From 04d50ff33b9dd4acf9740b38a159208d5ccce94d Mon Sep 17 00:00:00 2001 From: Lucie Date: Tue, 17 Oct 2023 15:18:04 +0200 Subject: [PATCH 1/4] feat(embedding_metrics): implement BERTScore and MAUVE and add unit tests support --- .github/workflows/ci.yaml | 4 +- poetry.lock | 1588 ++++++++++++++++- pyproject.toml | 5 + .../model/helpers/embedding_metrics.py | 60 + tests/__init__.py | 8 + tests/test.py | 0 tests/test_embedding_metrics.py | 32 + 7 files changed, 1632 insertions(+), 65 deletions(-) delete mode 100644 tests/test.py create mode 100644 tests/test_embedding_metrics.py diff --git a/.github/workflows/ci.yaml b/.github/workflows/ci.yaml index 3792e0e..3a099c1 100644 --- a/.github/workflows/ci.yaml +++ b/.github/workflows/ci.yaml @@ -44,8 +44,8 @@ jobs: - name: Run formatter run: | - poetry run black --check saga_predictor tests + poetry run black --check saga_llm_evaluation_ml tests - name: Run linter run: | - poetry run pylint saga_predictor tests \ No newline at end of file + 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lock-version = "2.0" python-versions = "^3.8,<3.11" -content-hash = "d3d7489a246a44cc9faa74f636daa3e3e39da83daf11fe48befe12b769108031" +content-hash = "8b80e3aff072a75a8fe40cbf3895eb37a97631c479e0f914f203a59a89a42abd" diff --git a/pyproject.toml b/pyproject.toml index 0147f1d..922f3c9 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -9,6 +9,11 @@ python = "^3.8,<3.11" transformers = "^4.21.1" numpy = "^1.21.2" spacy = "^3.1.3" +evaluate = "^0.4.1" +scikit-learn = "^1.3.1" +mauve-text = "^0.3.0" +pytest = "^7.4.2" +bert-score = "^0.3.13" [tool.poetry.dev-dependencies] pylint = "^2.13" diff --git a/saga_llm_evaluation_ml/model/helpers/embedding_metrics.py b/saga_llm_evaluation_ml/model/helpers/embedding_metrics.py index e69de29..2e20826 100644 --- a/saga_llm_evaluation_ml/model/helpers/embedding_metrics.py +++ b/saga_llm_evaluation_ml/model/helpers/embedding_metrics.py @@ -0,0 +1,60 @@ +# TODO: Implement BERTScore +# TODO: Implement MAUVE +from evaluate import load + + +class BERTScore: + def __init__(self, model_type="roberta-large"): + """ + BERTScore computes a similarity score for each token in the candidate sentence with each token in the reference sentence. + The final score is the average of the similarity scores of all tokens in the candidate sentence. + + Args: + model_type (str, optional): Model type to use. Defaults to "roberta-large". + """ + self.model_type = model_type + self.metric = load("bertscore") + + def compute(self, references, predictions, **kwargs): + """ + Args: + references (list): List of reference sentences. + predictions (list): List of candidate sentences. + + Returns: + list: List of scores for each candidate sentence. Contains a list of scores for precisions, recalls, and F1 scores. + """ + assert len(references) == len( + predictions + ), "Number of references and predictions must be equal." + assert isinstance(references, list), "References must be a list." + assert isinstance(predictions, list), "Predictions must be a list." + + return self.metric.compute( + predictions=predictions, + references=references, + model_type=self.model_type, + **kwargs + ) + + +class MAUVE: + def __init__(self): + """ + MAUVE score computes the difference between the candidate sentence distribution and the reference sentence distribution. + The bigger the MAUVE score, the better. + """ + self.metric = load("mauve") + + def compute(self, references, predictions, **kwargs): + """ + Args: + references (list): List of reference sentences. + predictions (list): List of candidate sentences. + + Returns: + list: List of MAUVE scores for each candidate sentence. + """ + return self.metric.compute( + predictions=predictions, references=references, **kwargs + ) diff --git a/tests/__init__.py b/tests/__init__.py index e69de29..1c25fbc 100644 --- a/tests/__init__.py +++ b/tests/__init__.py @@ -0,0 +1,8 @@ +import os +import sys + +MODULE_ROOT = os.path.abspath("/www/app/src") +sys.path.append(MODULE_ROOT) + +PROJ_ROOT = os.path.abspath("/www/app") +sys.path.append(PROJ_ROOT) diff --git a/tests/test.py b/tests/test.py deleted file mode 100644 index e69de29..0000000 diff --git a/tests/test_embedding_metrics.py b/tests/test_embedding_metrics.py new file mode 100644 index 0000000..c8967a8 --- /dev/null +++ b/tests/test_embedding_metrics.py @@ -0,0 +1,32 @@ +import unittest + +from saga_llm_evaluation_ml.model.helpers.embedding_metrics import BERTScore, MAUVE + + +class TestBERTScore(unittest.TestCase): + def test_compute(self): + """Tests that the BERTScore class computes the correct scores. And that the scores are the same when the same inputs are given.""" + references = ["The cat sat on the mat.", "The dog sat on the log."] + predictions = ["The cat sat on the mat.", "The dog sat on the log."] + bertscore = BERTScore() + scores = bertscore.compute(references, predictions) + print(scores) + self.assertEqual(len(scores["precision"]), len(references)) + self.assertEqual(len(scores["recall"]), len(references)) + self.assertEqual(len(scores["f1"]), len(references)) + + scores_2 = bertscore.compute(references, predictions) + self.assertEqual(scores["precision"], scores_2["precision"]) + self.assertEqual(scores["recall"], scores_2["recall"]) + self.assertEqual(scores["f1"], scores_2["f1"]) + + +class TestMAUVE(unittest.TestCase): + def test_compute(self): + """Tests that the MAUVE class computes the same scores when the same inputs are given.""" + mauve = MAUVE() + references = ["The cat sat on the mat.", "The dog sat on the log."] + predictions = ["The cat sat on the mat.", "The dog sat on the log."] + scores = mauve.compute(references, predictions) + scores_2 = mauve.compute(references, predictions) + self.assertEqual(scores.mauve, scores_2.mauve) From 8e9a20d1484cc597f8370ac4036e386c418f045a Mon Sep 17 00:00:00 2001 From: Lucie Date: Tue, 17 Oct 2023 16:24:14 +0200 Subject: [PATCH 2/4] fix(embedding_metrics): change default models for bertscore and mauve --- saga_llm_evaluation_ml/model/helpers/embedding_metrics.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/saga_llm_evaluation_ml/model/helpers/embedding_metrics.py b/saga_llm_evaluation_ml/model/helpers/embedding_metrics.py index 2e20826..0f84f43 100644 --- a/saga_llm_evaluation_ml/model/helpers/embedding_metrics.py +++ b/saga_llm_evaluation_ml/model/helpers/embedding_metrics.py @@ -4,7 +4,7 @@ class BERTScore: - def __init__(self, model_type="roberta-large"): + def __init__(self, model_type="distilbert-base-uncased"): """ BERTScore computes a similarity score for each token in the candidate sentence with each token in the reference sentence. The final score is the average of the similarity scores of all tokens in the candidate sentence. @@ -56,5 +56,5 @@ def compute(self, references, predictions, **kwargs): list: List of MAUVE scores for each candidate sentence. 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false +python-versions = ">=3.7" +files = [ + {file = "wheel-0.41.2-py3-none-any.whl", hash = "sha256:75909db2664838d015e3d9139004ee16711748a52c8f336b52882266540215d8"}, + {file = "wheel-0.41.2.tar.gz", hash = "sha256:0c5ac5ff2afb79ac23ab82bab027a0be7b5dbcf2e54dc50efe4bf507de1f7985"}, +] + +[package.extras] +test = ["pytest (>=6.0.0)", "setuptools (>=65)"] + [[package]] name = "wrapt" version = "1.15.0" @@ -3545,4 +3808,4 @@ testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "p [metadata] lock-version = "2.0" python-versions = "^3.8,<3.11" -content-hash = "8b80e3aff072a75a8fe40cbf3895eb37a97631c479e0f914f203a59a89a42abd" +content-hash = "d3d4af715bf7c7fe07c671f41e9d1fffcc3d910ec3d262258b2ef385ca88d128" diff --git a/pyproject.toml b/pyproject.toml index 922f3c9..4aaaf56 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -12,8 +12,8 @@ spacy = "^3.1.3" evaluate = "^0.4.1" scikit-learn = "^1.3.1" mauve-text = "^0.3.0" -pytest = "^7.4.2" bert-score = "^0.3.13" +torch = ">=2.0.0, !