self.send_server_request(server_req) File "/root/anaconda3/envs/neuralangelo/lib/python3.9/site-packages/wandb/sdk/lib/sock_client.py", line 155, in send_server_request self._loop_check_status( File "/root/anaconda3/envs/neuralangelo/lib/python3.9/site-packages/wandb/sdk/wandb_run.py", line 212, in _loop_check_status self._send_message(msg)
local_handle = request() File "/root/anaconda3/envs/neuralangelo/lib/python3.9/site-packages/wandb/sdk/lib/sock_client.py", line 152, in _send_messageFile "/root/anaconda3/envs/neuralangelo/lib/python3.9/site-packages/wandb/sdk/interface/interface.py", line 864, in deliver_network_status self._sendall_with_error_handle(header + data)
return self._deliver_network_status(status) File "/root/anaconda3/envs/neuralangelo/lib/python3.9/site-packages/wandb/sdk/lib/sock_client.py", line 130, in _sendall_with_error_handleFile "/root/anaconda3/envs/neuralangelo/lib/python3.9/site-packages/wandb/sdk/interface/interface_shared.py", line 610, in _deliver_network_status sent = self._sock.send(data) BrokenPipeErrorreturn self._deliver_record(record): [Errno 32] Broken pipe File "/root/anaconda3/envs/neuralangelo/lib/python3.9/site-packages/wandb/sdk/interface/interface_shared.py", line 569, in _deliver_record
handle = mailbox._deliver_record(record, interface=self) File "/root/anaconda3/envs/neuralangelo/lib/python3.9/site-packages/wandb/sdk/lib/mailbox.py", line 455, in _deliver_record interface._publish(record) File "/root/anaconda3/envs/neuralangelo/lib/python3.9/site-packages/wandb/sdk/interface/interface_sock.py", line 51, in _publish self._sock_client.send_record_publish(record) File "/root/anaconda3/envs/neuralangelo/lib/python3.9/site-packages/wandb/sdk/lib/sock_client.py", line 221, in send_record_publish self.send_server_request(server_req) File "/root/anaconda3/envs/neuralangelo/lib/python3.9/site-packages/wandb/sdk/lib/sock_client.py", line 155, in send_server_request self._send_message(msg) File "/root/anaconda3/envs/neuralangelo/lib/python3.9/site-packages/wandb/sdk/lib/sock_client.py", line 152, in _send_message self._sendall_with_error_handle(header + data) File "/root/anaconda3/envs/neuralangelo/lib/python3.9/site-packages/wandb/sdk/lib/sock_client.py", line 130, in _sendall_with_error_handle sent = self._sock.send(data) BrokenPipeError: [Errno 32] Broken pipe ERROR:torch.distributed.elastic.multiprocessing.api:failed (exitcode: 1) local_rank: 0 (pid: 63851) of binary: /root/anaconda3/envs/neuralangelo/bin/python Traceback (most recent call last): File "/root/anaconda3/envs/neuralangelo/bin/torchrun", line 8, in
sys.exit(main()) File "/root/anaconda3/envs/neuralangelo/lib/python3.9/site-packages/torch/distributed/elastic/multiprocessing/errors/init.py", line 346, in wrapper return f(*args, **kwargs) File "/root/anaconda3/envs/neuralangelo/lib/python3.9/site-packages/torch/distributed/run.py", line 794, in main run(args) File "/root/anaconda3/envs/neuralangelo/lib/python3.9/site-packages/torch/distributed/run.py", line 785, in run elastic_launch( File "/root/anaconda3/envs/neuralangelo/lib/python3.9/site-packages/torch/distributed/launcher/api.py", line 134, in call return launch_agent(self._config, self._entrypoint, list(args)) File "/root/anaconda3/envs/neuralangelo/lib/python3.9/site-packages/torch/distributed/launcher/api.py", line 250, in launch_agent raise ChildFailedError( torch.distributed.elastic.multiprocessing.errors.ChildFailedError: ============================================================ train.py FAILED
Failures: <NO_OTHER_FAILURES>
Root Cause (first observed failure): [0]: time : 2023-08-29_02:26:52 host : a0q74jbdps9k3-0 rank : 0 (local_rank: 0) exitcode : 1 (pid: 63851) error_file: <N/A> traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
I will also paste the content of the "debug-internal.log" file: 2023-08-29 02:25:55,696 INFO StreamThr :64464 [internal.py:wandb_internal():86] W&B internal server running at pid: 64464, started at: 2023-08-29 02:25:55.694795 2023-08-29 02:25:55,697 DEBUG HandlerThread:64464 [handler.py:handle_request():144] handle_request: status 2023-08-29 02:25:55,700 INFO WriterThread:64464 [datastore.py:open_for_write():85] open: logs/nerf_synthesis/lego_wandb/wandb/run-20230829_022555-ox3ubipj/run-ox3ubipj.wandb 2023-08-29 02:25:55,702 DEBUG SenderThread:64464 [sender.py:send():379] send: header 2023-08-29 02:25:55,775 DEBUG SenderThread:64464 [sender.py:send():379] send: run 2023-08-29 02:26:00,776 DEBUG HandlerThread:64464 [handler.py:handle_request():144] handle_request: keepalive 2023-08-29 02:26:05,778 DEBUG HandlerThread:64464 [handler.py:handle_request():144] handle_request: keepalive 2023-08-29 02:26:08,240 INFO SenderThread:64464 [dir_watcher.py:init():211] watching files in: logs/nerf_synthesis/lego_wandb/wandb/run-20230829_022555-ox3ubipj/files 2023-08-29 02:26:08,240 INFO SenderThread:64464 [sender.py:_start_run_threads():1121] run started: ox3ubipj with start time 1693275955.695242 2023-08-29 02:26:08,240 DEBUG SenderThread:64464 [sender.py:send_request():406] send_request: summary_record 2023-08-29 02:26:08,240 DEBUG HandlerThread:64464 [handler.py:handle_request():144] handle_request: status_report 2023-08-29 02:26:08,242 INFO SenderThread:64464 [sender.py:_save_file():1375] saving file wandb-summary.json with policy end 2023-08-29 02:26:08,248 DEBUG HandlerThread:64464 [handler.py:handle_request():144] handle_request: check_version 2023-08-29 02:26:08,249 DEBUG SenderThread:64464 [sender.py:send_request():406] send_request: check_version 2023-08-29 02:26:09,243 INFO Thread-12 :64464 [dir_watcher.py:_on_file_created():271] file/dir created: logs/nerf_synthesis/lego_wandb/wandb/run-20230829_022555-ox3ubipj/files/wandb-summary.json 2023-08-29 02:26:12,803 DEBUG HandlerThread:64464 [handler.py:handle_request():144] handle_request: run_start 2023-08-29 02:26:12,808 DEBUG HandlerThread:64464 [system_info.py:init():31] System info init 2023-08-29 02:26:12,808 DEBUG HandlerThread:64464 [system_info.py:init():46] System info init done 2023-08-29 02:26:12,808 INFO HandlerThread:64464 [system_monitor.py:start():181] Starting system monitor 2023-08-29 02:26:12,808 INFO SystemMonitor:64464 [system_monitor.py:_start():145] Starting system asset monitoring threads 2023-08-29 02:26:12,808 INFO HandlerThread:64464 [system_monitor.py:probe():201] Collecting system info 2023-08-29 02:26:12,809 INFO SystemMonitor:64464 [interfaces.py:start():190] Started cpu monitoring 2023-08-29 02:26:12,810 INFO SystemMonitor:64464 [interfaces.py:start():190] Started disk monitoring 2023-08-29 02:26:12,810 INFO SystemMonitor:64464 [interfaces.py:start():190] Started gpu monitoring 2023-08-29 02:26:12,811 INFO SystemMonitor:64464 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can it be a problem about my internet connection? or is there an alternative that I can use tensorBoard to visualize the training? thx
This seems to be an issue on the W&B side. We don't support Tensorboard right now, but PRs are welcome if you'd like to help add this support.
This seems to be an issue on the W&B side. We don't support Tensorboard right now, but PRs are welcome if you'd like to help add this support.
It seems to be an issue related to the distributed training. I've also tried setting the --single_gpu flag, it did not work. The error log was still about distributed training, as in the log "raise ChildFailedError( torch.distributed.elastic.multiprocessing.errors.ChildFailedError:" .
Is there any switch somewhere else in the code that I can make sure the distributed training is disabled?
To disable distributed training, you can run python train.py --single_gpu ... instead of torchrun --nproc_per_node=1 train.py ... and it should work.