Spaces:
Running
Running
Update Space (evaluate main: c447fc8e)
Browse files- precision.py +11 -26
- requirements.txt +1 -1
precision.py
CHANGED
|
@@ -13,9 +13,6 @@
|
|
| 13 |
# limitations under the License.
|
| 14 |
"""Precision metric."""
|
| 15 |
|
| 16 |
-
from dataclasses import dataclass
|
| 17 |
-
from typing import List, Optional, Union
|
| 18 |
-
|
| 19 |
import datasets
|
| 20 |
from sklearn.metrics import precision_score
|
| 21 |
|
|
@@ -105,30 +102,13 @@ _CITATION = """
|
|
| 105 |
"""
|
| 106 |
|
| 107 |
|
| 108 |
-
@dataclass
|
| 109 |
-
class PrecisionConfig(evaluate.info.Config):
|
| 110 |
-
|
| 111 |
-
name: str = "default"
|
| 112 |
-
|
| 113 |
-
pos_label: Union[str, int] = 1
|
| 114 |
-
average: str = "binary"
|
| 115 |
-
labels: Optional[List[str]] = None
|
| 116 |
-
sample_weight: Optional[List[float]] = None
|
| 117 |
-
zero_division: str = "warn"
|
| 118 |
-
|
| 119 |
-
|
| 120 |
@evaluate.utils.file_utils.add_start_docstrings(_DESCRIPTION, _KWARGS_DESCRIPTION)
|
| 121 |
class Precision(evaluate.Metric):
|
| 122 |
-
|
| 123 |
-
CONFIG_CLASS = PrecisionConfig
|
| 124 |
-
ALLOWED_CONFIG_NAMES = ["default", "multilabel"]
|
| 125 |
-
|
| 126 |
-
def _info(self, config):
|
| 127 |
return evaluate.MetricInfo(
|
| 128 |
description=_DESCRIPTION,
|
| 129 |
citation=_CITATION,
|
| 130 |
inputs_description=_KWARGS_DESCRIPTION,
|
| 131 |
-
config=config,
|
| 132 |
features=datasets.Features(
|
| 133 |
{
|
| 134 |
"predictions": datasets.Sequence(datasets.Value("int32")),
|
|
@@ -147,14 +127,19 @@ class Precision(evaluate.Metric):
|
|
| 147 |
self,
|
| 148 |
predictions,
|
| 149 |
references,
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 150 |
):
|
| 151 |
score = precision_score(
|
| 152 |
references,
|
| 153 |
predictions,
|
| 154 |
-
labels=
|
| 155 |
-
pos_label=
|
| 156 |
-
average=
|
| 157 |
-
sample_weight=
|
| 158 |
-
zero_division=
|
| 159 |
)
|
| 160 |
return {"precision": float(score) if score.size == 1 else score}
|
|
|
|
| 13 |
# limitations under the License.
|
| 14 |
"""Precision metric."""
|
| 15 |
|
|
|
|
|
|
|
|
|
|
| 16 |
import datasets
|
| 17 |
from sklearn.metrics import precision_score
|
| 18 |
|
|
|
|
| 102 |
"""
|
| 103 |
|
| 104 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 105 |
@evaluate.utils.file_utils.add_start_docstrings(_DESCRIPTION, _KWARGS_DESCRIPTION)
|
| 106 |
class Precision(evaluate.Metric):
|
| 107 |
+
def _info(self):
|
|
|
|
|
|
|
|
|
|
|
|
|
| 108 |
return evaluate.MetricInfo(
|
| 109 |
description=_DESCRIPTION,
|
| 110 |
citation=_CITATION,
|
| 111 |
inputs_description=_KWARGS_DESCRIPTION,
|
|
|
|
| 112 |
features=datasets.Features(
|
| 113 |
{
|
| 114 |
"predictions": datasets.Sequence(datasets.Value("int32")),
|
|
|
|
| 127 |
self,
|
| 128 |
predictions,
|
| 129 |
references,
|
| 130 |
+
labels=None,
|
| 131 |
+
pos_label=1,
|
| 132 |
+
average="binary",
|
| 133 |
+
sample_weight=None,
|
| 134 |
+
zero_division="warn",
|
| 135 |
):
|
| 136 |
score = precision_score(
|
| 137 |
references,
|
| 138 |
predictions,
|
| 139 |
+
labels=labels,
|
| 140 |
+
pos_label=pos_label,
|
| 141 |
+
average=average,
|
| 142 |
+
sample_weight=sample_weight,
|
| 143 |
+
zero_division=zero_division,
|
| 144 |
)
|
| 145 |
return {"precision": float(score) if score.size == 1 else score}
|
requirements.txt
CHANGED
|
@@ -1,2 +1,2 @@
|
|
| 1 |
-
git+https://github.com/huggingface/evaluate@
|
| 2 |
sklearn
|
|
|
|
| 1 |
+
git+https://github.com/huggingface/evaluate@c447fc8eda9c62af501bfdc6988919571050d950
|
| 2 |
sklearn
|