=2.0.1, !=2.1.0" [tool.poetry.dev-dependencies] pylint = "^2.13" @@ -28,6 +28,10 @@ url = "https://pypiserver.sagacify.com/" default = false secondary = true + +[tool.poetry.group.dev.dependencies] +pytest = "^7.4.2" + [build-system] requires = ["poetry-core>=1.0.0"] build-backend = "poetry.core.masonry.api" diff --git a/saga_llm_evaluation_ml/model/helpers/embedding_metrics.py b/saga_llm_evaluation_ml/model/helpers/embedding_metrics.py index 0f84f43..16a26cc 100644 --- a/saga_llm_evaluation_ml/model/helpers/embedding_metrics.py +++ b/saga_llm_evaluation_ml/model/helpers/embedding_metrics.py @@ -45,6 +45,7 @@ def __init__(self): The bigger the MAUVE score, the better. """ self.metric = load("mauve") + self.featurize_model_name = "gpt2" def compute(self, references, predictions, **kwargs): """ @@ -56,5 +57,8 @@ def compute(self, references, predictions, **kwargs): list: List of MAUVE scores for each candidate sentence. """ return self.metric.compute( - predictions=predictions, references=references, featurize_model_name="gpt2", **kwargs + predictions=predictions, + references=references, + featurize_model_name=self.featurize_model_name, + **kwargs ) diff --git a/tests/test_embedding_metrics.py b/tests/test_embedding_metrics.py index c8967a8..6e5c6a2 100644 --- a/tests/test_embedding_metrics.py +++ b/tests/test_embedding_metrics.py @@ -20,6 +20,19 @@ def test_compute(self): self.assertEqual(scores["recall"], scores_2["recall"]) self.assertEqual(scores["f1"], scores_2["f1"]) + def test_compute_improved_input(self): + """Tests that the BERTScore improves for a better prediction.""" + reference = "The cat sat on the mat." + prediction = "The dog sat on the mat." + better_prediction = "The cat sat on the mat." + + bertscore = BERTScore() + + scores = bertscore.compute([reference], [prediction]) + better_scores = bertscore.compute([reference], [better_prediction]) + + self.assertGreater(better_scores["f1"][0], scores["f1"][0]) + class TestMAUVE(unittest.TestCase): def test_compute(self): @@ -30,3 +43,16 @@ def test_compute(self): scores = mauve.compute(references, predictions) scores_2 = mauve.compute(references, predictions) self.assertEqual(scores.mauve, scores_2.mauve) + + def test_compute_improved_input(self): + """Tests that the MAUVE Score improves for a better prediction.""" + reference = "The cat sat on the mat." + prediction = "The dog sat on the mat." + better_prediction = "The cat sat on the mat." + + mauve = MAUVE() + + scores = mauve.compute([reference], [prediction]) + better_scores = mauve.compute([reference], [better_prediction]) + + self.assertGreater(better_scores.mauve, scores.mauve) From db39ad31dd226b24956cb39786198900cf937719 Mon Sep 17 00:00:00 2001 From: Lucie Date: Wed, 18 Oct 2023 11:51:11 +0200 Subject: [PATCH 4/4] fix(embedding_metrics): add featurize_model_name argument to init for mauve score --- saga_llm_evaluation_ml/model/helpers/embedding_metrics.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/saga_llm_evaluation_ml/model/helpers/embedding_metrics.py b/saga_llm_evaluation_ml/model/helpers/embedding_metrics.py index 16a26cc..70c25c7 100644 --- a/saga_llm_evaluation_ml/model/helpers/embedding_metrics.py +++ b/saga_llm_evaluation_ml/model/helpers/embedding_metrics.py @@ -39,13 +39,13 @@ def compute(self, references, predictions, **kwargs): class MAUVE: - def __init__(self): + def __init__(self, featurize_model_name="gpt2"): """ MAUVE score computes the difference between the candidate sentence distribution and the reference sentence distribution. The bigger the MAUVE score, the better. """ self.metric = load("mauve") - self.featurize_model_name = "gpt2" + self.featurize_model_name = featurize_model_name def compute(self, references, predictions, **kwargs): """