Add unsupervised learning experiments for linear_ntk #83
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jnkm
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Apr 19, 2022
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| #model_pars = flatten(model.parameters()) | ||
| #rand_proj = torch.randn(512, 10).cuda() |
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Probably best to remove the commented code in this file
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| test_images = dataset['test_images'] | ||
| test_targets = dataset['test_angles'] | ||
| #test_ids = dataset['test_people_ids'] |
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| test_images = dataset['test_images'] | ||
| test_targets = dataset['test_angles'] | ||
| #test_ids = dataset['test_people_ids'] |
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Can remove this line
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| #test_ids = dataset['test_people_ids'] |
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| import numpy as np | |||
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| import math | |||
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| import torch | |||
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| import math | |||
jnkm
requested changes
Apr 25, 2022
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| test_images = dataset['test_images'] | ||
| test_targets = dataset['test_angles'] | ||
| #test_ids = dataset['test_people_ids'] |
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| #test_ids = dataset['test_people_ids'] |
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| ###### now train the network | ||
| for i in range(args.epochs): | ||
| #train_epoch(trainloader, net, gaussian_loglikelihood, optimizer) |
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| #train_epoch(trainloader, net, gaussian_loglikelihood, optimizer) |
| #### train the last layer | ||
| f_optimizer = torch.optim.Adam(frozen_net.parameters(), lr = 1e-3, amsgrad=True) | ||
| for i in range(args.adapt_epochs): | ||
| #train_epoch(adaptloader, frozen_net, gaussian_loglikelihood, f_optimizer) |
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| #train_epoch(adaptloader, frozen_net, gaussian_loglikelihood, f_optimizer) |
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| ##### and finally we "fine-tune" the whole net | ||
| for i in range(args.adapt_epochs): | ||
| #train_epoch(trainloader, net, gaussian_loglikelihood, optimizer) |
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Suggested change
| #train_epoch(trainloader, net, gaussian_loglikelihood, optimizer) |
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Adds the code to reproduce Figure 7b (olivetti dataset) and Table 1 (unsupervised to supervised experiments) of https://arxiv.org/pdf/2103.01439.pdf that had not been included in the public version previously.
Let me know if I still need to modify licenses / attribution here.
@shuaitang @pgmoren
By submitting this pull request, I confirm that my contribution is made under the terms of the Apache 2.0 license.