git cloneだけでなく、リポジトリからpip installしてmain.pyの処理が実行できるようにする

README.md

@@ -16,7 +16,7 @@ poetry run pytest tests
 The following command evaluate the specified model on the all the tasks in JMTEB.
 
 ```bash
-poetry run python main.py \
+poetry run python -m jmteb \
   --embedder SentenceBertEmbedder \
   --embedder.model_name_or_path "<model_name_or_path>" \
   --save_dir "output/<model_name_or_path>"
@@ -26,7 +26,7 @@ By default, the evaluation tasks are read from `src/configs/jmteb.jsonnet`.
 If you want to evaluate the model on a specific task, you can specify the task via `--evaluators` option with the task config.
 
 ```bash
-poetry run python main.py \
+poetry run python -m jmteb \
   --evaluators "src/configs/tasks/jsts.jsonnet" \
   --embedder SentenceBertEmbedder \
   --embedder.model_name_or_path "<model_name_or_path>" \

pyproject.toml

@@ -10,7 +10,7 @@ authors = [
 ]
 description = "The evaluation scripts for JMTEB (Japanese Massive Text Embedding Benchmark)"
 name = "JMTEB"
-packages = [{from = ".", include = "src"}]
+packages = [{from = "src", include = "jmteb"}]
 readme = "README.md"
 version = "1.0.0"
 

main.py → src/jmteb/__main__.py

@@ -6,9 +6,9 @@
 from jsonargparse import ActionConfigFile, ArgumentParser
 from loguru import logger
 
-from src.embedders import TextEmbedder
-from src.evaluators import EmbeddingEvaluator
-from src.utils.score_recorder import JsonScoreRecorder
+from jmteb.embedders import TextEmbedder
+from jmteb.evaluators import EmbeddingEvaluator
+from jmteb.utils.score_recorder import JsonScoreRecorder
 
 
 def main(
@@ -49,7 +49,10 @@ def main(
 
     parser.add_subclass_arguments(TextEmbedder, nested_key="embedder", required=True)
     parser.add_argument(
-        "--evaluators", type=dict[str, EmbeddingEvaluator], enable_path=True, default="src/configs/jmteb.jsonnet"
+        "--evaluators",
+        type=dict[str, EmbeddingEvaluator],
+        enable_path=True,
+        default=str(Path(__file__).parent / "configs" / "jmteb.jsonnet"),
     )
     parser.add_argument("--config", action=ActionConfigFile, help="Path to the config file.")
     parser.add_argument("--save_dir", type=str, default=None, help="Directory to save the outputs")
@@ -66,6 +69,13 @@ def main(
                 args.evaluators.pop(key)
 
     args = parser.instantiate_classes(args)
+    if isinstance(args.evaluators, str):
+        raise ValueError(
+            "Evaluators should be a dictionary, not a string.\n"
+            "Perhaps you provided a path to a config file, "
+            "but the path does not exist or the config format is broken.\n"
+            f"Please check {args.evaluators}"
+        )
 
     main(
         text_embedder=args.embedder,

src/jmteb/embedders/__init__.py

@@ -0,0 +1,2 @@
+from jmteb.embedders.base import TextEmbedder
+from jmteb.embedders.sbert_embedder import SentenceBertEmbedder

src/embedders/sbert_embedder.py → src/jmteb/embedders/sbert_embedder.py

@@ -3,7 +3,7 @@
 import numpy as np
 from sentence_transformers import SentenceTransformer
 
-from src.embedders.base import TextEmbedder
+from jmteb.embedders.base import TextEmbedder
 
 
 class SentenceBertEmbedder(TextEmbedder):

src/evaluators/base.py → src/jmteb/evaluators/base.py

@@ -6,7 +6,7 @@
 
 from pydantic.dataclasses import dataclass
 
-from src.embedders import TextEmbedder
+from jmteb.embedders import TextEmbedder
 
 
 @dataclass

src/evaluators/classification/evaluator.py → src/jmteb/evaluators/classification/evaluator.py

@@ -6,8 +6,8 @@
 from loguru import logger
 from sklearn.metrics import accuracy_score, f1_score
 
-from src.embedders.base import TextEmbedder
-from src.evaluators.base import EmbeddingEvaluator, EvaluationResults
+from jmteb.embedders.base import TextEmbedder
+from jmteb.evaluators.base import EmbeddingEvaluator, EvaluationResults
 
 from .classifiers import Classifier, KnnClassifier, LogRegClassifier
 from .data import ClassificationDataset

src/evaluators/clustering/evaluator.py → src/jmteb/evaluators/clustering/evaluator.py

@@ -13,8 +13,8 @@
 )
 from sklearn.metrics import homogeneity_completeness_v_measure
 
-from src.embedders.base import TextEmbedder
-from src.evaluators.base import EmbeddingEvaluator, EvaluationResults
+from jmteb.embedders.base import TextEmbedder
+from jmteb.evaluators.base import EmbeddingEvaluator, EvaluationResults
 
 from .data import ClusteringDataset
 

src/evaluators/pair_classification/evaluator.py → src/jmteb/evaluators/pair_classification/evaluator.py

@@ -3,8 +3,8 @@
 from os import PathLike
 from pathlib import Path
 
-from src.embedders.base import TextEmbedder
-from src.evaluators.base import EmbeddingEvaluator, EvaluationResults
+from jmteb.embedders.base import TextEmbedder
+from jmteb.evaluators.base import EmbeddingEvaluator, EvaluationResults
 
 from .data import PairClassificationDataset
 from .threshold_accuracy import ThresholdAccuracyMetric

src/evaluators/retrieval/evaluator.py → src/jmteb/evaluators/retrieval/evaluator.py

