Model.eval() gives incorrect loss for model with batchnorm layers

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I have the same problem.

I’m trying to load caffe weights in a pytorch model with batchnorm layers, each time I load the weights from the caffemodel file, the result for the same input is different even in eval mode.

I’m actually updating the running_mean and running_var from the caffemodel weights, so there shouldn’t be any issue with bad running_means during inference.