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dnth / yolov5-deepsparse-blogpost

By the end of this post, you will learn how to: Train a SOTA YOLOv5 model on your own data. Sparsify the model using SparseML quantization aware training, sparse transfer learning, and one-shot quantization. Export the sparsified model and run it using the DeepSparse engine at insane speeds. P/S: The end result - YOLOv5 on CPU at 180+ FPS using on
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New issue appeared today during running train.py file #16

Open abirsince92 opened 1 year ago

abirsince92 commented 1 year ago

Got the error during running the train.py file:

Transferred 308/361 items from yolov5s.pt Scaled weight_decay = 0.0005 optimizer: Adam with parameter groups 59 weight (no decay), 62 weight, 62 bias albumentations: Blur(always_apply=False, p=0.01, blur_limit=(3, 7)), MedianBlur(always_apply=False, p=0.01, blur_limit=(3, 7)), ToGray(always_apply=False, p=0.01), CLAHE(always_apply=False, p=0.01, clip_limit=(1, 4.0), tile_grid_size=(8, 8)) train: Scanning '/content/data/train/labels' images and labels...11402 found, 0 missing, 0 empty, 0 corrupt: 100% 11402/11402 [00:22<00:00, 502.88it/s] train: New cache created: /content/data/train/labels.cache val: Scanning '/content/data/val/labels' images and labels...3801 found, 0 missing, 0 empty, 0 corrupt: 100% 3801/3801 [00:08<00:00, 472.10it/s] val: New cache created: /content/data/val/labels.cache [W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool) [W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool) [W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool) [W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool) Plotting labels to runs/train/exp/labels.jpg...

AutoAnchor: 4.46 anchors/target, 1.000 Best Possible Recall (BPR). Current anchors are a good fit to dataset ✅ Image sizes 640 train, 640 val Using 4 dataloader workers Logging results to runs/train/exp Starting training for 30 epochs... Traceback (most recent call last): File "train.py", line 745, in main(opt) File "train.py", line 641, in main train(opt.hyp, opt, device, callbacks) File "train.py", line 336, in train sparseml_wrapper.initialize_loggers(loggers.logger, loggers.tb, loggers.wandb) File "/content/yolov5-deepsparse-blogpost/yolov5-train/utils/sparse.py", line 97, in initialize_loggers SparsificationGroupLogger( File "/usr/local/lib/python3.8/dist-packages/sparseml/pytorch/utils/logger.py", line 630, in init TensorBoardLogger( File "/usr/local/lib/python3.8/dist-packages/sparseml/pytorch/utils/logger.py", line 443, in init raise tensorboard_import_error File "/usr/local/lib/python3.8/dist-packages/sparseml/pytorch/utils/logger.py", line 30, in from torch.utils.tensorboard import SummaryWriter File "/usr/local/lib/python3.8/dist-packages/torch/utils/tensorboard/init.py", line 4, in LooseVersion = distutils.version.LooseVersion AttributeError: module 'distutils' has no attribute 'version'

dnth commented 1 year ago

@abirsince92 have you tried running it on Colab? How do I produce this error on my machine?

abirsince92 commented 1 year ago

Sir, Today I got this error on Colab notebook after running the train.py file, yesterday it was fine...