diff --git a/apps/autointerp/neuronpedia_autointerp/routes/explain/default.py b/apps/autointerp/neuronpedia_autointerp/routes/explain/default.py index 17424b284..a9da6387c 100644 --- a/apps/autointerp/neuronpedia_autointerp/routes/explain/default.py +++ b/apps/autointerp/neuronpedia_autointerp/routes/explain/default.py @@ -1,6 +1,10 @@ import traceback import torch +from delphi.clients import OpenRouter +from delphi.explainers import DefaultExplainer +from delphi.explainers.explainer import ExplainerResult +from delphi.latents.latents import Example, Latent, LatentRecord from fastapi import HTTPException from neuronpedia_autointerp_client.models.explain_default_post200_response import ( ExplainDefaultPost200Response, @@ -8,10 +12,6 @@ from neuronpedia_autointerp_client.models.explain_default_post_request import ( ExplainDefaultPostRequest, ) -from sae_auto_interp.clients import OpenRouter -from sae_auto_interp.explainers import DefaultExplainer -from sae_auto_interp.explainers.explainer import ExplainerResult -from sae_auto_interp.features import Example, Feature, FeatureRecord async def explain_default(request: ExplainDefaultPostRequest): @@ -19,17 +19,21 @@ async def explain_default(request: ExplainDefaultPostRequest): Generate an explanation for a given set of activations. """ try: - feature = Feature("feature", 0) + feature = Latent("feature", 0) examples = [] for activation in request.activations: - example = Example(activation.tokens, torch.tensor(activation.values)) # type: ignore + example = Example( + tokens=activation.tokens, # type: ignore + activations=torch.tensor(activation.values), + str_tokens=activation.tokens, + ) examples.append(example) - feature_record = FeatureRecord(feature) + feature_record = LatentRecord(feature) feature_record.train = examples client = OpenRouter(api_key=request.openrouter_key, model=request.model) - explainer = DefaultExplainer(client, tokenizer=None, threshold=0.6) - result: ExplainerResult = await explainer.__call__(feature_record) # type: ignore + explainer = DefaultExplainer(client, threshold=0.6, activations=False) + result: ExplainerResult = await explainer.__call__(feature_record) return ExplainDefaultPost200Response(explanation=result.explanation) diff --git a/apps/autointerp/neuronpedia_autointerp/routes/score/embedding.py b/apps/autointerp/neuronpedia_autointerp/routes/score/embedding.py index e9f0548d5..31cce3c73 100644 --- a/apps/autointerp/neuronpedia_autointerp/routes/score/embedding.py +++ b/apps/autointerp/neuronpedia_autointerp/routes/score/embedding.py @@ -1,20 +1,25 @@ import traceback import torch -from fastapi import HTTPException -from neuronpedia_autointerp.utils import ( - convert_embedding_output_to_score_embedding_output, - per_feature_scores_embedding, +from delphi.latents.latents import ( + Example, + Latent, + LatentRecord, ) +from delphi.scorers import EmbeddingScorer +from delphi.scorers.scorer import ScorerResult +from fastapi import HTTPException from neuronpedia_autointerp_client.models.score_embedding_post200_response import ( ScoreEmbeddingPost200Response, ) from neuronpedia_autointerp_client.models.score_embedding_post_request import ( ScoreEmbeddingPostRequest, ) -from sae_auto_interp.features import Example, Feature, FeatureRecord -from sae_auto_interp.scorers import EmbeddingScorer -from sae_auto_interp.scorers.scorer import ScorerResult + +from neuronpedia_autointerp.utils import ( + convert_embedding_output_to_score_embedding_output, + per_feature_scores_embedding, +) async def generate_score_embedding(request: ScoreEmbeddingPostRequest, model): # type: ignore @@ -30,25 +35,32 @@ async def generate_score_embedding(request: ScoreEmbeddingPostRequest, model): Returns a score based on embedding similarity and a detailed breakdown of the scoring. """ try: - feature = Feature("feature", 0) + feature = Latent("feature", 0) activating_examples = [] non_activating_examples = [] for activation in request.activations: - example = Example(activation.tokens, torch.tensor(activation.values)) # type: ignore + example = Example( + tokens=activation.tokens, # type: ignore + activations=torch.tensor(activation.values), + ) if sum(activation.values) > 0: - activating_examples.append(example) + activating_examples.append( + [ + example + ] # TODO: remove brackets once https://github.com/EleutherAI/delphi/issues/132 is fixed + ) else: non_activating_examples.append(example) - feature_record = FeatureRecord(feature) - feature_record.test = [activating_examples] - feature_record.extra_examples = non_activating_examples # type: ignore - feature_record.random_examples = non_activating_examples # type: ignore + feature_record = LatentRecord(feature) + feature_record.test = activating_examples + feature_record.not_active = non_activating_examples + feature_record.extra_examples = non_activating_examples feature_record.explanation = request.explanation # type: ignore scorer = EmbeddingScorer(model) - result: ScorerResult = await scorer.