@@ -12,8 +12,8 @@
 from loguru import logger
 from torch import Tensor
 
-from src.embedders.base import TextEmbedder
-from src.evaluators.base import EmbeddingEvaluator, EvaluationResults
+from jmteb.embedders.base import TextEmbedder
+from jmteb.evaluators.base import EmbeddingEvaluator, EvaluationResults
 
 from .data import RetrievalDocDataset, RetrievalQueryDataset
 

src/evaluators/sts/evaluator.py → src/jmteb/evaluators/sts/evaluator.py

@@ -9,8 +9,8 @@
 from scipy.stats import pearsonr, spearmanr
 from torch import Tensor
 
-from src.embedders.base import TextEmbedder
-from src.evaluators.base import EmbeddingEvaluator, EvaluationResults
+from jmteb.embedders.base import TextEmbedder
+from jmteb.evaluators.base import EmbeddingEvaluator, EvaluationResults
 
 from .data import STSDataset
 

src/utils/score_recorder.py → src/jmteb/utils/score_recorder.py

@@ -7,7 +7,7 @@
 from pathlib import Path
 from typing import Any
 
-from src.evaluators import EvaluationResults
+from jmteb.evaluators import EvaluationResults
 
 
 class AbstractScoreRecorder(ABC):

tests/conftest.py

@@ -1,5 +1,7 @@
 import pytest
 
+from jmteb.embedders.sbert_embedder import SentenceBertEmbedder
+
 
 def pytest_addoption(parser: pytest.Parser):
     parser.addoption("--runslow", action="store_true", default=False, help="run slow tests")
@@ -17,3 +19,8 @@ def pytest_collection_modifyitems(config: pytest.Config, items: pytest.Parser):
     for item in items:
         if "slow" in item.keywords:
             item.add_marker(skip_slow)
+
+
+@pytest.fixture(scope="module")
+def embedder(model_name_or_path: str = "prajjwal1/bert-tiny"):
+    return SentenceBertEmbedder(model_name_or_path=model_name_or_path)

tests/embedders/test_sbert.py

@@ -1,6 +1,6 @@
 import numpy as np
 
-from src.embedders.sbert_embedder import SentenceBertEmbedder
+from jmteb.embedders.sbert_embedder import SentenceBertEmbedder
 
 MODEL_NAME_OR_PATH = "prajjwal1/bert-tiny"
 OUTPUT_DIM = 128

tests/evaluator/conftest.py

@@ -1,6 +1,6 @@
 import pytest
 
-from src.embedders.sbert_embedder import SentenceBertEmbedder
+from jmteb.embedders.sbert_embedder import SentenceBertEmbedder
 
 
 @pytest.fixture(scope="module")

tests/evaluator/test_classification_evaluator.py

@@ -1,11 +1,11 @@
-from src.evaluators.classification import (
+from jmteb.evaluators.classification import (
     ClassificationDataset,
     ClassificationEvaluator,
     ClassificationInstance,
     KnnClassifier,
     LogRegClassifier,
 )
-from src.evaluators.classification.data import JsonlClassificationDataset
+from jmteb.evaluators.classification.data import JsonlClassificationDataset
 
 
 class DummyClassificationDataset(ClassificationDataset):

tests/evaluator/test_clustering_evaluator.py

@@ -1,9 +1,9 @@
-from src.evaluators.clustering import (
+from jmteb.evaluators.clustering import (
     ClusteringDataset,
     ClusteringEvaluator,
     ClusteringInstance,
 )
-from src.evaluators.clustering.data import JsonlClusteringDataset
+from jmteb.evaluators.clustering.data import JsonlClusteringDataset
 
 
 class DummyClusteringDataset(ClusteringDataset):

tests/evaluator/test_pair_classification_evaluator.py

@@ -1,9 +1,9 @@
-from src.evaluators.pair_classification import (
+from jmteb.evaluators.pair_classification import (
     PairClassificationDataset,
     PairClassificationEvaluator,
     PairClassificationInstance,
 )
-from src.evaluators.pair_classification.data import JsonlPairClassificationDataset
+from jmteb.evaluators.pair_classification.data import JsonlPairClassificationDataset
 
 
 class DummyBinaryDataset(PairClassificationDataset):

tests/evaluator/test_retrieval_evaluator.py

@@ -1,11 +1,11 @@
-from src.evaluators.retrieval import (
+from jmteb.evaluators.retrieval import (
     RetrievalDoc,
     RetrievalDocDataset,
     RetrievalEvaluator,
     RetrievalQuery,
     RetrievalQueryDataset,
 )
-from src.evaluators.retrieval.data import (
+from jmteb.evaluators.retrieval.data import (
     JsonlRetrievalDocDataset,
     JsonlRetrievalQueryDataset,
 )

tests/evaluator/test_sts_evaluator.py

@@ -1,5 +1,5 @@
-from src.evaluators.sts import STSDataset, STSEvaluator, STSInstance
-from src.evaluators.sts.data import JsonlSTSDataset
+from jmteb.evaluators.sts import STSDataset, STSEvaluator, STSInstance
+from jmteb.evaluators.sts.data import JsonlSTSDataset
 
 
 class DummySTSDataset(STSDataset):