From 4df9f78aaef3575052c65f051793a87240c3ab7a Mon Sep 17 00:00:00 2001 From: Roya Javadi Date: Thu, 13 Jun 2024 17:48:12 -0700 Subject: [PATCH 01/10] Added report web endpoint --- deploy/api/__init__.py | 1 + deploy/api/main.py | 204 +++++++++++++++++++++++++++++++ deploy/api/model/eval_request.py | 13 ++ 3 files changed, 218 insertions(+) create mode 100644 deploy/api/__init__.py create mode 100644 deploy/api/main.py create mode 100644 deploy/api/model/eval_request.py diff --git a/deploy/api/__init__.py b/deploy/api/__init__.py new file mode 100644 index 000000000..ebbe15f68 --- /dev/null +++ b/deploy/api/__init__.py @@ -0,0 +1 @@ +"""Web api package.""" diff --git a/deploy/api/main.py b/deploy/api/main.py new file mode 100644 index 000000000..0f6c1af25 --- /dev/null +++ b/deploy/api/main.py @@ -0,0 +1,204 @@ +"""A light weight server for evaluation.""" +import copy +import shutil +from datetime import datetime +from typing import List, Union + +import numpy as np +import pandas as pd +from datasets.arrow_dataset import Dataset +from fastapi import Body, Depends, FastAPI, Form +from fastapi.responses import FileResponse, HTMLResponse +from fastapi.staticfiles import StaticFiles +from fastapi.templating import Jinja2Templates +from typing_extensions import Annotated + +from cyclops.api.model.eval_request import RequestData +from cyclops.evaluate import evaluator +from cyclops.evaluate.metrics import create_metric +from cyclops.evaluate.metrics.experimental import MetricDict +from cyclops.report.plot.classification import ClassificationPlotter +from cyclops.report.report import ModelCardReport +from cyclops.report.utils import flatten_results_dict + + +app = FastAPI() + +app.mount("/static", StaticFiles(directory="static"), name="static") +templates = Jinja2Templates(directory="templates") + +# This endpoint serves the UI +@app.get("/", response_class=HTMLResponse) +async def get_home(): + """Return home page for using evaluate API.""" + return templates.TemplateResponse("index.html", {"request": {"method": "POST"}}) + +@app.post("/evaluate") +async def evaluate_result(preds_prob: Annotated[str, Form()], target: Annotated[str, Form()]): + """Calculate metric and return result from request body.""" + print(type(preds_prob)) + print(type(target)) + + preds_prob = [float(num.strip()) for num in preds_prob.split(",")] + target = [float(num.strip()) for num in target.split(",")] + + # Evaluate and generate report file + df = pd.DataFrame( + data={"target":target, "preds_prob": preds_prob} + ) + _eval(df) + print("generated report.") + return templates.TemplateResponse("smart_test_report.html", {"request": {"method": "GET"}}) + +@app.get("/evaluate") +async def get_result(): + """Calculate metric and return result from request body.""" + return templates.TemplateResponse("smart_test_report.html", {"request": {"method": "GET"}}) + + +def _export(report: ModelCardReport): + """Prepare and export report file.""" + synthetic_timestamps = pd.date_range( + start=datetime.today().date(), periods=10, freq="D" + ).values.astype(str) + + + report._model_card.overview = None + report_path = report.export( + output_filename="smart_test_report.html", + synthetic_timestamp=synthetic_timestamps[0], + last_n_evals=3, + ) + + shutil.copy(f"{report_path}", "./static") + # metric_save = None + for i in range(len(synthetic_timestamps[1:])): + + report._model_card.overview = None + + for metric in report._model_card.quantitative_analysis.performance_metrics: + metric.value = np.clip( + metric.value + np.random.normal(0, 0.1), + 0, + 1, + ) + metric.tests[0].passed = bool(metric.value >= 0.6) + + report_path = report.export( + output_filename="smart_test_report.html", + synthetic_timestamp=synthetic_timestamps[i + 1], + last_n_evals=3, + ) + shutil.copy(f"{report_path}", "./static") + shutil.rmtree("./cyclops_report") + + +def _eval(df: pd.DataFrame): + """Evaluate and return report.""" + report = ModelCardReport() + + data = Dataset.from_pandas(df) + + metric_names = [ + "binary_accuracy", + "binary_precision", + "binary_recall", + "binary_f1_score" + ] + metrics = [ + create_metric(metric_name, experimental=True) for metric_name in metric_names + ] + metric_collection = MetricDict(metrics) + + result = evaluator.evaluate( + dataset=data, + metrics=metric_collection, # type: ignore[list-item] + target_columns="target", + prediction_columns="preds_prob", + ) + results_flat = flatten_results_dict(results=result) + + # Log into report + for name, metric in results_flat["model_for_preds_prob"].items(): + split, name = name.split("/") # noqa: PLW2901 + descriptions = { + "BinaryPrecision": "The proportion of predicted positive instances that are correctly predicted.", + "BinaryRecall": "The proportion of actual positive instances that are correctly predicted. Also known as recall or true positive rate.", + "BinaryAccuracy": "The proportion of all instances that are correctly predicted.", + "BinaryF1Score": "The harmonic mean of precision and recall.", + } + report.log_quantitative_analysis( + "performance", + name=name, + value=metric.tolist(), + description=descriptions[name], + metric_slice=split, + pass_fail_thresholds=0.6, + pass_fail_threshold_fns=lambda x, threshold: bool(x >= threshold), + ) + + # Log plot in report + plotter = ClassificationPlotter(task_type="binary", class_names=["0", "1"]) + plotter.set_template("plotly_white") + + # Extracting the overall classification metric values. + overall_performance = { + metric_name: metric_value + for metric_name, metric_value in