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Update Space (evaluate main: c447fc8e)
Browse files- coval.py +9 -25
- requirements.txt +1 -1
coval.py
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@@ -12,8 +12,6 @@
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# See the License for the specific language governing permissions and
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# limitations under the License.
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""" CoVal metric. """
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from dataclasses import dataclass
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import coval # From: git+https://github.com/ns-moosavi/coval.git noqa: F401
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import datasets
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from coval.conll import reader, util
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@@ -271,29 +269,13 @@ def check_gold_parse_annotation(key_lines):
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return has_gold_parse
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@dataclass
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class CovalConfig(evaluate.info.Config):
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name: str = "default"
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keep_singletons: bool = True
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NP_only: bool = False
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min_span: bool = False
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remove_nested: bool = False
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@evaluate.utils.file_utils.add_start_docstrings(_DESCRIPTION, _KWARGS_DESCRIPTION)
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class Coval(evaluate.Metric):
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CONFIG_CLASS = CovalConfig
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ALLOWED_CONFIG_NAMES = ["default"]
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def _info(self, config):
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return evaluate.MetricInfo(
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description=_DESCRIPTION,
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citation=_CITATION,
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inputs_description=_KWARGS_DESCRIPTION,
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config=config,
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features=datasets.Features(
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{
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"predictions": datasets.Sequence(datasets.Value("string")),
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@@ -308,7 +290,9 @@ class Coval(evaluate.Metric):
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],
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)
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def _compute(
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allmetrics = [
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("mentions", evaluator.mentions),
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("muc", evaluator.muc),
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@@ -317,7 +301,7 @@ class Coval(evaluate.Metric):
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("lea", evaluator.lea),
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]
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if
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has_gold_parse = util.check_gold_parse_annotation(references)
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if not has_gold_parse:
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raise NotImplementedError("References should have gold parse annotation to use 'min_span'.")
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@@ -328,10 +312,10 @@ class Coval(evaluate.Metric):
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key_lines=references,
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sys_lines=predictions,
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metrics=allmetrics,
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NP_only=
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remove_nested=
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keep_singletons=
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min_span=
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)
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return score
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# See the License for the specific language governing permissions and
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# limitations under the License.
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""" CoVal metric. """
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import coval # From: git+https://github.com/ns-moosavi/coval.git noqa: F401
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import datasets
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from coval.conll import reader, util
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return has_gold_parse
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@evaluate.utils.file_utils.add_start_docstrings(_DESCRIPTION, _KWARGS_DESCRIPTION)
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class Coval(evaluate.Metric):
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def _info(self):
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return evaluate.MetricInfo(
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description=_DESCRIPTION,
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citation=_CITATION,
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inputs_description=_KWARGS_DESCRIPTION,
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features=datasets.Features(
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{
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"predictions": datasets.Sequence(datasets.Value("string")),
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],
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)
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def _compute(
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self, predictions, references, keep_singletons=True, NP_only=False, min_span=False, remove_nested=False
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):
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allmetrics = [
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("mentions", evaluator.mentions),
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("muc", evaluator.muc),
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("lea", evaluator.lea),
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]
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if min_span:
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has_gold_parse = util.check_gold_parse_annotation(references)
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if not has_gold_parse:
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raise NotImplementedError("References should have gold parse annotation to use 'min_span'.")
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key_lines=references,
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sys_lines=predictions,
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metrics=allmetrics,
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NP_only=NP_only,
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remove_nested=remove_nested,
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keep_singletons=keep_singletons,
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min_span=min_span,
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)
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return score
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requirements.txt
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@@ -1,2 +1,2 @@
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git+https://github.com/huggingface/evaluate@
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git+https://github.com/ns-moosavi/coval.git
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git+https://github.com/huggingface/evaluate@c447fc8eda9c62af501bfdc6988919571050d950
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git+https://github.com/ns-moosavi/coval.git
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