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mikaylagawareckisvekarssekyondaMeta
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Bump tolerances for per_sample_grads tutorial (#3487)
* [DO NOT MERGE] 2.8 RC Test * Update .jenkins/build.sh * Update .jenkins/build.sh * Update build.sh * Update .jenkins/build.sh * Update dqn_with_rnn_tutorial.py https://github.com/pytorch/tutorials/actions/runs/16279151183/job/45965049712?pr=3463#step:9:8173 * Update dqn_with_rnn_tutorial.py * Update * Update dqn_with_rnn_tutorial.py Resetting changes in favor of: #3462 * Bump tolerances for per_sample_grads tutorial * Update build.sh --------- Co-authored-by: Svetlana Karslioglu <[email protected]> Co-authored-by: sekyondaMeta <[email protected]>
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intermediate_source/per_sample_grads.py

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@@ -169,7 +169,7 @@ def compute_loss(params, buffers, sample, target):
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# results of hand processing each one individually:
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for per_sample_grad, ft_per_sample_grad in zip(per_sample_grads, ft_per_sample_grads.values()):
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assert torch.allclose(per_sample_grad, ft_per_sample_grad, atol=3e-3, rtol=1e-5)
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assert torch.allclose(per_sample_grad, ft_per_sample_grad, atol=1.2e-1, rtol=1e-5)
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######################################################################
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# A quick note: there are limitations around what types of functions can be

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