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01/19 22:48:28 - mmengine - INFO - Checkpoints will be saved to /opt/ml/final-project-level3-cv-17/mmyolo/work_dirs/yolov7_l_syncbn_fast_8x16b-300e_coco. Traceback (most recent call last): File "tools/train.py", line 116, in <module> main() File "tools/train.py", line 112, in main runner.train() File "/opt/conda/envs/final2/lib/python3.8/site-packages/mmengine/runner/runner.py", line 1678, in train model = self.train_loop.run() # type: ignore File "/opt/conda/envs/final2/lib/python3.8/site-packages/mmengine/runner/loops.py", line 90, in run self.run_epoch() File "/opt/conda/envs/final2/lib/python3.8/site-packages/mmengine/runner/loops.py", line 106, in run_epoch self.run_iter(idx, data_batch) File "/opt/conda/envs/final2/lib/python3.8/site-packages/mmengine/runner/loops.py", line 122, in run_iter outputs = self.runner.model.train_step( File "/opt/conda/envs/final2/lib/python3.8/site-packages/mmengine/model/base_model/base_model.py", line 114, in train_step losses = self._run_forward(data, mode='loss') # type: ignore File "/opt/conda/envs/final2/lib/python3.8/site-packages/mmengine/model/base_model/base_model.py", line 314, in _run_forward results = self(**data, mode=mode) File "/opt/conda/envs/final2/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl return forward_call(*input, **kwargs) File "/opt/conda/envs/final2/lib/python3.8/site-packages/mmdet/models/detectors/base.py", line 92, in forward return self.loss(inputs, data_samples) File "/opt/conda/envs/final2/lib/python3.8/site-packages/mmdet/models/detectors/single_stage.py", line 77, in loss x = self.extract_feat(batch_inputs) File "/opt/conda/envs/final2/lib/python3.8/site-packages/mmdet/models/detectors/single_stage.py", line 143, in extract_feat x = self.backbone(batch_inputs) File "/opt/conda/envs/final2/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl return forward_call(*input, **kwargs) File "/opt/ml/final-project-level3-cv-17/mmyolo/mmyolo/models/backbones/base_backbone.py", line 221, in forward x = layer(x) File "/opt/conda/envs/final2/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl return forward_call(*input, **kwargs) File "/opt/conda/envs/final2/lib/python3.8/site-packages/torch/nn/modules/container.py", line 141, in forward input = module(input) File "/opt/conda/envs/final2/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl return forward_call(*input, **kwargs) File "/opt/ml/final-project-level3-cv-17/mmyolo/mmyolo/models/layers/yolo_bricks.py", line 714, in forward x_short = self.short_conv(x) File "/opt/conda/envs/final2/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl return forward_call(*input, **kwargs) File "/opt/conda/envs/final2/lib/python3.8/site-packages/mmcv/cnn/bricks/conv_module.py", line 207, in forward x = self.conv(x) File "/opt/conda/envs/final2/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl return forward_call(*input, **kwargs) File "/opt/conda/envs/final2/lib/python3.8/site-packages/torch/nn/modules/conv.py", line 446, in forward return self._conv_forward(input, self.weight, self.bias) File "/opt/conda/envs/final2/lib/python3.8/site-packages/torch/nn/modules/conv.py", line 442, in _conv_forward return F.conv2d(input, weight, bias, self.stride, RuntimeError: CUDA out of memory. Tried to allocate 508.00 MiB (GPU 0; 31.75 GiB total capacity; 27.35 GiB already allocated; 50.50 MiB free; 27.74 GiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split_size_mb to avoid fragmentation. See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF
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