From 5576ff2926620b20ed626acb92bb0fc43bd9ad2d Mon Sep 17 00:00:00 2001 From: Rui Vieira Date: Sat, 7 Sep 2024 19:45:21 +0100 Subject: [PATCH 1/5] Update JPype to 1.5.0 --- pyproject.toml | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index d9df207..c5d0522 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -22,7 +22,7 @@ classifiers = [ ] dependencies = [ - "Jpype1==1.4.1", + "Jpype1==1.5.0", "pyarrow==17.0.0", "matplotlib~=3.6.3", "pandas~=1.5.3", @@ -32,7 +32,7 @@ dependencies = [ [project.optional-dependencies] dev = [ - "JPype1==1.4.1", + "JPype1==1.5.0", "black~=22.12.0", "click==8.0.4", "joblib~=1.2.0", From b1646628f452101916ce2857491dbdc5ecb5982b Mon Sep 17 00:00:00 2001 From: Rui Vieira Date: Sat, 7 Sep 2024 19:48:05 +0100 Subject: [PATCH 2/5] Add Python 3.11 to GHAs --- .github/workflows/workflow.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/workflow.yml b/.github/workflows/workflow.yml index 90392e4..dead34a 100644 --- a/.github/workflows/workflow.yml +++ b/.github/workflows/workflow.yml @@ -7,7 +7,7 @@ jobs: runs-on: ubuntu-latest strategy: matrix: - python-version: [ 3.8, 3.9 ] + python-version: [ 3.8, 3.9, 3.11 ] java-version: [ 17 ] maven-version: [ '3.8.6' ] steps: From 541e4cf1ef0473101569a754d7d7d523c64b6a06 Mon Sep 17 00:00:00 2001 From: Rui Vieira Date: Sat, 7 Sep 2024 19:52:41 +0100 Subject: [PATCH 3/5] Fix lint error --- src/trustyai/language/detoxify/tmarco.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/trustyai/language/detoxify/tmarco.py b/src/trustyai/language/detoxify/tmarco.py index 73904fa..eea6022 100644 --- a/src/trustyai/language/detoxify/tmarco.py +++ b/src/trustyai/language/detoxify/tmarco.py @@ -111,7 +111,7 @@ def load_models(self, experts: list[str] = None, expert_weights: list = None): expert_models = [] for expert in experts: # Load TMaRCO models - if (expert == "trustyai/gplus" or expert == "trustyai/gminus"): + if expert in ["trustyai/gplus", "trustyai/gminus"]: expert = BartForConditionalGeneration.from_pretrained( expert, forced_bos_token_id=self.tokenizer.bos_token_id, From 5d49d747b6aa6ebefe525f05b0abf9cc43273c18 Mon Sep 17 00:00:00 2001 From: Rui Vieira Date: Sat, 7 Sep 2024 20:45:47 +0100 Subject: [PATCH 4/5] Workaround Pylint error --- src/trustyai/language/detoxify/tmarco.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/trustyai/language/detoxify/tmarco.py b/src/trustyai/language/detoxify/tmarco.py index eea6022..5597473 100644 --- a/src/trustyai/language/detoxify/tmarco.py +++ b/src/trustyai/language/detoxify/tmarco.py @@ -104,7 +104,7 @@ def __init__( "cuda" if torch.cuda.is_available() else "cpu" ) - def load_models(self, experts: list[str] = None, expert_weights: list = None): + def load_models(self, experts: list[str] = None, expert_weights: list = None): # pylint: disable=unsubscriptable-object """Load expert models.""" if expert_weights is not None: self.expert_weights = expert_weights From 21fa9cb0d0ded725ee920330d1d7a6accbce9cb1 Mon Sep 17 00:00:00 2001 From: Rui Vieira Date: Sat, 7 Sep 2024 20:50:39 +0100 Subject: [PATCH 5/5] Fix styling --- src/trustyai/language/detoxify/tmarco.py | 8 +++++--- 1 file changed, 5 insertions(+), 3 deletions(-) diff --git a/src/trustyai/language/detoxify/tmarco.py b/src/trustyai/language/detoxify/tmarco.py index 5597473..676624d 100644 --- a/src/trustyai/language/detoxify/tmarco.py +++ b/src/trustyai/language/detoxify/tmarco.py @@ -104,7 +104,9 @@ def __init__( "cuda" if torch.cuda.is_available() else "cpu" ) - def load_models(self, experts: list[str] = None, expert_weights: list = None): # pylint: disable=unsubscriptable-object + def load_models( + self, experts: list[str] = None, expert_weights: list = None + ): # pylint: disable=unsubscriptable-object """Load expert models.""" if expert_weights is not None: self.expert_weights = expert_weights @@ -122,14 +124,14 @@ def load_models(self, experts: list[str] = None, expert_weights: list = None): # expert = AutoModelForMaskedLM.from_pretrained( expert, forced_bos_token_id=self.tokenizer.bos_token_id, - device_map = "auto" + device_map="auto", ) # Load HuggingFace models else: expert = AutoModelForCausalLM.from_pretrained( expert, forced_bos_token_id=self.tokenizer.bos_token_id, - device_map = "auto" + device_map="auto", ) expert_models.append(expert) self.experts = expert_models