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This article mainly introduces "the method of using tensorboard to add pr curve in Pytorch". In the daily operation, I believe that many people have doubts about the method of using tensorboard to add pr curve in Pytorch. Xiaobian consulted all kinds of data and sorted out a simple and easy-to-use method of operation. I hope it will be helpful to answer the question of "adding pr curve with tensorboard in Pytorch". Next, please follow the editor to study!

Code:

From torch.utils.tensorboard import SummaryWriterimport numpy as npnp.random.seed (20200910) labels = np.random.randint (2, size=100) # binary labelpredictions = np.random.rand (100) writer = SummaryWriter () writer.add_pr_curve ('pr_curve pockmarked forest', labels, predictions, 0) writer.close () # tensorboard-- logdir=runs

Show the running results:

At this point, the study on "the method of using tensorboard to add pr curve in Pytorch" is over. I hope to be able to solve everyone's doubts. The collocation of theory and practice can better help you learn, go and try it! If you want to continue to learn more related knowledge, please continue to follow the website, the editor will continue to work hard to bring you more practical articles!

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