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tensor dimension input error when running 3D N2V #143
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Hi! We will try to have a look in the coming days! In the mean time, you could try with older versions of tensorflow. I am pretty sure the notebook was tested with TF2.10 but not with TF2.13. |
Thank you! I am using a M1 macbook and it only supports TF2.13 to my knowledge. Also I tested the napari-n2v plugins. II used napari 0.4.18 and TF2.13, and napari-n2v 0.1.0. Same issue (tensor dimension error) appeared. |
It seems to be a known M1 problem, but there also seem to be solutions. Could you try the suggestion here: #133? |
Any luck? |
still no luck. I created a new conda environment with tensorflow 2.9.0 and tensorflow-metal 0.5.0. And n2v 0.3.2. I reproduced the error I got earlier (the same as #133 ). 2D works fine still. |
Seems like a For now, training of 3D model on M1/M2 seems possible only on CPU:
|
I had a similar issue when I ran 2D-RGB and it prompted: |
Hello, I encountered this error when running the example 3D training for N2V. The error says: Node: 'model/batch_normalization/FusedBatchNormV3'
2 root error(s) found.
(0) INVALID_ARGUMENT: input must be 4-dimensional[4,32,64,64,32]
[[{{node model/batch_normalization/FusedBatchNormV3}}]]
[[gradient_tape/model/batch_normalization_1/FusedBatchNormGradV3/_184]]
(1) INVALID_ARGUMENT: input must be 4-dimensional[4,32,64,64,32]
[[{{node model/batch_normalization/FusedBatchNormV3}}]]
0 successful operations.
0 derived errors ignored. [Op:__inference_train_function_3323];
It seems it is expecting 2D input, not 3D (5D tensor). And indeed the 2D training example works for me. I am running the example notebook locally. My N2V version: 0.3.2; my tensorflow version: 2.13.0; I am using a M1 macbook.
was this error related to version issue? What would you suggest me to do? Thank you!
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