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I want to create a model in nnUNET version 2 with the same architecture as the model created in version 1.
I used the same dataset to create the model from scratch.
However, I noticed slight differences between the 2 created models.
(Both used the default settings)
First, the size of the model: V1:
344M Aug 7 11:44 model_best.model V2:
235M Aug 5 01:21 checkpoint_final.pth
I also noticed differences in the plan files: V1 plans.pkl:
AssertionError: n_conv_per_stage must have as many entries as we have resolution stages. here: 7. n_conv_per_stage: [2, 2, 2, 2, 2, 2]
After that I tried changing the n_conv_per_stage
But without success:
"n_conv_per_stage_encoder": [2, 2, 2, 2, 2, 2,2],
"n_conv_per_stage_decoder": [2, 2, 2, 2, 2, 2]
->
AssertionError: strides must have as many entries as we have resolution stages (n_stages). Important: first entry is recommended to be 1, else we run strided conv drectly on the input
Any ideas on how to implement the V1 configuration in V2?
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I want to create a model in nnUNET version 2 with the same architecture as the model created in version 1.
I used the same dataset to create the model from scratch.
However, I noticed slight differences between the 2 created models.
(Both used the default settings)
First, the size of the model:
V1:
344M Aug 7 11:44 model_best.model
V2:
235M Aug 5 01:21 checkpoint_final.pth
I also noticed differences in the plan files:
V1 plans.pkl:
V2 plans.json:
I tried to change the pool_op_kernel_sizes and conv_kernel_sizes in V2, but it did not work:
Gives:
After that I tried changing the n_conv_per_stage
But without success:
Any ideas on how to implement the V1 configuration in V2?
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