result["model_for_preds_prob"]["overall"].items() + if metric_name not in ["BinaryROC", "BinaryPrecisionRecallCurve"] + } + # Plotting the overall classification metric values. + overall_performance_plot = plotter.metrics_value( + overall_performance, + title="Overall Performance", + ) + report.log_plotly_figure( + fig=overall_performance_plot, + caption="Overall Performance", + section_name="quantitative analysis", + ) + + report.log_from_dict( + data={ + "name": "Heart Failure Prediction Model", + "description": "The model was trained on the Kaggle Heart Failure \ + Prediction Dataset to predict risk of heart failure.", + }, + section_name="model_details", +) + + report.log_version( + version_str="0.0.1", + date=str(datetime.today().date()), + description="Initial Release", + ) + report.log_owner( + name="CyclOps Team", + contact="vectorinstitute.github.io/cyclops/", + email="cyclops@vectorinstitute.ai", + ) + report.log_license(identifier="Apache-2.0") + report.log_reference( + link="https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.SGDClassifier.html", # noqa: E501 + ) + + report.log_from_dict( + data={ + "users": [ + {"description": "Hospitals"}, + {"description": "Clinicians"}, + ], + }, + section_name="considerations", +) + report.log_user(description="ML Engineers") + report.log_use_case( + description="Predicting risk of heart failure.", + kind="primary", + ) + + _export(report) + + +if __name__ == "__main__": + app.run(debug=True) diff --git a/deploy/api/model/eval_request.py b/deploy/api/model/eval_request.py new file mode 100644 index 000000000..ef5f3e962 --- /dev/null +++ b/deploy/api/model/eval_request.py @@ -0,0 +1,13 @@ +"""A Modle for requesting evaluation.""" +from typing import List, Union + +from pydantic import BaseModel + + +class RequestData(BaseModel): + """A Modle for requesting evaluation.""" + + target: List[Union[int, float]] + preds_prob: List[float] + metric_slice: str | None = None + metrics: List[str] | None = None From f0753d89a5c3c5370c01efb40cfdad40075fec65 Mon Sep 17 00:00:00 2001 From: Amrit Krishnan Date: Tue, 18 Jun 2024 10:16:23 -0400 Subject: [PATCH 02/10] Restructure deploy dir --- deploy/api/model/eval_request.py | 13 - deploy/{ => models}/README.md | 0 deploy/{ => models}/bentofile.yaml | 0 deploy/{ => models}/deployment.yaml | 0 .../densenet121_res224_all/config.pbtxt | 0 .../heart_failure_prediction/config.pbtxt | 0 .../resnet50_res512_all/config.pbtxt | 0 deploy/{ => models}/service.py | 0 deploy/{ => report}/api/__init__.py | 0 deploy/{ => report}/api/main.py | 70 +-- deploy/report/api/static/.gitkeep | 0 poetry.lock | 563 ++++++++++++++++-- pyproject.toml | 10 +- 13 files changed, 546 insertions(+), 110 deletions(-) delete mode 100644 deploy/api/model/eval_request.py rename deploy/{ => models}/README.md (100%) rename deploy/{ => models}/bentofile.yaml (100%) rename deploy/{ => models}/deployment.yaml (100%) rename deploy/{ => models}/model_repo/densenet121_res224_all/config.pbtxt (100%) rename deploy/{ => models}/model_repo/heart_failure_prediction/config.pbtxt (100%) rename deploy/{ => models}/model_repo/resnet50_res512_all/config.pbtxt (100%) rename deploy/{ => models}/service.py (100%) rename deploy/{ => report}/api/__init__.py (100%) rename deploy/{ => report}/api/main.py (83%) create mode 100644 deploy/report/api/static/.gitkeep diff --git a/deploy/api/model/eval_request.py b/deploy/api/model/eval_request.py deleted file mode 100644 index ef5f3e962..000000000 --- a/deploy/api/model/eval_request.py +++ /dev/null @@ -1,13 +0,0 @@ -"""A Modle for requesting evaluation.""" -from typing import List, Union - -from pydantic import BaseModel - - -class RequestData(BaseModel): - """A Modle for requesting evaluation.""" - - target: List[Union[int, float]] - preds_prob: List[float] - metric_slice: str | None = None - metrics: List[str] | None = None diff --git a/deploy/README.md b/deploy/models/README.md similarity index 100% rename from deploy/README.md rename to deploy/models/README.md diff --git a/deploy/bentofile.yaml b/deploy/models/bentofile.yaml similarity index 100% rename from deploy/bentofile.yaml rename to deploy/models/bentofile.yaml diff --git a/deploy/deployment.yaml b/deploy/models/deployment.yaml similarity index 100% rename from deploy/deployment.yaml rename to deploy/models/deployment.yaml diff --git a/deploy/model_repo/densenet121_res224_all/config.pbtxt b/deploy/models/model_repo/densenet121_res224_all/config.pbtxt similarity index 100% rename from deploy/model_repo/densenet121_res224_all/config.pbtxt rename to deploy/models/model_repo/densenet121_res224_all/config.pbtxt diff --git a/deploy/model_repo/heart_failure_prediction/config.pbtxt b/deploy/models/model_repo/heart_failure_prediction/config.pbtxt similarity index 100% rename from deploy/model_repo/heart_failure_prediction/config.pbtxt rename to deploy/models/model_repo/heart_failure_prediction/config.pbtxt diff --git a/deploy/model_repo/resnet50_res512_all/config.pbtxt b/deploy/models/model_repo/resnet50_res512_all/config.pbtxt similarity index 100% rename from deploy/model_repo/resnet50_res512_all/config.pbtxt rename to deploy/models/model_repo/resnet50_res512_all/config.pbtxt diff --git a/deploy/service.py b/deploy/models/service.py similarity index 100% rename from deploy/service.py rename to deploy/models/service.py diff --git a/deploy/api/__init__.py b/deploy/report/api/__init__.py similarity index 100% rename from deploy/api/__init__.py rename to deploy/report/api/__init__.py diff --git a/deploy/api/main.py b/deploy/report/api/main.py