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Hi! My question is about computing gradients for each sample in the batch. I reproduced your example with simple neural net, which works exactly fine. However, when using ResNet50 (which has batchnorm, for example) the code produces the following error: AttributeError: 'Parameter' object has no attribute 'grad1'
The text was updated successfully, but these errors were encountered:
Hi @yaroslavvb , thank you very much for this package, does this package support GroupNorm, BatchNorm etc. which are commonly used in res net architectures?
Hi! My question is about computing gradients for each sample in the batch. I reproduced your example with simple neural net, which works exactly fine. However, when using ResNet50 (which has batchnorm, for example) the code produces the following error:
AttributeError: 'Parameter' object has no attribute 'grad1'
The text was updated successfully, but these errors were encountered: