Comments (2)
perslev
commented on June 2, 2024
Hi,
This is likely because the mpunet still relies on the old tf.keras multi_gpu_model function for distributing models across multiple GPUs. I will soon (within the next few days) update to use the proper TensorFlow 2 approach (tf.distribute.MirroredStrategy), which I believe will fix your error.
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perslev
commented on June 2, 2024
Hi,
Could you try and checkout on branch 'v.0.2.5' and see if it that works for you?
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Related Issues (20)
- [urgent] Inputs to operation AddN_7 of type AddN must have the same size and shape.
- AttributeError: 'UNet' object has no attribute 'loss_functions' HOT 4
- Does it support multi-channel input images? HOT 1
- ValueError: 'bg_value' should be a list of length 'n_channels'. Got [4.0] for n_channels=2 HOT 1
- Input volume is sampled on 2D HOT 2
- Error when trying to train HOT 1
- Does MPU have to install "tensorflow-gpu==2.3.2"? The readme file says that GPU is not required. HOT 1
- Why do we need 'predict_single' in predict.py? HOT 2
- No available GPUs... Sleeping 120 seconds HOT 1
- What is real_space_span? HOT 1
- nan weights, nan validation losses HOT 3
- dataset folder structure
- Could you please provide the pdf of your paper? HOT 1
- my system restarts automatically whenever I start training HOT 1
- Clallbacks: Cannot feed value of shape (16, 128, 128, 1) for Tensor 'conv2d/truediv:0', which has shape '(?, 128, 128, 3)' HOT 7
- Getting ValueError in new environment HOT 1
- Memory Error and Lack of GPU Usage HOT 4
- When training on toy_data, TypeError: can only concatenate list (not "dict") to list HOT 1
- weights can not be broadcast to values. values.rank=3. weights.rank=1. values.shape=(2, 448, 448). weights.shape=(2,). HOT 12
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