similarity index 83% rename from deploy/api/main.py rename to deploy/report/api/main.py index 0f6c1af25..368a663f9 100644 --- a/deploy/api/main.py +++ b/deploy/report/api/main.py @@ -1,19 +1,17 @@ """A light weight server for evaluation.""" -import copy + import shutil from datetime import datetime -from typing import List, Union import numpy as np import pandas as pd from datasets.arrow_dataset import Dataset -from fastapi import Body, Depends, FastAPI, Form -from fastapi.responses import FileResponse, HTMLResponse +from fastapi import FastAPI, Form +from fastapi.responses import HTMLResponse from fastapi.staticfiles import StaticFiles from fastapi.templating import Jinja2Templates from typing_extensions import Annotated -from cyclops.api.model.eval_request import RequestData from cyclops.evaluate import evaluator from cyclops.evaluate.metrics import create_metric from cyclops.evaluate.metrics.experimental import MetricDict @@ -27,14 +25,18 @@ app.mount("/static", StaticFiles(directory="static"), name="static") templates = Jinja2Templates(directory="templates") + # This endpoint serves the UI @app.get("/", response_class=HTMLResponse) async def get_home(): """Return home page for using evaluate API.""" return templates.TemplateResponse("index.html", {"request": {"method": "POST"}}) + @app.post("/evaluate") -async def evaluate_result(preds_prob: Annotated[str, Form()], target: Annotated[str, Form()]): +async def evaluate_result( + preds_prob: Annotated[str, Form()], target: Annotated[str, Form()] +): """Calculate metric and return result from request body.""" print(type(preds_prob)) print(type(target)) @@ -43,17 +45,20 @@ async def evaluate_result(preds_prob: Annotated[str, Form()], target: Annotated[ target = [float(num.strip()) for num in target.split(",")] # Evaluate and generate report file - df = pd.DataFrame( - data={"target":target, "preds_prob": preds_prob} - ) + df = pd.DataFrame(data={"target": target, "preds_prob": preds_prob}) _eval(df) print("generated report.") - return templates.TemplateResponse("smart_test_report.html", {"request": {"method": "GET"}}) + return templates.TemplateResponse( + "smart_test_report.html", {"request": {"method": "GET"}} + ) + @app.get("/evaluate") async def get_result(): """Calculate metric and return result from request body.""" - return templates.TemplateResponse("smart_test_report.html", {"request": {"method": "GET"}}) + return templates.TemplateResponse( + "smart_test_report.html", {"request": {"method": "GET"}} + ) def _export(report: ModelCardReport): @@ -62,7 +67,6 @@ def _export(report: ModelCardReport): start=datetime.today().date(), periods=10, freq="D" ).values.astype(str) - report._model_card.overview = None report_path = report.export( output_filename="smart_test_report.html", @@ -71,9 +75,7 @@ def _export(report: ModelCardReport): ) shutil.copy(f"{report_path}", "./static") - # metric_save = None for i in range(len(synthetic_timestamps[1:])): - report._model_card.overview = None for metric in report._model_card.quantitative_analysis.performance_metrics: @@ -85,7 +87,7 @@ def _export(report: ModelCardReport): metric.tests[0].passed = bool(metric.value >= 0.6) report_path = report.export( - output_filename="smart_test_report.html", + output_filename="test_report.html", synthetic_timestamp=synthetic_timestamps[i + 1], last_n_evals=3, ) @@ -103,7 +105,7 @@ def _eval(df: pd.DataFrame): "binary_accuracy", "binary_precision", "binary_recall", - "binary_f1_score" + "binary_f1_score", ] metrics = [ create_metric(metric_name, experimental=True) for metric_name in metric_names @@ -144,7 +146,9 @@ def _eval(df: pd.DataFrame): # Extracting the overall classification metric values. overall_performance = { metric_name: metric_value - for metric_name, metric_value in result["model_for_preds_prob"]["overall"].items() + for metric_name, metric_value in result["model_for_preds_prob"][ + "overall" + ].items() if metric_name not in ["BinaryROC", "BinaryPrecisionRecallCurve"] } # Plotting the overall classification metric values. @@ -159,13 +163,13 @@ def _eval(df: pd.DataFrame): ) report.log_from_dict( - data={ - "name": "Heart Failure Prediction Model", - "description": "The model was trained on the Kaggle Heart Failure \ + data={ + "name": "Heart Failure Prediction Model", + "description": "The model was trained on the Kaggle Heart Failure \ Prediction Dataset to predict risk of heart failure.", - }, - section_name="model_details", -) + }, + section_name="model_details", + ) report.log_version( version_str="0.0.1", @@ -183,14 +187,14 @@ def _eval(df: pd.DataFrame): ) report.log_from_dict( - data={ - "users": [ - {"description": "Hospitals"}, - {"description": "Clinicians"}, - ], - }, - section_name="considerations", -) + data={ + "users": [ + {"description": "Hospitals"}, + {"description": "Clinicians"}, + ], + }, + section_name="considerations", + ) report.log_user(description="ML Engineers") report.log_use_case( description="Predicting risk of heart failure.", @@ -198,7 +202,3 @@ def _eval(df: pd.DataFrame): ) _export(report) - - -if __name__ == "__main__": - app.run(debug=True) diff --git a/deploy/report/api/static/.gitkeep b/deploy/report/api/static/.gitkeep new file mode 100644 index 000000000..e69de29bb diff --git a/poetry.lock b/poetry.lock index a162e5f89..a6148b485 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 1.7.1 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand. 