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I encountered an issue while training the 2D case on Google Colab. Here's the error message:
`/content/Medical-SAM2/sam2_train/modeling/sam/transformer.py:22: UserWarning: Flash Attention is disabled as it requires a GPU with Ampere (8.0) CUDA capability. OLD_GPU, USE_FLASH_ATTN, MATH_KERNEL_ON = get_sdpa_settings() INFO:root:Namespace(net='sam2', encoder='vit_b', exp_name='REFUGE_MedSAM2', vis=True, train_vis=False, prompt='bbox', prompt_freq=2, pretrain=None, val_freq=1, gpu=True, gpu_device=0, image_size=1024, out_size=1024, distributed='none', dataset='REFUGE', sam_ckpt='./checkpoints/sam2_hiera_small.pt', sam_config='sam2_hiera_s', video_length=2, b=4, lr=0.0001, weights=0, multimask_output=1, memory_bank_size=16, data_path='/content/Medical-SAM2/REFUGE', path_helper={'prefix': 'logs/REFUGE_MedSAM2_2024_09_30_12_34_25', 'ckpt_path': 'logs/REFUGE_MedSAM2_2024_09_30_12_34_25/Model', 'log_path': 'logs/REFUGE_MedSAM2_2024_09_30_12_34_25/Log', 'sample_path': 'logs/REFUGE_MedSAM2_2024_09_30_12_34_25/Samples'}) Namespace(net='sam2', encoder='vit_b', exp_name='REFUGE_MedSAM2', vis=True, train_vis=False, prompt='bbox', prompt_freq=2, pretrain=None, val_freq=1, gpu=True, gpu_device=0, image_size=1024, out_size=1024, distributed='none', dataset='REFUGE', sam_ckpt='./checkpoints/sam2_hiera_small.pt', sam_config='sam2_hiera_s', video_length=2, b=4, lr=0.0001, weights=0, multimask_output=1, memory_bank_size=16, data_path='/content/Medical-SAM2/REFUGE', path_helper={'prefix': 'logs/REFUGE_MedSAM2_2024_09_30_12_34_25', 'ckpt_path': 'logs/REFUGE_MedSAM2_2024_09_30_12_34_25/Model', 'log_path': 'logs/REFUGE_MedSAM2_2024_09_30_12_34_25/Log', 'sample_path': 'logs/REFUGE_MedSAM2_2024_09_30_12_34_25/Samples'}) Traceback (most recent call last): File "/content/Medical-SAM2/train_2d.py", line 124, in <module> main() File "/content/Medical-SAM2/train_2d.py", line 97, in main tol, (eiou, edice) = function.validation_sam(args, nice_test_loader, epoch, net, writer) File "/content/Medical-SAM2/func_2d/function.py", line 335, in validation_sam vision_feats_temp = vision_feats[-1].permute(1, 0, 2).view(B, -1, 64, 64) RuntimeError: view size is not compatible with input tensor's size and stride (at least one dimension spans across two contiguous subspaces). Use .reshape(...) instead.`
Could you provide guidance on how to resolve this issue or any suggestions to address this dimensionality problem?
Thanks for your support.
The text was updated successfully, but these errors were encountered:
I get the same error. Did you fix that?
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I encountered an issue while training the 2D case on Google Colab. Here's the error message:
Could you provide guidance on how to resolve this issue or any suggestions to address this dimensionality problem?
Thanks for your support.
The text was updated successfully, but these errors were encountered: