diff --git a/bugbug/model.py b/bugbug/model.py index 9ef60c51d3..ad13cbe078 100644 --- a/bugbug/model.py +++ b/bugbug/model.py @@ -415,7 +415,8 @@ def train(self, importance_cutoff=0.15, limit=None): logger.info(f"X_test: {X_test.shape}, y_test: {y_test.shape}") self.clf.fit(X_train, self.le.transform(y_train)) - logger.info("Number of features: %d", self.clf.steps[-1][1].n_features_in_) + if hasattr(self.clf.steps[-1][1], "n_features_in_"): + logger.info("Number of features: %d", self.clf.steps[-1][1].n_features_in_) logger.info("Model trained") diff --git a/bugbug/models/__init__.py b/bugbug/models/__init__.py index eb1a66a84f..3d719e616b 100644 --- a/bugbug/models/__init__.py +++ b/bugbug/models/__init__.py @@ -17,6 +17,8 @@ "bugtype": "bugbug.models.bugtype.BugTypeModel", "component": "bugbug.models.component.ComponentModel", "defect": "bugbug.models.defect.DefectModel", + "defect_finetuning": "bugbug.models.defect.DefectFinetuningModel", + "defect_embedding": "bugbug.models.defect.DefectEmbeddingModel", "defectenhancementtask": "bugbug.models.defect_enhancement_task.DefectEnhancementTaskModel", "devdocneeded": "bugbug.models.devdocneeded.DevDocNeededModel", "fixtime": "bugbug.models.fixtime.FixTimeModel", diff --git a/bugbug/models/defect.py b/bugbug/models/defect.py index 9e99537134..523872722f 100644 --- a/bugbug/models/defect.py +++ b/bugbug/models/defect.py @@ -7,15 +7,22 @@ import logging from typing import Any +import torch import xgboost from imblearn.over_sampling import BorderlineSMOTE from imblearn.pipeline import Pipeline as ImblearnPipeline from sklearn.compose import ColumnTransformer from sklearn.feature_extraction import DictVectorizer from sklearn.pipeline import Pipeline +from skorch import NeuralNetClassifier +from skorch.callbacks import ProgressBar +from skorch.hf import HuggingfacePretrainedTokenizer +from torch import nn from bugbug import bug_features, bugzilla, feature_cleanup, labels, utils from bugbug.model import BugModel +from bugbug.nn import DistilBertModule, ExtractEmbeddings, get_training_device +from bugbug.utils import MergeText logging.basicConfig(level=logging.INFO) logger = logging.getLogger(__name__) @@ -290,3 +297,94 @@ def overwrite_classes(self, bugs, classes, probabilities): classes[i] = 0 if not probabilities else [1.0, 0.0] return classes + + +class DefectFinetuningModel(DefectModel): + def __init__(self, last_layer_only=True, **kwargs): + super().__init__(**kwargs) + + self.sampler = None + self.calculate_importance = False + self.cross_validation_enabled = False + + self.extraction_pipeline = Pipeline( + [ + ( + "bug_extractor", + bug_features.BugExtractor([], [], rollback=True), + ), + ("extract", MergeText(["title", "comments"])), + ] + ) + + self.clf = Pipeline( + [ + ( + "tokenizer", + HuggingfacePretrainedTokenizer( + "distilbert-base-uncased", max_length=512 + ), + ), + ( + "classifier", + NeuralNetClassifier( + DistilBertModule, + module__name="distilbert-base-uncased", + module__num_labels=2, + module__last_layer_only=last_layer_only, + optimizer=torch.optim.AdamW, + lr=6e-5, + max_epochs=2, + criterion=nn.CrossEntropyLoss, + batch_size=4, + iterator_train__shuffle=True, + device=get_training_device(), + callbacks=[ + ProgressBar(), + ], + ), + ), + ] + ) + + def get_feature_names(self): + return [] + + +class DefectEmbeddingModel(DefectModel): + def __init__(self, **kwargs): + print(**kwargs) + super().__init__(**kwargs) + + self.sampler = None + self.calculate_importance = False + self.cross_validation_enabled = False + + self.extraction_pipeline = Pipeline( + [ + ( + "bug_extractor", + bug_features.BugExtractor([], [], rollback=True), + ), + ("extract", MergeText(["title", "comments"])), + ] + ) + + self.clf = Pipeline( + [ + ( + "tokenizer", + HuggingfacePretrainedTokenizer( + "distilbert-base-uncased", max_length=512 + ), + ), + ("extract_embeddings", ExtractEmbeddings("distilbert-base-uncased")), + ( + "classifier", + xgboost.XGBClassifier(n_jobs=utils.get_physical_cpu_count()), + ), + ] + ) + + def get_feature_names(self): + return [] diff --git a/bugbug/nn.py b/bugbug/nn.py new file mode 100644 index 0000000000..6f7aa9ed60 --- /dev/null +++ b/bugbug/nn.py @@ -0,0 +1,52 @@ +# -*- coding: utf-8 -*- +# This Source Code Form is subject to the terms of the Mozilla Public +# License, v. 2.0. If a copy of the MPL was not distributed with this file, +# You can obtain one at http://mozilla.org/MPL/2.0/. + +import torch +from sklearn.base import BaseEstimator, TransformerMixin +from torch import nn +from transformers import AutoModel, AutoModelForSequenceClassification + +OPT_MSG_MISSING = ( + "Optional dependencies are missing, install them with: pip install bugbug[nn]\n" +) + + +class ExtractEmbeddings(BaseEstimator, TransformerMixin): + def __init__(self, model_name: str): + self.model = AutoModel.from_pretrained(model_name) + + def fit(self, X, y): + return self + + def transform(self, X): + with torch.no_grad(): + # TODO: support .last_hidden_state.mean(dim=1) as an alternative + return self.model(**X).last_hidden_state[:, 0, :] + + +def get_training_device() -> str: + return "cuda" if torch.cuda.is_available() else "cpu" + + +class DistilBertModule(nn.Module): + def __init__(self, name, num_labels, last_layer_only=False): + super().__init__() + self.name = name + self.num_labels = num_labels + self.last_layer_only = last_layer_only + + self.reset_weights() + + def reset_weights(self): + self.bert = AutoModelForSequenceClassification.from_pretrained( + self.name, num_labels=self.num_labels + ) + if self.last_layer_only: + for param in self.bert.distilbert.parameters(): + param.requires_grad = False + + def forward(self, **kwargs): + pred = self.bert(**kwargs) + return pred.logits diff --git a/pyproject.toml b/pyproject.toml index d2c849eff7..5f36fa98a5 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -52,6 +52,9 @@ dependencies = [ "requests==2.33.0", "requests-html==0.10.0", "rs-parsepatch==0.4.6", + "skorch==1.3.1", + "torch==2.11.0", + "transformers==5.4.0", "scikit-learn==1.7.2", "scipy==1.17.1", "sendgrid==6.12.5", @@ -70,7 +73,6 @@ dependencies = [ nlp = [ "spacy==3.8.13", ] -nn = [] [dependency-groups] test = [ diff --git a/scripts/trainer.py b/scripts/trainer.py index 29df276581..85cb0856c0 100644 --- a/scripts/trainer.py +++ b/scripts/trainer.py @@ -22,7 +22,9 @@ def go(self, args): model_name = args.model model_class = get_model_class(model_name) - parameter_names = set(inspect.signature(model_class.__init__).parameters) + parameter_names = set(inspect.signature(model_class.__init__).parameters) - { + "kwargs" + } parameters = { key: value for key, value in vars(args).items() if key in parameter_names } @@ -47,7 +49,7 @@ def go(self, args): logger.info("Training done") - model_directory = f"{model_name}model" + model_directory = model_obj.__class__.__name__.lower() assert os.path.exists(model_directory) create_tar_zst(f"{model_directory}.tar.zst") diff --git a/tests/test_trainer.py b/tests/test_trainer.py index 3b2d7c17c2..e297e54d2f 100644 --- a/tests/test_trainer.py +++ b/tests/test_trainer.py @@ -3,13 +3,16 @@ # License, v. 2.0. If a copy of the MPL was not distributed with this file, # You can obtain one at http://mozilla.org/MPL/2.0/. +import re + import responses from bugbug import bugzilla, db from scripts import trainer -def test_trainer(): +# Test xgboost model on TF-IDF +def test_trainer_simple(): # Pretend the DB was already downloaded and no new DB is available. url = "https://community-tc.services.mozilla.com/api/index/v1/task/project.bugbug.data_bugs.latest/artifacts/public/bugs.json" @@ -29,3 +32,53 @@ def test_trainer(): ) trainer.Trainer().go(trainer.parse_args(["regression"])) + + +# Test finetuning of transformer model +def test_trainer_finetuning(): + responses.add_passthru(re.compile(r"https://.*\.?huggingface.co/\w+")) + + # Pretend the DB was already downloaded and no new DB is available. + + url = "https://community-tc.services.mozilla.com/api/index/v1/task/project.bugbug.data_bugs.latest/artifacts/public/bugs.json" + + responses.add( + responses.GET, + f"{url}.version", + status=200, + body=str(db.DATABASES[bugzilla.BUGS_DB]["version"]), + ) + + responses.add( + responses.HEAD, + f"{url}.zst", + status=200, + headers={"ETag": "etag"}, + ) + + trainer.Trainer().go(trainer.parse_args(["defect_finetuning"])) + + +# Test xgboost model on transformed model's embeddings +def test_trainer_embedding(): + responses.add_passthru(re.compile(r"https://.*\.?huggingface.co/\w+")) + + # Pretend the DB was already downloaded and no new DB is available. + + url = "https://community-tc.services.mozilla.com/api/index/v1/task/project.bugbug.data_bugs.latest/artifacts/public/bugs.json" + + responses.add( + responses.GET, + f"{url}.version", + status=200, + body=str(db.DATABASES[bugzilla.BUGS_DB]["version"]), + ) + + responses.add( + responses.HEAD, + f"{url}.zst", + status=200, + headers={"ETag": "etag"}, + ) + + trainer.Trainer().go(trainer.parse_args(["defect_embedding"])) diff --git a/uv.lock b/uv.lock index 079301522a..ec59b156f9 100644 --- a/uv.lock +++ b/uv.lock @@ -456,10 +456,13 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