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--- a/pyproject.toml +++ b/pyproject.toml @@ -141,10 +141,10 @@ mpi4py = {git = "https://github.com/mpi4py/mpi4py"} imbalanced-learn = "^0.12.0" pyperf = "^2.6.3" -[tool.poetry.group.deploy] +[tool.poetry.group.deploy_models] optional = true -[tool.poetry.group.deploy.dependencies] +[tool.poetry.group.deploy_models.dependencies] aiohttp = "^3.9.2" bentoml = { version = "1.2.5", extras = ["triton"] } torchxrayvision = "^1.2.1" @@ -152,6 +152,12 @@ kaggle = "^1.5.13" onnx = "^1.15.0" skl2onnx = "^1.16.0" +[tool.poetry.group.deploy_report] +optional = true + +[tool.poetry.group.deploy_report.dependencies] +fastapi = "^0.111.0" + [tool.poetry.extras] torch = ["torch"] torchvision = ["torchvision"] From 0c243842640609ee4f7f404c0876707535fc227d Mon Sep 17 00:00:00 2001 From: Amrit Krishnan Date: Tue, 18 Jun 2024 16:20:46 -0400 Subject: [PATCH 03/10] Fix readme --- deploy/models/README.md | 2 +- deploy/report/README.md | 27 +++++++++++++++++++++ deploy/report/api/main.py | 51 +++++++++------------------------------ poetry.lock | 8 +++--- 4 files changed, 43 insertions(+), 45 deletions(-) create mode 100644 deploy/report/README.md diff --git a/deploy/models/README.md b/deploy/models/README.md index 764398464..51738a4cf 100644 --- a/deploy/models/README.md +++ b/deploy/models/README.md @@ -2,7 +2,7 @@ 1. Install the required dependencies with poetry. ```bash -poetry install --with deploy +poetry install --with deploy_models ``` 2. Serialize trained model and move it to the `model_repo` directory. Then create a `config.pbtxt` file for the model. diff --git a/deploy/report/README.md b/deploy/report/README.md new file mode 100644 index 000000000..7c89bb99b --- /dev/null +++ b/deploy/report/README.md @@ -0,0 +1,27 @@ +# Model Report Deployment using FastAPI + +1. Install the required dependencies with poetry. +```bash +poetry install --with deploy_report +``` + +The end points you can access are: + +`/evaluate`: Lists all models that can be queried with the server and their status. +```bash +curl -X 'POST' \ + 'http://cyclops.cluster.local:3000/list_models' \ + -H 'accept: application/json' \ + -H 'Content-Type: text/plain' \ + -H 'access-key: admin' +``` + +`/load_model`: load a given model to memory in preparation for inference. +```bash +curl -X 'POST' \ + 'http://cyclops.cluster.local:3000/load_model' \ + -H 'accept: application/json' \ + -H 'Content-Type: text/plain' \ + -H 'access-key: admin' \ + -d 'densenet121_res224_all' +``` diff --git a/deploy/report/api/main.py b/deploy/report/api/main.py index 368a663f9..f07d0ba12 100644 --- a/deploy/report/api/main.py +++ b/deploy/report/api/main.py @@ -1,9 +1,9 @@ """A light weight server for evaluation.""" +import logging import shutil from datetime import datetime -import numpy as np import pandas as pd from datasets.arrow_dataset import Dataset from fastapi import FastAPI, Form @@ -18,10 +18,14 @@ from cyclops.report.plot.classification import ClassificationPlotter from cyclops.report.report import ModelCardReport from cyclops.report.utils import flatten_results_dict +from cyclops.utils.log import setup_logging -app = FastAPI() +LOGGER = logging.getLogger(__name__) +setup_logging(print_level="WARN", logger=LOGGER) + +app = FastAPI() app.mount("/static", StaticFiles(directory="static"), name="static") templates = Jinja2Templates(directory="templates") @@ -38,18 +42,15 @@ async def evaluate_result( preds_prob: Annotated[str, Form()], target: Annotated[str, Form()] ): """Calculate metric and return result from request body.""" - print(type(preds_prob)) - print(type(target)) - preds_prob = [float(num.strip()) for num in preds_prob.split(",")] target = [float(num.strip()) for num in target.split(",")] # Evaluate and generate report file df = pd.DataFrame(data={"target": target, "preds_prob": preds_prob}) _eval(df) - print("generated report.") + LOGGER.info("Generated report.") return templates.TemplateResponse( - "smart_test_report.html", {"request": {"method": "GET"}} + "test_report.html", {"request": {"method": "GET"}} ) @@ -57,50 +58,25 @@ async def evaluate_result( async def get_result(): """Calculate metric and return result from request body.""" return templates.TemplateResponse( - "smart_test_report.html", {"request": {"method": "GET"}} + "test_report.html", {"request": {"method": "GET"}} ) def _export(report: ModelCardReport): """Prepare and export report file.""" - synthetic_timestamps = pd.date_range( - start=datetime.today().date(), periods=10, freq="D" - ).values.astype(str) - - report._model_card.overview = None report_path = report.export( - output_filename="smart_test_report.html", - synthetic_timestamp=synthetic_timestamps[0], + output_filename="test_report.html", + synthetic_timestamp=str(datetime.today()), last_n_evals=3, ) - shutil.copy(f"{report_path}", "./static") - for i in range(len(synthetic_timestamps[1:])): - report._model_card.overview = None - - for metric in report._model_card.quantitative_analysis.performance_metrics: - metric.value = np.clip( - metric.value + np.random.normal(0, 0.1), - 0, - 1, - ) - metric.tests[0].passed = bool(metric.value >= 0.6) - - report_path = report.export( - output_filename="test_report.html", - synthetic_timestamp=synthetic_timestamps[i + 1], - last_n_evals=3, - ) - shutil.copy(f"{report_path}", "./static") shutil.rmtree("./cyclops_report") def _eval(df: pd.DataFrame): """Evaluate and return report.""" report = ModelCardReport() - data = Dataset.from_pandas(df) - metric_names = [ "binary_accuracy", "binary_precision", @@ -111,7 +87,6 @@ def _eval(df: pd.DataFrame): create_metric(metric_name, experimental=True) for metric_name in metric_names ] metric_collection = MetricDict(metrics) - result = evaluator.evaluate( dataset=data, metrics=metric_collection, # type: ignore[list-item] @@ -161,7 +136,6 @@ def _eval(df: pd.DataFrame): caption="Overall Performance", section_name="quantitative analysis", ) - report.log_from_dict( data={ "name": "Heart Failure Prediction Model", @@ -170,7 +144,6 @@ def _eval(df: pd.DataFrame): }, section_name="model_details", ) - report.log_version( version_str="0.0.1", date=str(datetime.today().date()), @@ -185,7 +158,6 @@ def _eval(df: pd.DataFrame): report.log_reference( link="https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.SGDClassifier.html", # noqa: E501 ) - report.log_from_dict( data={ "users": [ @@ -200,5 +172,4 @@ def _eval(df: pd.DataFrame): description="Predicting risk of heart failure.", kind="primary", ) - _export(report) diff --git a/poetry.lock b/poetry.lock index a6148b485..a338f1c5c 100644 --- a/poetry.lock +++ b/poetry.lock @@ -2754,13 +2754,13 @@ files = [ [[package]] name = "imbalanced-learn" -version = "0.12.0" +version = "0.12.3" description = "Toolbox for imbalanced dataset in machine learning." optional = false python-versions = "*" files = [ - {file = "imbalanced-learn-0.12.0.tar.gz", hash = "sha256:b9ccd9aaa3028699079d43a6d4d9fc9d039f55376733b31f87c7d9b125dcc165"}, - {file = "imbalanced_learn-0.12.0-py3-none-any.whl", hash = "sha256:02ef5bc9ef046f44aa20353a904366a948f7944155e77b6f09b500a70981fd13"}, + {file = "imbalanced-learn-0.12.3.tar.gz", hash = "sha256:5b00796a01419e9102bd425e27c319d58d1f6cf2dfa751e02ed7f4edf67c3c1b"}, + {file = "imbalanced_learn-0.12.3-py3-none-any.whl", hash = "sha256:0e83e8226cb27dd567dff6aef0136bde0f54922ea1bd9d5f38f62701dc51a152"}, ] [package.dependencies] @@ -2771,7 +2771,7 @@ scipy = ">=1.5.0" threadpoolctl = ">=2.0.0" [package.extras] -docs = ["keras (>=2.4.3)", "matplotlib (>=3.1.2)", "memory-profiler (>=0.57.0)", "numpydoc (>=1.5.0)", "pandas (>=1.0.5)", "pydata-sphinx-theme (>=0.13.3)", "seaborn (>=0.9.0)", "sphinx (>=6.0.0)", "sphinx-copybutton (>=0.5.2)", "sphinx-gallery (>=0.13.0)", "sphinxcontrib-bibtex (>=2.4.1)", "tensorflow (>=2.4.3)"] +docs = ["keras (>=2.4.3)", "matplotlib (>=3.1.2)", "memory-profiler (>=0.57.0)", "numpydoc (>=1.5.0)", "pandas (>=1.0.5)", "pydata-sphinx-theme (>=0.13.3)", "seaborn (>=0.9.0)", "sphinx (>=6.0.0)", "sphinx-copybutton (>=0.5.2)", "sphinx-design (>=0.5.0)", "sphinx-gallery (>=0.13.0)", "sphinxcontrib-bibtex (>=2.4.1)", "tensorflow (>=2.4.3)"] examples = ["keras (>=2.4.3)", "matplotlib (>=3.1.2)", "pandas (>=1.0.5)", "seaborn (>=0.9.0)", "tensorflow (>=2.4.3)"] optional = ["keras (>=2.4.3)", "pandas (>=1.0.5)", "tensorflow (>=2.4.3)"] tests = ["black (>=23.3.0)", "flake8 (>=3.8.2)", "keras (>=2.4.3)", "mypy (>=1.3.0)", "pandas (>=1.0.5)", "pytest (>=5.0.1)", "pytest-cov (>=2.9.0)", "tensorflow (>=2.4.3)"] From 8c8a692ec4aba8d5c067e9a53790240f794f05ff Mon Sep 17 00:00:00 2001 From: Amrit Krishnan Date: Fri, 21 Jun 2024 23:36:25 -0400 Subject: [PATCH 04/10] Add working example API endpoints, README --- deploy/report/README.md | 45 +++-- deploy/report/api/__init__.py | 2 +- deploy/report/api/main.py | 190 +++++++++++++++--- .../report/api/{static => templates}/.gitkeep | 0 4 files changed, 193 insertions(+), 44 deletions(-) rename deploy/report/api/{static => templates}/.gitkeep (100%) diff --git a/deploy/report/README.md b/deploy/report/README.md index 7c89bb99b..f1df34c3d 100644 --- a/deploy/report/README.md +++ b/deploy/report/README.md @@ -1,27 +1,44 @@ # Model Report Deployment using FastAPI 1. Install the required dependencies with poetry. + ```bash poetry install --with deploy_report ``` -The end points you can access are: +2. Run the evaluation server (development). + +```bash +cd api/ +fastapi dev main.py --host --port +``` + +If running in production, -`/evaluate`: Lists all models that can be queried with the server and their status. ```bash -curl -X 'POST' \ - 'http://cyclops.cluster.local:3000/list_models' \ - -H 'accept: application/json' \ - -H 'Content-Type: text/plain' \ - -H 'access-key: admin' +cd api/ +fastapi run main.py --host --port ``` -`/load_model`: load a given model to memory in preparation for inference. +The end points you can access are: + +`/evaluate`: You can send model predictions, labels and metadata +for evaluation to this API endpoint using a POST request. For example: ```bash -curl -X 'POST' \ - 'http://cyclops.cluster.local:3000/load_model' \ - -H 'accept: application/json' \ - -H 'Content-Type: text/plain' \ - -H 'access-key: admin' \ - -d 'densenet121_res224_all' +curl -X POST 'http://:/evaluate' \ + -H 'Content-Type: application/json' \ + -d '{ + "preds_prob": [0.2, 0.7, 0.1, 0.9], + "target": [0, 1, 0, 1], + "metadata": { + "Age": [25, 30, 45, 50], + "Sex": ["M", "F", "M", "F"] + } + }' ``` + +If this is the first evaluation for the model, a new model report is created. +Else, the previous model report is used to add the new evaluation. + +The server serves the latest model report, and hence to view it you +can navigate to the server IP address either directly at `http://:` or `http://:/evaluate`. In the latter case, we essentially send a GET request to the ``evaluate`` API endpoint which fetches the latest model report. diff --git a/deploy/report/api/__init__.py b/deploy/report/api/__init__.py index ebbe15f68..b2f82c3ad 100644 --- a/deploy/report/api/__init__.py +++ b/deploy/report/api/__init__.py @@ -1 +1 @@ -"""Web api package.""" +"""CyclOps evaluation server.""" diff --git a/deploy/report/api/main.py b/deploy/report/api/main.py index f07d0ba12..39e1f9f4e 