__call__(feature_record) # type: ignore + result: ScorerResult = await scorer.__call__(feature_record) score = per_feature_scores_embedding(result.score) breakdown = [ convert_embedding_output_to_score_embedding_output(item) diff --git a/apps/autointerp/neuronpedia_autointerp/routes/score/fuzz_detection.py b/apps/autointerp/neuronpedia_autointerp/routes/score/fuzz_detection.py index f08eff843..a80eee9fa 100644 --- a/apps/autointerp/neuronpedia_autointerp/routes/score/fuzz_detection.py +++ b/apps/autointerp/neuronpedia_autointerp/routes/score/fuzz_detection.py @@ -1,6 +1,15 @@ import traceback import torch +from delphi.clients import OpenRouter +from delphi.latents.latents import ( + ActivatingExample, + Latent, + LatentRecord, + NonActivatingExample, +) +from delphi.scorers import DetectionScorer, FuzzingScorer +from delphi.scorers.scorer import ScorerResult from fastapi import HTTPException from neuronpedia_autointerp_client.models.np_score_fuzz_detection_type import ( NPScoreFuzzDetectionType, @@ -11,10 +20,6 @@ from neuronpedia_autointerp_client.models.score_fuzz_detection_post_request import ( ScoreFuzzDetectionPostRequest, ) -from sae_auto_interp.clients import OpenRouter -from sae_auto_interp.features import Example, Feature, FeatureRecord -from sae_auto_interp.scorers import DetectionScorer, FuzzingScorer -from sae_auto_interp.scorers.scorer import ScorerResult from neuronpedia_autointerp.utils import ( convert_classifier_output_to_score_classifier_output, @@ -39,29 +44,39 @@ async def generate_score_fuzz_detection(request: ScoreFuzzDetectionPostRequest): We currently show 5 examples at a time (batch_size=5). """ try: - feature = Feature("feature", 0) + feature = Latent("feature", 0) activating_examples = [] non_activating_examples = [] for activation in request.activations: - example = Example(activation.tokens, torch.tensor(activation.values)) # type: ignore if sum(activation.values) > 0: + example = ActivatingExample( + tokens=activation.tokens, # type: ignore + activations=torch.tensor(activation.values), + str_tokens=activation.tokens, + quantile=1, + ) activating_examples.append(example) else: + example = NonActivatingExample( + tokens=activation.tokens, # type: ignore + activations=torch.tensor(activation.values), + str_tokens=activation.tokens, + distance=-1, + ) non_activating_examples.append(example) - feature_record = FeatureRecord(feature) - feature_record.test = [activating_examples] - feature_record.extra_examples = non_activating_examples # type: ignore - feature_record.random_examples = non_activating_examples # type: ignore - feature_record.explanation = request.explanation # type: ignore + feature_record = LatentRecord(feature) + feature_record.test = activating_examples + feature_record.not_active = non_activating_examples + feature_record.extra_examples = non_activating_examples + feature_record.explanation = request.explanation client = OpenRouter(api_key=request.openrouter_key, model=request.model) if request.type == NPScoreFuzzDetectionType.FUZZ: scorer = FuzzingScorer( client, - tokenizer=None, # type: ignore batch_size=5, verbose=False, log_prob=False, @@ -69,7 +84,6 @@ async def generate_score_fuzz_detection(request: ScoreFuzzDetectionPostRequest): elif request.type == NPScoreFuzzDetectionType.DETECTION: scorer = DetectionScorer( client, - tokenizer=None, # type: ignore batch_size=5, verbose=False, log_prob=False, @@ -77,7 +91,7 @@ async def generate_score_fuzz_detection(request: ScoreFuzzDetectionPostRequest): else: raise HTTPException(status_code=400, detail="Invalid scoring type") - result: ScorerResult = await scorer.__call__(feature_record) # type: ignore + result: ScorerResult = await scorer.__call__(feature_record) score = per_feature_scores_fuzz_detection(result.score) breakdown = [ diff --git a/apps/autointerp/neuronpedia_autointerp/utils.py b/apps/autointerp/neuronpedia_autointerp/utils.py index 06a4d7a65..aaa1a8e28 100644 --- a/apps/autointerp/neuronpedia_autointerp/utils.py +++ b/apps/autointerp/neuronpedia_autointerp/utils.py @@ -14,25 +14,23 @@ def per_feature_scores_embedding(score_data: list[dict[Any, Any]]) -> float: data_df = pd.DataFrame(score_data) - data_df["ground_truth"] = data_df["distance"] > 0 - auc_score = float(roc_auc_score(data_df["ground_truth"], data_df["similarity"])) + data_df["activating"] = data_df["distance"] > 0 + auc_score = float(roc_auc_score(data_df["activating"], data_df["similarity"])) return auc_score # noqa: RET504 def calculate_balanced_accuracy(dataframe: pd.DataFrame) -> float: tp = len( - dataframe[(dataframe["ground_truth"] == True) & (dataframe["correct"] == True)] + dataframe[(dataframe["activating"] == True) & (dataframe["correct"] == True)] ) tn = len( - dataframe[(dataframe["ground_truth"] == False) & (dataframe["correct"] == True)] + dataframe[(dataframe["activating"] == False) & (dataframe["correct"] == True)] ) fp = len( - dataframe[ - (dataframe["ground_truth"] == False) & (dataframe["correct"] == False) - ] + dataframe[(dataframe["activating"] == False) & (dataframe["correct"] == False)] ) fn = len( - dataframe[(dataframe["ground_truth"] == True) & (dataframe["correct"] == False)] + dataframe[(dataframe["activating"] == True) & (dataframe["correct"] == False)] ) recall = 0 if tp + fn == 0 else tp / (tp + fn) return 0 if tn + fp == 0 else (recall + tn / (tn + fp)) / 2 @@ -50,18 +48,12 @@ def per_feature_scores_fuzz_detection( def convert_classifier_output_to_score_classifier_output( classifier_output: ScoreFuzzDetectionPost200ResponseBreakdownInner, ) -> ScoreFuzzDetectionPost200ResponseBreakdownInner: - # if prediction is -1, count it as false (it's an error state) - # https://github.com/EleutherAI/sae-auto-interp/issues/46 - # TODO: fix this in sae-auto-interp - it should be a boolean as specified in: https://github.com/EleutherAI/sae-auto-interp/blob/3659ff3bfefbe2628d37484e5bcc0087a5b10a27/sae_auto_interp/scorers/classifier/sample.py#L19 - if classifier_output.prediction == -1: - classifier_output.prediction = False return ScoreFuzzDetectionPost200ResponseBreakdownInner( str_tokens=classifier_output.str_tokens, activations=classifier_output.activations, distance=classifier_output.distance, - ground_truth=classifier_output.ground_truth, + activating=classifier_output.activating, prediction=bool(classifier_output.prediction), - highlighted=classifier_output.highlighted, probability=classifier_output.probability, correct=classifier_output.correct, ) diff --git a/apps/autointerp/poetry.lock b/apps/autointerp/poetry.lock index fe685ef51..a4bfeeadd 100644 --- a/apps/autointerp/poetry.lock +++ b/apps/autointerp/poetry.lock @@ -2,14 +2,14 @@ [[package]] name = "accelerate" -version = "1.5.2" +version = "1.7.0" description = "Accelerate" optional = false python-versions = ">=3.9.0" groups = ["main"] files = [ - {file = "accelerate-1.5.2-py3-none-any.whl", hash = "sha256:68a3b272f6a6ffebb457bdc138581a2bf52efad6a5e0214dc46675f3edd98792"}, - {file = "accelerate-1.5.2.tar.gz", hash = "sha256:a1cf39473edc0e42772a9d9a18c9eb1ce8ffd9e1719dc0ab80670f5c1fd4dc43"}, + {file = "accelerate-1.7.0-py3-none-any.whl", hash = "sha256:cf57165cca28769c6cf2650812371c81b18e05743dfa3c748524b1bb4f2b272f"}, + {file = "accelerate-1.7.0.tar.gz", hash = "sha256:e8a2a5503d6237b9eee73cc8d36cf543f9c2d8dd2c6713450b322f5e6d53a610"}, ] [package.dependencies] @@ -23,13 +23,14 @@ torch = ">=2.0.0" [package.extras] deepspeed = ["deepspeed"] -dev = ["bitsandbytes", "black (>=23.1,<24.0)", "datasets", "diffusers", "evaluate", "hf-doc-builder (>=0.3.0)", "parameterized", "pytest (>=7.2.0,<=8.0.0)", "pytest-order", "pytest-subtests", 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cover = ["pytest-cov"] doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"] enabler = ["pytest-enabler (>=2.2)"] -test = ["big-O", "importlib-resources ; python_version < \"3.9\"", "jaraco.functools", "jaraco.itertools", "jaraco.test", "more-itertools", "pytest (>=6,!=8.1.*)", "pytest-ignore-flaky"] +test = ["big-O", "importlib_resources ; python_version < \"3.9\"", "jaraco.functools", "jaraco.itertools", "jaraco.test", "more_itertools", "pytest (>=6,!=8.1.*)", "pytest-ignore-flaky"] type = ["pytest-mypy"] [metadata] lock-version = "2.1" python-versions = ">=3.10,<4.0" -content-hash = "b9cc5f9ef8702e1e770bf05ba993031c8d0e133c3ab608cd4ac2053c0727f3da" +content-hash = "5e1d62d26739e3726a0431e9897dd2422732621c1e3a75634e8220e8b5620d50" diff --git a/apps/autointerp/pyproject.toml b/apps/autointerp/pyproject.toml index a086415a3..0ee09bf34 100644 --- a/apps/autointerp/pyproject.toml +++ b/apps/autointerp/pyproject.toml @@ -13,9 +13,9 @@ fastapi = "^0.115.0" pydantic = "^2.0.0" uvicorn = "^0.34.0" python-dotenv = "^1.1.0" -neuronpedia-autointerp-client = "^1.0.0" +neuronpedia-autointerp-client = {path = "../../packages/python/neuronpedia-autointerp-client"} sentry-sdk = { extras = ["fastapi"], version = "^2.20.0" } -sae-auto-interp = { git = "https://github.com/hijohnnylin/sae-auto-interp" } +eai-delphi = "0.0.2" bitsandbytes = "==0.42.0" torchtyping = "^0.1.5" @@ -37,8 +37,6 @@ build-backend = "poetry.core.masonry.api" "typing.List".msg = "Use 'list' instead" [tool.pyright] -# Add this line to ignore import errors for missing libraries -reportMissingImports = "none" typeCheckingMode = "strict" reportMissingTypeStubs = "none" reportUnknownMemberType = "none" diff --git a/apps/autointerp/tests/unit/test_utils.py b/apps/autointerp/tests/unit/test_utils.py index 310365f3e..11ad928ec 100644 --- a/apps/autointerp/tests/unit/test_utils.py +++ b/apps/autointerp/tests/unit/test_utils.py @@ -32,10 +32,10 @@ def test_per_feature_scores_embedding(): def test_calculate_balanced_accuracy_positives_and_negatives(): df = pd.DataFrame( [ - {"ground_truth": True, "correct": True}, # TP - {"ground_truth": True, "correct": False}, # FN - {"ground_truth": False, "correct": True}, # TN - {"ground_truth": False, "correct": False}, # FP + {"activating": True, "correct": True}, # TP + {"activating": True, "correct": False}, # FN + {"activating": False, "correct": True}, # TN + {"activating": False, "correct": False}, # FP ] ) balanced_accuracy = calculate_balanced_accuracy(df) @@ -48,8 +48,8 @@ def test_calculate_balanced_accuracy_positives_and_negatives(): def test_calculate_balanced_accuracy_no_positives(): df = pd.DataFrame( [ - {"ground_truth": False, "correct": True}, # TN - {"ground_truth": False, "correct": False}, # FP + {"activating": False, "correct": True}, # TN + {"activating": False, "correct": False}, # FP ] ) balanced_accuracy = calculate_balanced_accuracy(df) @@ -62,8 +62,8 @@ def test_calculate_balanced_accuracy_no_positives(): def test_calculate_balanced_accuracy_no_negatives(): df = pd.DataFrame( [ - {"ground_truth": True, "correct": True}, # TP - {"ground_truth": True, "correct": False}, # FP + {"activating": True, "correct": True}, # TP + {"activating": True, "correct": False}, # FP ] ) balanced_accuracy = calculate_balanced_accuracy(df) @@ -82,12 +82,12 @@ def dataframe_wrapper(data: list[Any], *args: Any, **kwargs: Any) -> pd.DataFram monkeypatch.setattr(pd, "DataFrame", dataframe_wrapper) response_1 = ScoreFuzzDetectionPost200ResponseBreakdownInner( - ground_truth=True, + activating=True, prediction=True, correct=True, ) response_2 = ScoreFuzzDetectionPost200ResponseBreakdownInner( - ground_truth=False, + activating=False, prediction=False, correct=True, ) @@ -96,7 +96,7 @@ def dataframe_wrapper(data: list[Any], *args: Any, **kwargs: Any) -> pd.DataFram # which is invalid according to the model, we can test how our function handles # this error state response_3 = ScoreFuzzDetectionPost200ResponseBreakdownInner.model_construct( - ground_truth=False, + activating=False, prediction=-1, correct=False, ) @@ -106,14 +106,13 @@ def dataframe_wrapper(data: list[Any], *args: Any, **kwargs: Any) -> pd.DataFram assert pytest.approx(balanced_accuracy) == 1.0 -def test_convert_classifier_output_negative_prediction(): +def test_convert_classifier_output_no_prediction(): expected_response = ScoreFuzzDetectionPost200ResponseBreakdownInner.model_construct( str_tokens=["test"], activations=[0.1], distance=1, - ground_truth=True, - prediction=-1, - highlighted=False, + activating=True, + prediction=None, probability=0.7, correct=False, ) @@ -122,8 +121,7 @@ def test_convert_classifier_output_negative_prediction(): assert response.str_tokens == expected_response.str_tokens assert response.activations == expected_response.activations assert response.distance == expected_response.distance - assert response.ground_truth == expected_response.ground_truth - assert response.highlighted == expected_response.highlighted + assert response.activating == expected_response.activating assert response.probability == expected_response.probability assert response.correct == expected_response.correct @@ -133,9 +131,8 @@ def test_convert_classifier_output_true_prediction(): str_tokens=["test2"], activations=[0.2], distance=2, - ground_truth=False, + activating=False, prediction=True, - highlighted=True, probability=0.8, correct=True, ) diff --git a/packages/python/neuronpedia-autointerp-client/.github/workflows/python.yml b/packages/python/neuronpedia-autointerp-client/.github/workflows/python.yml index 7a1d8fc84..19a08994e 100644 --- a/packages/python/neuronpedia-autointerp-client/.github/workflows/python.yml +++ b/packages/python/neuronpedia-autointerp-client/.github/workflows/python.yml @@ -28,4 +28,4 @@ jobs: pip install -r test-requirements.txt - name: Test with pytest run: | - pytest --cov={{packageName}} + pytest --cov=neuronpedia_autointerp_client diff --git a/packages/python/neuronpedia-autointerp-client/.openapi-generator/VERSION b/packages/python/neuronpedia-autointerp-client/.openapi-generator/VERSION index b23eb2752..5f84a81db 100644 --- a/packages/python/neuronpedia-autointerp-client/.openapi-generator/VERSION +++ b/packages/python/neuronpedia-autointerp-client/.openapi-generator/VERSION @@ -1 +1 @@ -7.11.0 +7.12.0 diff --git a/packages/python/neuronpedia-autointerp-client/README.md b/packages/python/neuronpedia-autointerp-client/README.md index c114dbe19..40c49acb2 100644 --- a/packages/python/neuronpedia-autointerp-client/README.md +++ b/packages/python/neuronpedia-autointerp-client/README.md @@ -4,8 +4,8 @@ No description provided (generated by Openapi Generator https://github.com/opena This Python package is automatically generated by the [OpenAPI Generator](https://openapi-generator.tech) project: - API version: 1.0.0 -- Package version: 1.0.0 -- Generator version: 7.11.0 +- Package version: 2.0.0 +- Generator version: 7.12.0 - Build package: org.openapitools.codegen.languages.PythonClientCodegen ## Requirements. diff --git a/packages/python/neuronpedia-autointerp-client/docs/ScoreFuzzDetectionPost200ResponseBreakdownInner.md b/packages/python/neuronpedia-autointerp-client/docs/ScoreFuzzDetectionPost200ResponseBreakdownInner.md index bc3932d66..c8b48bb8a 100644 --- a/packages/python/neuronpedia-autointerp-client/docs/ScoreFuzzDetectionPost200ResponseBreakdownInner.md +++ b/packages/python/neuronpedia-autointerp-client/docs/ScoreFuzzDetectionPost200ResponseBreakdownInner.md @@ -1,6 +1,6 @@ # ScoreFuzzDetectionPost200ResponseBreakdownInner -The \"scorer.__call__\" result's score breakdown. Type copied from https://github.com/EleutherAI/sae-auto-interp/blob/3659ff3bfefbe2628d37484e5bcc0087a5b10a27/sae_auto_interp/scorers/classifier/sample.py#L19 +The \"scorer.__call__\" result's score breakdown. Type copied from https://github.com/EleutherAI/delphi/blob/10b855691891f39df96bbc6247ccc7cdfb243ede/delphi/scorers/classifier/sample.py#L18 ## Properties @@ -8,10 +8,9 @@ Name | Type | Description | Notes ------------ | ------------- | ------------- | ------------- **str_tokens** | **List[str]** | List of strings | [optional] **activations** | **List[float]** | List of floats | [optional] -**distance** | **int** | Quantile or neighbor distance | [optional] -**ground_truth** | **bool** | Whether the example is activating or not | [optional] +**distance** | **float** | Quantile or neighbor distance | [optional] +**activating** | **bool** | Whether the example is activating or not | [optional] **prediction** | **bool** | Whether the model predicted the example activating or not | [optional] [default to False] -**highlighted** | **bool** | Whether the sample is highlighted | [optional] [default to False] **probability** | **float** | The probability of the example activating | [optional] [default to 0.0] **correct** | **bool** | Whether the prediction is correct | [optional] [default to False] diff --git a/packages/python/neuronpedia-autointerp-client/neuronpedia_autointerp_client/__init__.py b/packages/python/neuronpedia-autointerp-client/neuronpedia_autointerp_client/__init__.py index 009b3cafe..90de108c4 100644 --- a/packages/python/neuronpedia-autointerp-client/neuronpedia_autointerp_client/__init__.py +++ b/packages/python/neuronpedia-autointerp-client/neuronpedia_autointerp_client/__init__.py @@ -15,7 +15,7 @@ """ # noqa: E501 -__version__ = "1.0.0" +__version__ = "2.0.0" # import apis into sdk package from neuronpedia_autointerp_client.api.default_api import DefaultApi diff --git a/packages/python/neuronpedia-autointerp-client/neuronpedia_autointerp_client/api_client.py b/packages/python/neuronpedia-autointerp-client/neuronpedia_autointerp_client/api_client.py index 966075a8c..7755916b5 100644 --- a/packages/python/neuronpedia-autointerp-client/neuronpedia_autointerp_client/api_client.py +++ b/packages/python/neuronpedia-autointerp-client/neuronpedia_autointerp_client/api_client.py @@ -91,7 +91,7 @@ def __init__( self.default_headers[header_name] = header_value self.cookie = cookie # Set default User-Agent. - self.user_agent = 'OpenAPI-Generator/1.0.0/python' + self.user_agent = 'OpenAPI-Generator/2.0.0/python' self.client_side_validation = configuration.client_side_validation def __enter__(self): diff --git a/packages/python/neuronpedia-autointerp-client/neuronpedia_autointerp_client/configuration.py b/packages/python/neuronpedia-autointerp-client/neuronpedia_autointerp_client/configuration.py index 1fbaada85..bdfb3860f 100644 --- a/packages/python/neuronpedia-autointerp-client/neuronpedia_autointerp_client/configuration.py +++ b/packages/python/neuronpedia-autointerp-client/neuronpedia_autointerp_client/configuration.py @@ -19,7 +19,7 @@ from logging import FileHandler import multiprocessing import sys -from typing import Any, ClassVar, Dict, List, Literal, Optional, TypedDict +from typing import Any, ClassVar, Dict, List, Literal, Optional, TypedDict, Union from typing_extensions import NotRequired, Self import urllib3 @@ -162,6 +162,8 @@ class Configuration: :param ssl_ca_cert: str - the path to a file of concatenated CA certificates in PEM format. :param retries: Number of retries for API requests. + :param ca_cert_data: verify the peer using concatenated CA certificate data + in PEM (str) or DER (bytes) format. :Example: @@ -195,13 +197,14 @@ def __init__( username: Optional[str]=None, password: Optional[str]=None, access_token: Optional[str]=None, - server_index: Optional[int]=None, + server_index: Optional[int]=None, server_variables: Optional[ServerVariablesT]=None, server_operation_index: Optional[Dict[int, int]]=None, server_operation_variables: Optional[Dict[int, ServerVariablesT]]=None, ignore_operation_servers: bool=False, ssl_ca_cert: Optional[str]=None, retries: Optional[int] = None, + ca_cert_data: Optional[Union[str, bytes]] = None, *, debug: Optional[bool] = None, ) -> None: @@ -279,6 +282,10 @@ def __init__( self.ssl_ca_cert = ssl_ca_cert """Set this to customize the certificate file to verify the peer. """ + self.ca_cert_data = ca_cert_data + """Set this to verify the peer using PEM (str) or DER (bytes) + certificate data. + """ self.cert_file = None """client certificate file """ @@ -525,7 +532,7 @@ def to_debug_report(self) -> str: "OS: {env}\n"\ "Python Version: {pyversion}\n"\ "Version of the API: 1.0.0\n"\ - "SDK Package Version: 1.0.0".