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[keras/optimizer_v2/ftrl.py] Reflect defaults in docstring #44679

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merged 2 commits into from Nov 17, 2020
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[keras/optimizer_v2/ftrl.py] Reflect defaults in docstring #44679

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[tensorflow/python/keras/optimizer_v2/ftrl.py] Reflect defaults in do…
SamuelMarks Nov 8, 2020
abdbeac
[tensorflow/python/keras/optimizer_v2/ftrl.py] Resolve C0301
SamuelMarks Nov 12, 2020
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5 changes: 3 additions & 2 deletions tensorflow/python/keras/optimizer_v2/ftrl.py
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Expand Up @@ -64,16 +64,17 @@ class Ftrl(optimizer_v2.OptimizerV2):
initial_accumulator_value: The starting value for accumulators.
Only zero or positive values are allowed.
l1_regularization_strength: A float value, must be greater than or
equal to zero.
equal to zero. Defaults to 0.0.
l2_regularization_strength: A float value, must be greater than or
equal to zero.
equal to zero. Defaults to 0.0.
name: Optional name prefix for the operations created when applying
gradients. Defaults to `"Ftrl"`.
l2_shrinkage_regularization_strength: A float value, must be greater than
or equal to zero. This differs from L2 above in that the L2 above is a
stabilization penalty, whereas this L2 shrinkage is a magnitude penalty.
When input is sparse shrinkage will only happen on the active weights.
beta: A float value, representing the beta value from the paper.
Defaults to 0.0.
**kwargs: Keyword arguments. Allowed to be one of
`"clipnorm"` or `"clipvalue"`.
`"clipnorm"` (float) clips gradients by norm; `"clipvalue"` (float) clips
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