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Anonymous-submission-repo
2022-10-18 17:33:12 +00:00
parent 2f8f8ba9d8
commit 02d643bc80
3 changed files with 25 additions and 13 deletions
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14
flaml/tune/searcher/blendsearch.py
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@@ -126,10 +126,14 @@ class BlendSearch(Searcher):
- "tolerances"(optional): a dictionary to specify the optimality tolerances on objectives. The keys are the
metric names (provided in "metrics"), and the values are the numerical tolerances values.
E.g.,
```python
lexico_objectives = {"metrics":["error_rate","pred_time"], "modes":["min","min"],
"tolerances":{"error_rate":0.01,"pred_time":0.0}, "targets":{"error_rate":0.0}}
```
```python
lexico_objectives = {
"metrics": ["error_rate", "pred_time"],
"modes": ["min", "min"],
"tolerances": {"error_rate": 0.01, "pred_time": 0.0},
"targets": {"error_rate": 0.0},
}
```
experimental: A bool of whether to use experimental features.
"""
self._eps = SEARCH_THREAD_EPS
@@ -145,7 +149,7 @@ class BlendSearch(Searcher):
self.penalty = PENALTY # penalty term for constraints
self._metric, self._mode = metric, mode
self._use_incumbent_result_in_evaluation = use_incumbent_result_in_evaluation
self.lexico_objectives = lexico_objectives
self.lexico_objectives =
init_config = low_cost_partial_config or {}
if not init_config:
logger.info(

12
flaml/tune/searcher/flow2.py
View File

@@ -83,10 +83,14 @@ class FLOW2(Searcher):
- "tolerances"(optional): a dictionary to specify the optimality tolerances on objectives. The keys are the
metric names (provided in "metrics"), and the values are the numerical tolerances values.
E.g.,
```python
lexico_objectives = {"metrics":["error_rate","pred_time"], "modes":["min","min"],
"tolerances":{"error_rate":0.01,"pred_time":0.0}, "targets":{"error_rate":0.0}}
```
```python
lexico_objectives = {
"metrics": ["error_rate", "pred_time"],
"modes": ["min", "min"],
"tolerances": {"error_rate": 0.01, "pred_time": 0.0},
"targets": {"error_rate": 0.0},
}
```
"""
if mode:
assert mode in ["min", "max"], "`mode` must be 'min' or 'max'."

12
flaml/tune/tune.py
View File

@@ -400,10 +400,14 @@ def run(
- "tolerances"(optional): a dictionary to specify the optimality tolerances on objectives. The keys are the
metric names (provided in "metrics"), and the values are the numerical tolerances values.
E.g.,
```python
lexico_objectives = {"metrics":["error_rate","pred_time"], "modes":["min","min"],
"tolerances":{"error_rate":0.01,"pred_time":0.0}, "targets":{"error_rate":0.0}}
```
```python
lexico_objectives = {
"metrics": ["error_rate", "pred_time"],
"modes": ["min", "min"],
"tolerances": {"error_rate": 0.01, "pred_time": 0.0},
"targets": {"error_rate": 0.0},
}
```
**ray_args: keyword arguments to pass to ray.tune.run().
Only valid when use_ray=True.
"""