\ + "SDK Package Version: 2.0.0".\ format(env=sys.platform, pyversion=sys.version) def get_host_settings(self) -> List[HostSetting]: diff --git a/packages/python/neuronpedia-autointerp-client/neuronpedia_autointerp_client/models/score_fuzz_detection_post200_response_breakdown_inner.py b/packages/python/neuronpedia-autointerp-client/neuronpedia_autointerp_client/models/score_fuzz_detection_post200_response_breakdown_inner.py index 2ff092c21..7f822ecc5 100644 --- a/packages/python/neuronpedia-autointerp-client/neuronpedia_autointerp_client/models/score_fuzz_detection_post200_response_breakdown_inner.py +++ b/packages/python/neuronpedia-autointerp-client/neuronpedia_autointerp_client/models/score_fuzz_detection_post200_response_breakdown_inner.py @@ -25,17 +25,16 @@ class ScoreFuzzDetectionPost200ResponseBreakdownInner(BaseModel): """ - The \"scorer.__call__\" result's score breakdown. Type copied from https://github.com/EleutherAI/sae-auto-interp/blob/3659ff3bfefbe2628d37484e5bcc0087a5b10a27/sae_auto_interp/scorers/classifier/sample.py#L19 + The \"scorer.__call__\" result's score breakdown. Type copied from https://github.com/EleutherAI/delphi/blob/10b855691891f39df96bbc6247ccc7cdfb243ede/delphi/scorers/classifier/sample.py#L18 """ # noqa: E501 str_tokens: Optional[List[StrictStr]] = Field(default=None, description="List of strings") activations: Optional[List[Union[StrictFloat, StrictInt]]] = Field(default=None, description="List of floats") - distance: Optional[StrictInt] = Field(default=None, description="Quantile or neighbor distance") - ground_truth: Optional[StrictBool] = Field(default=None, description="Whether the example is activating or not") + distance: Optional[Union[StrictFloat, StrictInt]] = Field(default=None, description="Quantile or neighbor distance") + activating: Optional[StrictBool] = Field(default=None, description="Whether the example is activating or not") prediction: Optional[StrictBool] = Field(default=False, description="Whether the model predicted the example activating or not") - highlighted: Optional[StrictBool] = Field(default=False, description="Whether the sample is highlighted") probability: Optional[Union[StrictFloat, StrictInt]] = Field(default=0.0, description="The probability of the example activating") correct: Optional[StrictBool] = Field(default=False, description="Whether the prediction is correct") - __properties: ClassVar[List[str]] = ["str_tokens", "activations", "distance", "ground_truth", "prediction", "highlighted", "probability", "correct"] + __properties: ClassVar[List[str]] = ["str_tokens", "activations", "distance", "activating", "prediction", "probability", "correct"] model_config = ConfigDict( populate_by_name=True, @@ -76,6 +75,21 @@ def to_dict(self) -> Dict[str, Any]: exclude=excluded_fields, exclude_none=True, ) + # set to None if prediction (nullable) is None + # and model_fields_set contains the field + if self.prediction is None and "prediction" in self.model_fields_set: + _dict['prediction'] = None + + # set to None if probability (nullable) is None + # and model_fields_set contains the field + if self.probability is None and "probability" in self.model_fields_set: + _dict['probability'] = None + + # set to None if correct (nullable) is None + # and model_fields_set contains the field + if self.correct is None and "correct" in self.model_fields_set: + _dict['correct'] = None + return _dict @classmethod @@ -91,9 +105,8 @@ def from_dict(cls, obj: Optional[Dict[str, Any]]) -> Optional[Self]: "str_tokens": obj.get("str_tokens"), "activations": obj.get("activations"), "distance": obj.get("distance"), - "ground_truth": obj.get("ground_truth"), + "activating": obj.get("activating"), "prediction": obj.get("prediction") if obj.get("prediction") is not None else False, - "highlighted": obj.get("highlighted") if obj.get("highlighted") is not None else False, "probability": obj.get("probability") if obj.get("probability") is not None else 0.0, "correct": obj.get("correct") if obj.get("correct") is not None else False }) diff --git a/packages/python/neuronpedia-autointerp-client/neuronpedia_autointerp_client/rest.py b/packages/python/neuronpedia-autointerp-client/neuronpedia_autointerp_client/rest.py index 58ba2dfc3..c1f1061ec 100644 --- a/packages/python/neuronpedia-autointerp-client/neuronpedia_autointerp_client/rest.py +++ b/packages/python/neuronpedia-autointerp-client/neuronpedia_autointerp_client/rest.py @@ -77,6 +77,7 @@ def __init__(self, configuration) -> None: "ca_certs": configuration.ssl_ca_cert, "cert_file": configuration.cert_file, "key_file": configuration.key_file, + "ca_cert_data": configuration.ca_cert_data, } if configuration.assert_hostname is not None: pool_args['assert_hostname'] = ( diff --git a/packages/python/neuronpedia-autointerp-client/pyproject.toml b/packages/python/neuronpedia-autointerp-client/pyproject.toml index a83967ea3..54ed3c7d1 100644 --- a/packages/python/neuronpedia-autointerp-client/pyproject.toml +++ b/packages/python/neuronpedia-autointerp-client/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "neuronpedia_autointerp_client" -version = "1.0.0" +version = "2.0.0" description = "Neuronpedia - AutoInterp Server" authors = ["OpenAPI Generator Community "] license = "MIT" diff --git a/packages/python/neuronpedia-autointerp-client/setup.py b/packages/python/neuronpedia-autointerp-client/setup.py index 50d35314b..95a1ae913 100644 --- a/packages/python/neuronpedia-autointerp-client/setup.py +++ b/packages/python/neuronpedia-autointerp-client/setup.py @@ -22,7 +22,7 @@ # prerequisite: setuptools # http://pypi.python.org/pypi/setuptools NAME = "neuronpedia-autointerp-client" -VERSION = "1.0.0" +VERSION = "2.0.0" PYTHON_REQUIRES = ">= 3.8" REQUIRES = [ "urllib3 >= 1.25.3, < 3.0.0", diff --git a/packages/python/neuronpedia-autointerp-client/test/test_score_fuzz_detection_post200_response.py b/packages/python/neuronpedia-autointerp-client/test/test_score_fuzz_detection_post200_response.py index c8677f8ae..6f1eac705 100644 --- a/packages/python/neuronpedia-autointerp-client/test/test_score_fuzz_detection_post200_response.py +++ b/packages/python/neuronpedia-autointerp-client/test/test_score_fuzz_detection_post200_response.py @@ -45,10 +45,9 @@ def make_instance(self, include_optional) -> ScoreFuzzDetectionPost200Response: activations = [ 1.337 ], - distance = 56, - ground_truth = True, + distance = 1.337, + activating = True, prediction = True, - highlighted = True, probability = 1.337, correct = True, ) ] @@ -64,10 +63,9 @@ def make_instance(self, include_optional) -> ScoreFuzzDetectionPost200Response: activations = [ 1.337 ], - distance = 56, - ground_truth = True, + distance = 1.337, + activating = True, prediction = True, - highlighted = True, probability = 1.337, correct = True, ) ], diff --git a/packages/python/neuronpedia-autointerp-client/test/test_score_fuzz_detection_post200_response_breakdown_inner.py b/packages/python/neuronpedia-autointerp-client/test/test_score_fuzz_detection_post200_response_breakdown_inner.py index 5268d7866..df63fc242 100644 --- a/packages/python/neuronpedia-autointerp-client/test/test_score_fuzz_detection_post200_response_breakdown_inner.py +++ b/packages/python/neuronpedia-autointerp-client/test/test_score_fuzz_detection_post200_response_breakdown_inner.py @@ -42,10 +42,9 @@ def make_instance(self, include_optional) -> ScoreFuzzDetectionPost200ResponseBr activations = [ 1.337 ], - distance = 56, - ground_truth = True, + distance = 1.337, + activating = True, prediction = True, - highlighted = True, probability = 1.337, correct = True ) diff --git a/packages/typescript/neuronpedia-autointerp-client/.openapi-generator/VERSION b/packages/typescript/neuronpedia-autointerp-client/.openapi-generator/VERSION index b23eb2752..5f84a81db 100644 --- a/packages/typescript/neuronpedia-autointerp-client/.openapi-generator/VERSION +++ b/packages/typescript/neuronpedia-autointerp-client/.openapi-generator/VERSION @@ -1 +1 @@ -7.11.0 +7.12.0 diff --git a/packages/typescript/neuronpedia-autointerp-client/README.md b/packages/typescript/neuronpedia-autointerp-client/README.md index e7a3cee79..5c989d196 100644 --- a/packages/typescript/neuronpedia-autointerp-client/README.md +++ b/packages/typescript/neuronpedia-autointerp-client/README.md @@ -1,4 +1,4 @@ -## neuronpedia-autointerp-client@1.0.0 +## neuronpedia-autointerp-client@2.0.0 This generator creates TypeScript/JavaScript client that utilizes [Fetch API](https://fetch.spec.whatwg.org/). The generated Node module can be used in the following environments: @@ -36,7 +36,7 @@ navigate to the folder of your consuming project and run one of the following co _published:_ ``` -npm install neuronpedia-autointerp-client@1.0.0 --save +npm install neuronpedia-autointerp-client@2.0.0 --save ``` _unPublished (not recommended):_ diff --git a/packages/typescript/neuronpedia-autointerp-client/package.json b/packages/typescript/neuronpedia-autointerp-client/package.json index c38db68bb..cbabef84a 100644 --- a/packages/typescript/neuronpedia-autointerp-client/package.json +++ b/packages/typescript/neuronpedia-autointerp-client/package.json @@ -1,6 +1,6 @@ { "name": "neuronpedia-autointerp-client", - "version": "1.0.0", + "version": "2.0.0", "description": "OpenAPI client for neuronpedia-autointerp-client", "author": "OpenAPI-Generator", "repository": { diff --git a/packages/typescript/neuronpedia-autointerp-client/src/models/ScoreFuzzDetectionPost200ResponseBreakdownInner.ts b/packages/typescript/neuronpedia-autointerp-client/src/models/ScoreFuzzDetectionPost200ResponseBreakdownInner.ts index 6d7b39d06..66f5c74d9 100644 --- a/packages/typescript/neuronpedia-autointerp-client/src/models/ScoreFuzzDetectionPost200ResponseBreakdownInner.ts +++ b/packages/typescript/neuronpedia-autointerp-client/src/models/ScoreFuzzDetectionPost200ResponseBreakdownInner.ts @@ -14,7 +14,7 @@ import { mapValues } from '../runtime'; /** - * The "scorer.