100644 --- a/deploy/report/api/main.py +++ b/deploy/report/api/main.py @@ -1,17 +1,19 @@ """A light weight server for evaluation.""" import logging +import os import shutil from datetime import datetime +from typing import Any, Dict, List import pandas as pd from datasets.arrow_dataset import Dataset -from fastapi import FastAPI, Form +from fastapi import FastAPI, HTTPException from fastapi.responses import HTMLResponse -from fastapi.staticfiles import StaticFiles from fastapi.templating import Jinja2Templates -from typing_extensions import Annotated +from pydantic import BaseModel, Field, validator +from cyclops.data.slicer import SliceSpec from cyclops.evaluate import evaluator from cyclops.evaluate.metrics import create_metric from cyclops.evaluate.metrics.experimental import MetricDict @@ -26,55 +28,165 @@ app = FastAPI() -app.mount("/static", StaticFiles(directory="static"), name="static") -templates = Jinja2Templates(directory="templates") +TEMPLATES_PATH = os.path.join(os.path.dirname(os.path.abspath(__file__)), "templates") +templates = Jinja2Templates(directory=TEMPLATES_PATH) + + +class EvaluationInput(BaseModel): + """Input data for evaluation.""" + + preds_prob: List[float] = Field(..., min_items=1) + target: List[float] = Field(..., min_items=1) + metadata: Dict[str, List[Any]] = Field(default_factory=dict) + + @classmethod + @validator("preds_prob", "target") + def check_list_length( + cls, v: List[float], values: Dict[str, List[Any]], **kwargs: Any + ) -> List[float]: + """Check if preds_prob and target have the same length. + + Parameters + ---------- + v : List[float] + List of values. + values : Dict[str, List[Any]] + Dictionary of values. + + Returns + ------- + List[float] + List of values. + + Raises + ------ + ValueError + If preds_prob and target have different lengths. + + """ + if "preds_prob" in values and len(v) != len(values["preds_prob"]): + raise ValueError("preds_prob and target must have the same length") + return v + + @classmethod + @validator("metadata") + def check_metadata_length( + cls, v: Dict[str, List[Any]], values: Dict[str, List[Any]], **kwargs: Any + ) -> Dict[str, List[Any]]: + """Check if metadata columns have the same length as preds_prob and target. + + Parameters + ---------- + v : Dict[str, List[Any]] + Dictionary of values. + values : Dict[str, List[Any]] + Dictionary of values. + + Returns + ------- + Dict[str, List[Any]] + Dictionary of values. + + Raises + ------ + ValueError + If metadata columns have different lengths than preds_prob and target. + + """ + if "preds_prob" in values: + for column in v.values(): + if len(column) != len(values["preds_prob"]): + raise ValueError( + "All metadata columns must have the same length as preds_prob and target" + ) + return v # This endpoint serves the UI @app.get("/", response_class=HTMLResponse) -async def get_home(): - """Return home page for using evaluate API.""" - return templates.TemplateResponse("index.html", {"request": {"method": "POST"}}) +async def get_home() -> HTMLResponse: + """Return home page for cyclops model report app. + Returns + ------- + HTMLResponse + Home page for cyclops model report app. -@app.post("/evaluate") -async def evaluate_result( - preds_prob: Annotated[str, Form()], target: Annotated[str, Form()] -): - """Calculate metric and return result from request body.""" - preds_prob = [float(num.strip()) for num in preds_prob.split(",")] - target = [float(num.strip()) for num in target.split(",")] - - # Evaluate and generate report file - df = pd.DataFrame(data={"target": target, "preds_prob": preds_prob}) - _eval(df) - LOGGER.info("Generated report.") + """ return templates.TemplateResponse( - "test_report.html", {"request": {"method": "GET"}} + "test_report.html", {"request": {"method": "POST"}} ) +@app.post("/evaluate") +async def evaluate_result(data: EvaluationInput) -> None: + """Calculate metric and return result from request body. + + Parameters + ---------- + data : EvaluationInput + Input data for evaluation. + + Raises + ------ + HTTPException + If there is an internal server error. + + """ + try: + # Create a dictionary with all data + df_dict = { + "target": data.target, + "preds_prob": data.preds_prob, + **data.metadata, + } + + # Create DataFrame + df = pd.DataFrame(df_dict) + + _eval(df) + LOGGER.info("Generated report.") + except Exception as e: + LOGGER.error(f"Error during evaluation: {str(e)}") + raise HTTPException(status_code=500, detail="Internal server error") from e + + @app.get("/evaluate") -async def get_result(): - """Calculate metric and return result from request body.""" +async def get_report() -> HTMLResponse: + """Return latest updated model report. + + Returns + ------- + HTMLResponse + Latest updated model report as HTML response. + + """ return templates.TemplateResponse( "test_report.html", {"request": {"method": "GET"}} ) -def _export(report: ModelCardReport): +def _export(report: ModelCardReport) -> None: """Prepare and export report file.""" + if not os.path.exists("./cyclops_report"): + LOGGER.info("Creating report for the first time!") report_path = report.export( output_filename="test_report.html", synthetic_timestamp=str(datetime.today()), last_n_evals=3, ) - shutil.copy(f"{report_path}", "./static") - shutil.rmtree("./cyclops_report") + shutil.copy(f"{report_path}", TEMPLATES_PATH) + + +def _eval(df: pd.DataFrame) -> None: + """Evaluate and return report. + Parameters + ---------- + df : pd.DataFrame + DataFrame containing target, preds_prob and metadata columns. -def _eval(df: