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Update Space (evaluate main: e4a27243)
Browse files- code_eval.py +21 -5
- requirements.txt +1 -1
code_eval.py
CHANGED
@@ -20,6 +20,8 @@ import itertools
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import os
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from collections import Counter, defaultdict
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from concurrent.futures import ThreadPoolExecutor, as_completed
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import datasets
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import numpy as np
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@@ -131,14 +133,28 @@ OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
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THE SOFTWARE."""
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@evaluate.utils.file_utils.add_start_docstrings(_DESCRIPTION, _KWARGS_DESCRIPTION)
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class CodeEval(evaluate.Metric):
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-
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return evaluate.MetricInfo(
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# This is the description that will appear on the metrics page.
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description=_DESCRIPTION,
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citation=_CITATION,
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inputs_description=_KWARGS_DESCRIPTION,
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# This defines the format of each prediction and reference
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features=datasets.Features(
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{
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@@ -152,7 +168,7 @@ class CodeEval(evaluate.Metric):
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license=_LICENSE,
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)
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def _compute(self, predictions, references
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"""Returns the scores"""
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if os.getenv("HF_ALLOW_CODE_EVAL", 0) != "1":
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@@ -161,7 +177,7 @@ class CodeEval(evaluate.Metric):
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if os.name == "nt":
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raise NotImplementedError("This metric is currently not supported on Windows.")
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with ThreadPoolExecutor(max_workers=num_workers) as executor:
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futures = []
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completion_id = Counter()
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n_samples = 0
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@@ -170,7 +186,7 @@ class CodeEval(evaluate.Metric):
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for task_id, (candidates, test_case) in enumerate(zip(predictions, references)):
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for candidate in candidates:
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test_program = candidate + "\n" + test_case
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args = (test_program, timeout, task_id, completion_id[task_id])
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future = executor.submit(check_correctness, *args)
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futures.append(future)
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completion_id[task_id] += 1
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@@ -189,7 +205,7 @@ class CodeEval(evaluate.Metric):
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total = np.array(total)
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correct = np.array(correct)
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ks = k
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pass_at_k = {f"pass@{k}": estimate_pass_at_k(total, correct, k).mean() for k in ks if (total >= k).all()}
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return pass_at_k, results
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import os
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from collections import Counter, defaultdict
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from concurrent.futures import ThreadPoolExecutor, as_completed
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from dataclasses import dataclass, field
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from typing import List
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import datasets
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import numpy as np
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THE SOFTWARE."""
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@dataclass
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class CodeEvalConfig(evaluate.info.Config):
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name: str = "default"
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k: List[int] = field(default_factory=lambda: [1, 10, 100])
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num_workers: int = 4
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timeout: float = 3.0
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@evaluate.utils.file_utils.add_start_docstrings(_DESCRIPTION, _KWARGS_DESCRIPTION)
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class CodeEval(evaluate.Metric):
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CONFIG_CLASS = CodeEvalConfig
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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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# This is the description that will appear on the metrics page.
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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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# This defines the format of each prediction and reference
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features=datasets.Features(
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{
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license=_LICENSE,
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)
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def _compute(self, predictions, references):
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"""Returns the scores"""
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if os.getenv("HF_ALLOW_CODE_EVAL", 0) != "1":
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if os.name == "nt":
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raise NotImplementedError("This metric is currently not supported on Windows.")
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with ThreadPoolExecutor(max_workers=self.config.num_workers) as executor:
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futures = []
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completion_id = Counter()
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n_samples = 0
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for task_id, (candidates, test_case) in enumerate(zip(predictions, references)):
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for candidate in candidates:
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test_program = candidate + "\n" + test_case
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args = (test_program, self.config.timeout, task_id, completion_id[task_id])
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future = executor.submit(check_correctness, *args)
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futures.append(future)
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completion_id[task_id] += 1
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total = np.array(total)
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correct = np.array(correct)
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ks = self.config.k
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pass_at_k = {f"pass@{k}": estimate_pass_at_k(total, correct, k).mean() for k in ks if (total >= k).all()}
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return pass_at_k, results
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requirements.txt
CHANGED
@@ -1 +1 @@
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git+https://github.com/huggingface/evaluate@
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git+https://github.com/huggingface/evaluate@e4a2724377909fe2aeb4357e3971e5a569673b39
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