fastaiのplot_confusion_matrixでメモリが足りなくなる
interp.plot_confusion_matrix(figsize=(12,12), dpi=60)
メモリが足りなくなったとき、slice_sizeを変えればいいようだ。
Working with large datasets When working with large datasets, memory problems can arise when computing the confusion matrix. For example, an error can look like this:
RuntimeError: $ Torch: not enough memory: you tried to allocate 64GB. Buy new RAM!
In this case it is possible to force ClassificationInterpretation to compute the confusion matrix for data slices and then aggregate the result by specifying slice_size parameter.
interp.confusion_matrix(slice_size=10) array([[ 970, 40], [ 18, 1010]]) interp.plot_confusion_matrix(slice_size=10)