pd.DataFrame): - """Evaluate and return report.""" + """ report = ModelCardReport() data = Dataset.from_pandas(df) metric_names = [ @@ -87,9 +199,29 @@ def _eval(df: pd.DataFrame): create_metric(metric_name, experimental=True) for metric_name in metric_names ] metric_collection = MetricDict(metrics) + spec_list = [ + { + "Age": { + "min_value": 30, + "max_value": 50, + "min_inclusive": True, + "max_inclusive": False, + }, + }, + { + "Age": { + "min_value": 50, + "max_value": 70, + "min_inclusive": True, + "max_inclusive": False, + }, + }, + ] + slice_spec = SliceSpec(spec_list) result = evaluator.evaluate( dataset=data, - metrics=metric_collection, # type: ignore[list-item] + metrics=metric_collection, + slice_spec=slice_spec, target_columns="target", prediction_columns="preds_prob", ) diff --git a/deploy/report/api/static/.gitkeep b/deploy/report/api/templates/.gitkeep similarity index 100% rename from deploy/report/api/static/.gitkeep rename to deploy/report/api/templates/.gitkeep From cdb83ffb8554cff36d47cbc8d544088967925cd4 Mon Sep 17 00:00:00 2001 From: Amrit Krishnan Date: Sat, 22 Jun 2024 11:23:48 -0400 Subject: [PATCH 05/10] Migrate to pydantic v2 --- cyclops/evaluate/__init__.py | 3 + cyclops/evaluate/metrics/__init__.py | 53 +++++ .../evaluate/metrics/experimental/__init__.py | 61 ++++++ cyclops/report/model_card/base.py | 2 + cyclops/report/model_card/fields.py | 13 +- cyclops/report/model_card/model_card.py | 2 + deploy/report/api/main.py | 77 +++---- poetry.lock | 192 ++++++++++++------ pyproject.toml | 6 +- 9 files changed, 303 insertions(+), 106 deletions(-) diff --git a/cyclops/evaluate/__init__.py b/cyclops/evaluate/__init__.py index 9d0814cf5..f35ce2d9a 100644 --- a/cyclops/evaluate/__init__.py +++ b/cyclops/evaluate/__init__.py @@ -2,3 +2,6 @@ from cyclops.evaluate.evaluator import evaluate from cyclops.evaluate.fairness.evaluator import evaluate_fairness + + +__all__ = ["evaluate", "evaluate_fairness"] diff --git a/cyclops/evaluate/metrics/__init__.py b/cyclops/evaluate/metrics/__init__.py index 87ec863df..ec176bb5c 100644 --- a/cyclops/evaluate/metrics/__init__.py +++ b/cyclops/evaluate/metrics/__init__.py @@ -67,3 +67,56 @@ MultilabelStatScores, StatScores, ) + + +__all__ = [ + "create_metric", + "MetricCollection", + "Accuracy", + "AUROC", + "BinaryAccuracy", + "BinaryAUROC", + "BinaryAveragePrecision", + "BinaryPrecisionRecallCurve", + "MulticlassPrecisionRecallCurve", + "MultilabelPrecisionRecallCurve", + "PrecisionRecallCurve", + "BinaryF1Score", + "BinaryFbetaScore", + "BinaryPrecision", + "BinaryRecall", + "BinaryROCCurve", + "BinarySensitivity", + "BinarySpecificity", + "F1Score", + "FbetaScore", + "MulticlassAccuracy", + "MulticlassAUROC", + "MulticlassAveragePrecision", + "MulticlassF1Score", + "MulticlassFbetaScore", + "MulticlassPrecision", + "MulticlassRecall", + "MulticlassROCCurve", + "MulticlassSensitivity", + "MulticlassSpecificity", + "MultilabelAccuracy", + "MultilabelAUROC", + "MultilabelAveragePrecision", + "MultilabelF1Score", + "MultilabelFbetaScore", + "MultilabelPrecision", + "MultilabelRecall", + "MultilabelROCCurve", + "MultilabelSensitivity", + "MultilabelSpecificity", + "Precision", + "Recall", + "ROCCurve", + "Sensitivity", + "Specificity", + "StatScores", + "BinaryStatScores", + "MulticlassStatScores", + "MultilabelStatScores", +] diff --git a/cyclops/evaluate/metrics/experimental/__init__.py b/cyclops/evaluate/metrics/experimental/__init__.py index 98d6891a6..f80f1c431 100644 --- a/cyclops/evaluate/metrics/experimental/__init__.py +++ b/cyclops/evaluate/metrics/experimental/__init__.py @@ -83,3 +83,64 @@ from cyclops.evaluate.metrics.experimental.wmape import ( WeightedMeanAbsolutePercentageError, ) + + +__all__ = [ + "BinaryAccuracy", + "MulticlassAccuracy", + "MultilabelAccuracy", + "BinaryAUROC", + "MulticlassAUROC", + "MultilabelAUROC", + "BinaryAveragePrecision", + "MulticlassAveragePrecision", + "MultilabelAveragePrecision", + "BinaryConfusionMatrix", + "MulticlassConfusionMatrix", + "MultilabelConfusionMatrix", + "BinaryF1Score", + "BinaryFBetaScore", + "MulticlassF1Score", + "MulticlassFBetaScore", + "MultilabelF1Score", + "MultilabelFBetaScore", + "MeanAbsoluteError", + "MeanAbsolutePercentageError", + "MeanSquaredError", + "BinaryMCC", + "MulticlassMCC", + "MultilabelMCC", + "MetricDict", + "BinaryNPV", + "MulticlassNPV", + "MultilabelNPV", + "BinaryPPV", + "BinaryPrecision", + "BinaryRecall", + "BinarySensitivity", + "BinaryTPR", + "MulticlassPPV", + "MulticlassPrecision", + "MulticlassRecall", + "MulticlassSensitivity", + "MulticlassTPR", + "MultilabelPPV", + "MultilabelPrecision", + "MultilabelRecall", + "MultilabelSensitivity", + "MultilabelTPR", + "BinaryPrecisionRecallCurve", + "MulticlassPrecisionRecallCurve", + "MultilabelPrecisionRecallCurve", + "BinaryROC", + "MulticlassROC", + "MultilabelROC", + "SymmetricMeanAbsolutePercentageError", + "BinarySpecificity", + "BinaryTNR", + "MulticlassSpecificity", + "MulticlassTNR", + "MultilabelSpecificity", + "MultilabelTNR", + "WeightedMeanAbsolutePercentageError", +] diff --git a/cyclops/report/model_card/base.py b/cyclops/report/model_card/base.py index 235f37fba..b6178d52e 100644 --- a/cyclops/report/model_card/base.py +++ b/cyclops/report/model_card/base.py @@ -60,6 +60,8 @@ class BaseModelCardConfig(BaseConfig): class BaseModelCardField(BaseModel): """Base class for model card fields.""" + # TODO[pydantic]: The `Config` class inherits from another class, please create the `model_config` manually. + # Check https://docs.pydantic.dev/dev-v2/migration/#changes-to-config