[RLlib] - Fix numerical overflow in gradient clipping for (many) large gradients #45055
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…ring values or summing many large values results in +/- infinity. As we clip by multiplying with a clipping coefficient instead of overriding values inside of the gradients tensors this modification allows to clip very large gradients. Signed-off-by: Simon Zehnder <simon.zehnder@gmail.com>
Signed-off-by: Simon Zehnder <simon.zehnder@gmail.com>
Signed-off-by: Simon Zehnder <simon.zehnder@gmail.com>
Signed-off-by: Simon Zehnder <simon.zehnder@gmail.com>
sven1977
reviewed
May 2, 2024
| @@ -94,6 +95,29 @@ def test_copy_torch_tensors(self): | |||
| all(copied_tensor.detach().numpy() == tensor.detach().cpu().numpy()) | |||
| ) | |||
|
|
|||
| def test_large_gradients_clipping(self): | |||
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Nice! Thanks for creating this important test case!
simonsays1980
requested review from
avnishn,
ArturNiederfahrenhorst,
maxpumperla and
kouroshHakha
as code owners
sven1977
reviewed
May 2, 2024
rllib/utils/torch_utils.py
Outdated
| if torch.logical_or(total_norm.isnan(), total_norm.isinf()): | ||
| raise RuntimeError( | ||
| f"The total norm of order {norm_type} for gradients from " | ||
| "`parameters` is non-finite, so it cannot be clipped. " | ||
| ) | ||
| clip_coef = grad_clip / (total_norm + 1e-6) | ||
| clip_coef = grad_clip / torch.maximum( | ||
| torch.tensor(grad_clip), total_norm + 1e-6 |
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Two questions:
- Would this
torch.tensor()pose a danger when on another device? GPU? - Can we add a comment here (or enhance the one below) explaining why we compute the coeff like this? What are the expected final values of the coeff (between 0.0 and 1.0)?
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Good catch! Yes, let's put the tensor on the device we have extracted before to be save. I will add then a note why we want the coefficient not larger than 1.0.
sven1977
approved these changes
May 2, 2024
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Looks great! Thanks for fixing this very important piece of code @simonsays1980 . Just 2 nits and questions before we can merge.
Signed-off-by: Simon Zehnder <simon.zehnder@gmail.com>
sven1977
reviewed
May 2, 2024
| clip_coef = grad_clip / (total_norm + 1e-6) | ||
| # We do want the coefficient to be in between 0.0 and 1.0, therefore | ||
| # if the global_norm is smaller than the clip value, we use the clip value | ||
| # as normalization constant. |
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Perfect, thanks for making this comment much more clear!
|
Looks great, let's merge once tests pass ... |
harborn
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May 8, 2024
…lipping in case of (many) large gradient matrices. (ray-project#45055)
peytondmurray
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May 13, 2024
…lipping in case of (many) large gradient matrices. (ray-project#45055) Signed-off-by: pdmurray <peynmurray@gmail.com>
ryanaoleary
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Jun 6, 2024
…lipping in case of (many) large gradient matrices. (ray-project#45055) Signed-off-by: Ryan O'Leary <ryanaoleary@google.com>
ryanaoleary
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Jun 7, 2024
…lipping in case of (many) large gradient matrices. (ray-project#45055)
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Why are these changes needed?
Large gradients and many of these could lead to numerical overflow when computing their l2-norm in
torch_utils.clip_gradients(using the "global_norm"). This is counterproductive as a user wants to clip such gradients and instead runs into numerical overflow because of clipping gradients.This PR proposes small changes to turn
infandneginfvalues returned from norms to10e8and-10e8, respectively. This does not harm gradients themselves (if these for example were alreadyinf/neginfb/c we clip gradients by multiplication and not overriding values).Related issue number
Checks
git commit -s) in this PR.scripts/format.shto lint the changes in this PR.method in Tune, I've added it in
doc/source/tune/api/under thecorresponding
.rstfile.