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Escape the escape #783

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Feb 8, 2022
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Escape the escape #783

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8 changes: 4 additions & 4 deletions src/orion/algo/pbt/exploit.py
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Original file line number Diff line number Diff line change
Expand Up @@ -171,7 +171,7 @@ class TruncateExploit(BaseExploit):
If the given trial is under a ``truncation_quantile`` compared to all other trials that
has reached the same fidelity level, then a new candidate trial is selected for forking.
The new candidate is selected from a pool of best ``candidate_pool_ratio``\% of the available
The new candidate is selected from a pool of best ``candidate_pool_ratio``\\% of the available
trials at the same fidelity level.
If there are less than ``min_forking_population`` trials that have reached the fidelity level
Expand All @@ -189,7 +189,7 @@ class TruncateExploit(BaseExploit):
candidate is considered for forking. Default: 0.8
candidate_pool_ratio: float, optional
When choosing another candidate for forking, it will be randomly selected from the
best ``candidate_pool_ratio``\% of the available trials. Default: 0.2
best ``candidate_pool_ratio``\\% of the available trials. Default: 0.2
"""

Expand All @@ -208,7 +208,7 @@ def __call__(self, rng, trial, lineages):
If the given trial is under a ``self.truncation_quantile`` compared to all other trials that
has reached the same fidelity level, then a new candidate trial is selected for forking.
The new candidate is selected from a pool of best ``self.candidate_pool_ratio``\% of the
The new candidate is selected from a pool of best ``self.candidate_pool_ratio``\\% of the
available trials at the same fidelity level.
If there are less than ``self.min_forking_population`` trials that have reached the fidelity
Expand Down Expand Up @@ -333,7 +333,7 @@ def __call__(self, rng, trial, lineages):
If the given trial is under a ``self.truncation_quantile`` compared to all other best
trials with lower or equal fidelity level,
then a new candidate trial is selected for forking.
The new candidate is selected from a pool of best ``self.candidate_pool_ratio``\% of the
The new candidate is selected from a pool of best ``self.candidate_pool_ratio``\\% of the
best trials with lower or equal fidelity level. See class description for more
explanation on the rationale.
Expand Down