AttributeError: 'YOLOLayer' object has no attribute 'grid'

[jingweirobot]

python3 train.py --batch-size 8

Apex recommended for faster mixed precision training: https://github.com/NVIDIA/apex Your branch is behind 'origin/master' by 9 commits, and can be fast-forwarded. (use "git pull" to update your local branch)

Namespace(adam=False, batch_size=8, bucket='', cache_images=False, cfg='cfg/yolov3-spp.cfg', data='data/coco2017.data', device='', epochs=1, evolve=False, img_size=[320, 640], multi_scale=False, name='', nosave=False, notest=False, rect=False, resume=False, single_cls=False, weights='weights/yolov3-spp-ultralytics.pt') Using CPU

Start Tensorboard with "tensorboard --logdir=runs", view at http://localhost:6006/ Model Summary: 225 layers, 6.29987e+07 parameters, 6.29987e+07 gradients Optimizer groups: 76 .bias, 76 Conv2d.weight, 73 other Caching labels (117266 found, 1021 missing, 0 empty, 0 duplicate, for 118287 ima Caching labels (4952 found, 48 missing, 0 empty, 0 duplicate, for 5000 images): Image sizes 320 - 640 train, 640 test Using 8 dataloader workers Starting training for 1 epochs...

 Epoch   gpu_mem      GIoU       obj       cls     total   targets  img_size
   0/0        0G      1.95      1.66      0.37      3.98        79       512/home/jingwei/yolov3/utils/layers.py:60: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!

if nx == na: # same shape /home/jingwei/yolov3/models.py:187: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs! if (self.nx, self.ny) != (nx, ny): 0/0 0G 1.95 1.66 0.37 3.98 79 512 Traceback (most recent call last): File "train.py", line 416, in train() # train normally File "train.py", line 298, in train tb_writer.add_graph(model, imgs) # add model to tensorboard File "/home/jingwei/miniconda3/lib/python3.7/site-packages/torch/utils/tensorboard/writer.py", line 707, in add_graph self._get_file_writer().add_graph(graph(model, input_to_model, verbose)) File "/home/jingwei/miniconda3/lib/python3.7/site-packages/torch/utils/tensorboard/_pytorch_graph.py", line 285, in graph trace = torch.jit.trace(model, args) File "/home/jingwei/miniconda3/lib/python3.7/site-packages/torch/jit/init.py", line 882, in trace check_tolerance, _force_outplace, _module_class) File "/home/jingwei/miniconda3/lib/python3.7/site-packages/torch/jit/init.py", line 1034, in trace_module module._c._create_method_from_trace(method_name, func, example_inputs, var_lookup_fn, _force_outplace) File "/home/jingwei/miniconda3/lib/python3.7/site-packages/torch/nn/modules/module.py", line 530, in call result = self._slow_forward(*input, kwargs) File "/home/jingwei/miniconda3/lib/python3.7/site-packages/torch/nn/modules/module.py", line 516, in _slow_forward result = self.forward(*input, *kwargs) File "/home/jingwei/yolov3/models.py", line 238, in forward return self.forward_once(x) File "/home/jingwei/yolov3/models.py", line 290, in forward_once yolo_out.append(module(x, out)) File "/home/jingwei/miniconda3/lib/python3.7/site-packages/torch/nn/modules/module.py", line 530, in call result = self._slow_forward(input, kwargs) File "/home/jingwei/miniconda3/lib/python3.7/site-packages/torch/nn/modules/module.py", line 516, in _slow_forward result = self.forward(*input, **kwargs) File "/home/jingwei/yolov3/models.py", line 212, in forward io[..., :2] = torch.sigmoid(io[..., :2]) + self.grid # xy File "/home/jingwei/miniconda3/lib/python3.7/site-packages/torch/nn/modules/module.py", line 576, in getattr type(self).name, name)) AttributeError: 'YOLOLayer' object has no attribute 'grid'

[jingweirobot]

there is self.training = False ( models.py ). 146 line. I found someone asked you this question. He/She set self.training = False ( models.py ). But it has still the same issue. Could you help me to solve this issue? Thanks a lot.

[glenn-jocher]

Hello, thank you for your interest in our work! This issue seems to lack the minimum requirements for a proper response, or is insufficiently detailed for us to help you. Please note that most technical problems are due to:

• Your changes to the default repository. If your issue is not reproducible in a fresh git clone version of this repository we can not debug it. Before going further run this code and ensure your issue persists:

  sudo rm -rf yolov3  # remove existing
  git clone https://github.com/ultralytics/yolov3 && cd yolov3 # clone latest
  python3 detect.py  # verify detection
  python3 train.py  # verify training (a few batches only)
  # CODE TO REPRODUCE YOUR ISSUE HERE

• Your custom data. If your issue is not reproducible with COCO data we can not debug it. Visit our Custom Training Tutorial for exact details on how to format your custom data. Examine train_batch0.jpg and test_batch0.jpg for a sanity check of training and testing data.
• Your environment. If your issue is not reproducible in a GCP Quickstart Guide VM we can not debug it. Ensure you meet the requirements specified in the README: Unix, MacOS, or Windows with Python >= 3.7, PyTorch >= 1.4 etc. You can also use our Google Colab Notebook and our Docker Image to test your code in a working environment.

If none of these apply to you, we suggest you close this issue and raise a new one using the Bug Report template, providing screenshots and minimum viable code to reproduce your issue. Thank you!