Add SynthID (watermerking by Google DeepMind) #34350
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# Add PT version of the bayesian detector
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| return all_masks, all_g_values | ||
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| def tpr_at_fpr(detector, detector_inputs, w_true, minibatch_size, target_fpr=0.01) -> torch.Tensor: |
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I have no idea what tpr and fpr means, let's either be explicit, or have a small docstring
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| self.beta = torch.nn.Parameter(-2.5 + 0.001 * torch.randn(1, 1, watermarking_depth)) | ||
| self.delta = torch.nn.Parameter(0.001 * torch.randn(1, 1, self.watermarking_depth, watermarking_depth)) |
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these are usually initialized in the _init_weights function rather than here!
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Ihere we init with zeros or empty
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It's not common, but we do have this pattern in other places (e.g.)
(I also have no idea how to set this specific initialization in _init_weights 😅 )
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| # [batch_size, seq_len, watermarking_depth] | ||
| # Long tensor doesn't work with einsum, so we need to switch to the same dtype as self.delta (FP32) | ||
| logits = torch.einsum("ijkl,ijkl->ijk", self.delta, x.type(self.delta.dtype)) + self.beta |
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would be a lot better if we can avoid einsums! 🤗
(i, j, k, l) x (i, j, k, l) -> (i, j, k)
would be:
(i, j, k, 1, l) x (i, j, k, l, 1) -> (i, j, k,1)
so:
self.delta[.., None,:] @ x.transpose(-2,-1)[..., None])
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Good idea!
(the correct form is then (self.delta[.., None,:] @ x[..., None]).squeeze())
ArthurZucker
approved these changes
Oct 23, 2024
BernardZach
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to BernardZach/transformers
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Dec 5, 2024
* Add SynthIDTextWatermarkLogitsProcessor * esolving comments. * Resolving comments. * esolving commits, * Improving SynthIDWatermark tests. * switch to PT version * detector as pretrained model + style * update training + style * rebase * Update logits_process.py * Improving SynthIDWatermark tests. * Shift detector training to wikitext negatives and stabilize with lower learning rate. * Clean up. * in for 7B * cleanup * upport python 3.8. * README and final cleanup. * HF Hub upload and initiaze. * Update requirements for synthid_text. * Adding SynthIDTextWatermarkDetector. * Detector testing. * Documentation changes. * Copyrights fix. * Fix detector api. * ironing out errors * ironing out errors * training checks * make fixup and make fix-copies * docstrings and add to docs * copyright * BC * test docstrings * move import * protect type hints * top level imports * watermarking example * direct imports * tpr fpr meaning * process_kwargs * SynthIDTextWatermarkingConfig docstring * assert -> exception * example updates * no immutable dict (cant be serialized) * pack fn * einsum equivalent * import order * fix test on gpu * add detector example --------- Co-authored-by: Sumedh Ghaisas <sumedhg@google.com> Co-authored-by: Marc Sun <marc@huggingface.co> Co-authored-by: sumedhghaisas2 <138781311+sumedhghaisas2@users.noreply.github.com> Co-authored-by: raushan <raushan@huggingface.co>
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What does this PR do?
Adds SynthID, a watermarking by DeepMind.
https://deepmind.google/technologies/synthid/
Applying watermarking and using a detector is added to
transfomers. Training a detector is added as a research project.