__call__" result's score breakdown. Type copied from https://github.com/EleutherAI/sae-auto-interp/blob/3659ff3bfefbe2628d37484e5bcc0087a5b10a27/sae_auto_interp/scorers/classifier/sample.py#L19 + * The "scorer.__call__" result's score breakdown. Type copied from https://github.com/EleutherAI/delphi/blob/10b855691891f39df96bbc6247ccc7cdfb243ede/delphi/scorers/classifier/sample.py#L18 * @export * @interface ScoreFuzzDetectionPost200ResponseBreakdownInner */ @@ -42,31 +42,25 @@ export interface ScoreFuzzDetectionPost200ResponseBreakdownInner { * @type {boolean} * @memberof ScoreFuzzDetectionPost200ResponseBreakdownInner */ - groundTruth?: boolean; + activating?: boolean; /** * Whether the model predicted the example activating or not * @type {boolean} * @memberof ScoreFuzzDetectionPost200ResponseBreakdownInner */ - prediction?: boolean; - /** - * Whether the sample is highlighted - * @type {boolean} - * @memberof ScoreFuzzDetectionPost200ResponseBreakdownInner - */ - highlighted?: boolean; + prediction?: boolean | null; /** * The probability of the example activating * @type {number} * @memberof ScoreFuzzDetectionPost200ResponseBreakdownInner */ - probability?: number; + probability?: number | null; /** * Whether the prediction is correct * @type {boolean} * @memberof ScoreFuzzDetectionPost200ResponseBreakdownInner */ - correct?: boolean; + correct?: boolean | null; } /** @@ -89,9 +83,8 @@ export function ScoreFuzzDetectionPost200ResponseBreakdownInnerFromJSONTyped(jso 'strTokens': json['str_tokens'] == null ? undefined : json['str_tokens'], 'activations': json['activations'] == null ? undefined : json['activations'], 'distance': json['distance'] == null ? undefined : json['distance'], - 'groundTruth': json['ground_truth'] == null ? undefined : json['ground_truth'], + 'activating': json['activating'] == null ? undefined : json['activating'], 'prediction': json['prediction'] == null ? undefined : json['prediction'], - 'highlighted': json['highlighted'] == null ? undefined : json['highlighted'], 'probability': json['probability'] == null ? undefined : json['probability'], 'correct': json['correct'] == null ? undefined : json['correct'], }; @@ -111,9 +104,8 @@ export function ScoreFuzzDetectionPost200ResponseBreakdownInnerToJSONTyped(value 'str_tokens': value['strTokens'], 'activations': value['activations'], 'distance': value['distance'], - 'ground_truth': value['groundTruth'], + 'activating': value['activating'], 'prediction': value['prediction'], - 'highlighted': value['highlighted'], 'probability': value['probability'], 'correct': value['correct'], }; diff --git a/schemas/openapi/autointerp/paths/score/fuzz-detection.yaml b/schemas/openapi/autointerp/paths/score/fuzz-detection.yaml index c9cc48889..a09780a7f 100644 --- a/schemas/openapi/autointerp/paths/score/fuzz-detection.yaml +++ b/schemas/openapi/autointerp/paths/score/fuzz-detection.yaml @@ -53,7 +53,7 @@ post: type: array items: type: object - description: The "scorer.__call__" result's score breakdown. Type copied from https://github.com/EleutherAI/sae-auto-interp/blob/3659ff3bfefbe2628d37484e5bcc0087a5b10a27/sae_auto_interp/scorers/classifier/sample.py#L19 + description: The "scorer.__call__" result's score breakdown. Type copied from https://github.com/EleutherAI/delphi/blob/10b855691891f39df96bbc6247ccc7cdfb243ede/delphi/scorers/classifier/sample.py#L18 properties: str_tokens: type: array @@ -67,26 +67,25 @@ post: format: float description: List of floats distance: - type: integer + type: number description: Quantile or neighbor distance - ground_truth: + activating: type: boolean description: Whether the example is activating or not prediction: type: boolean + nullable: true default: false description: Whether the model predicted the example activating or not - highlighted: - type: boolean - default: false - description: Whether the sample is highlighted probability: type: number format: float + nullable: true default: 0.0 description: The probability of the example activating correct: type: boolean + nullable: true default: false description: Whether the prediction is correct description: Detailed breakdown of the classification outputs