for more information. class Config(BaseModelCardConfig): """Global config for model card fields. diff --git a/cyclops/report/model_card/fields.py b/cyclops/report/model_card/fields.py index 12dd29497..892126ed3 100644 --- a/cyclops/report/model_card/fields.py +++ b/cyclops/report/model_card/fields.py @@ -17,8 +17,8 @@ StrictFloat, StrictInt, StrictStr, - root_validator, - validator, + field_validator, + model_validator, ) from cyclops.report.model_card.base import BaseModelCardField @@ -90,7 +90,8 @@ class License( ) text_url: Optional[AnyUrl] = Field(None, description="A URL to the license text.") - @root_validator(skip_on_failure=True) + @model_validator(skip_on_failure=True) + @classmethod def validate_spdx_identifier( cls: "License", # noqa: N805 values: Dict[str, StrictStr], @@ -154,7 +155,8 @@ class Citation( description="The citation content in BibTeX format.", ) - @validator("content") + @field_validator("content") + @classmethod def parse_content( cls: "Citation", # noqa: N805 value: StrictStr, @@ -414,7 +416,8 @@ class UseCase( ), ) - @validator("kind") + @field_validator("kind") + @classmethod def kind_must_be_valid( cls: "UseCase", # noqa: N805 value: str, diff --git a/cyclops/report/model_card/model_card.py b/cyclops/report/model_card/model_card.py index dc75640ef..99db0c119 100644 --- a/cyclops/report/model_card/model_card.py +++ b/cyclops/report/model_card/model_card.py @@ -26,6 +26,8 @@ class ModelCard(BaseModel): """ + # TODO[pydantic]: The `Config` class inherits from another class, please create the `model_config` manually. + # Check https://docs.pydantic.dev/dev-v2/migration/#changes-to-config for more information. class Config(BaseModelCardConfig): """Model Card configuration.""" diff --git a/deploy/report/api/main.py b/deploy/report/api/main.py index 39e1f9f4e..5dbea0d62 100644 --- a/deploy/report/api/main.py +++ b/deploy/report/api/main.py @@ -11,7 +11,7 @@ from fastapi import FastAPI, HTTPException from fastapi.responses import HTMLResponse from fastapi.templating import Jinja2Templates -from pydantic import BaseModel, Field, validator +from pydantic import BaseModel, Field, ValidationInfo, field_validator from cyclops.data.slicer import SliceSpec from cyclops.evaluate import evaluator @@ -35,28 +35,26 @@ class EvaluationInput(BaseModel): """Input data for evaluation.""" - preds_prob: List[float] = Field(..., min_items=1) - target: List[float] = Field(..., min_items=1) + preds_prob: List[float] = Field(..., min_length=1) + target: List[float] = Field(..., min_length=1) metadata: Dict[str, List[Any]] = Field(default_factory=dict) + @field_validator("target") @classmethod - @validator("preds_prob", "target") - def check_list_length( - cls, v: List[float], values: Dict[str, List[Any]], **kwargs: Any - ) -> List[float]: + def check_list_length(cls, v: List[float], info: ValidationInfo) -> List[float]: """Check if preds_prob and target have the same length. Parameters ---------- v : List[float] - List of values. - values : Dict[str, List[Any]] - Dictionary of values. + List of target values. + info : ValidationInfo + Validation information. Returns ------- List[float] - List of values. + List of target values. Raises ------ @@ -64,28 +62,30 @@ def check_list_length( If preds_prob and target have different lengths. """ - if "preds_prob" in values and len(v) != len(values["preds_prob"]): + preds_prob = info.data.get("preds_prob", []) + if len(v) != len(preds_prob): raise ValueError("preds_prob and target must have the same length") return v + @field_validator("metadata") @classmethod - @validator("metadata") def check_metadata_length( - cls, v: Dict[str, List[Any]], values: Dict[str, List[Any]], **kwargs: Any + cls, v: Dict[str, List[Any]], info: ValidationInfo ) -> Dict[str, List[Any]]: """Check if metadata columns have the same length as preds_prob and target. Parameters ---------- v : Dict[str, List[Any]] - Dictionary of values. - values : Dict[str, List[Any]] - Dictionary of values. + Dictionary of metadata columns. + + info : ValidationInfo + Validation information. Returns ------- Dict[str, List[Any]] - Dictionary of values. + Dictionary of metadata columns. Raises ------ @@ -93,12 +93,12 @@ def check_metadata_length( If metadata columns have different lengths than preds_prob and target. """ - if "preds_prob" in values: - for column in v.values(): - if len(column) != len(values["preds_prob"]): - raise ValueError( - "All metadata columns must have the same length as preds_prob and target" - ) + preds_prob = info.data.get("preds_prob", []) + for column in v.values(): + if len(column) != len(preds_prob): + raise ValueError( + "All metadata columns must have the same length as preds_prob and target" + ) return v @@ -134,16 +134,14 @@ async def evaluate_result(data: EvaluationInput) -> None: """ try: - # Create a dictionary with all data - df_dict = { - "target": data.target, - "preds_prob": data.preds_prob, - **data.metadata, - } - - # Create DataFrame - df = pd.DataFrame(df_dict) - + # Create dataframe with target, preds_prob and metadata columns + df = pd.DataFrame( + { + "target": data.target, + "preds_prob": data.preds_prob, + **data.metadata, + } + ) _eval(df) LOGGER.info("Generated report.") except Exception as e: @@ -167,7 +165,14 @@ async def get_report() -> HTMLResponse: def _export(report: ModelCardReport) -> None: - """Prepare and export report file.""" + """Prepare and export report file. + + Parameters + ---------- + report : ModelCardReport + ModelCardReport object. + + """ if not os.path.exists("./cyclops_report"): LOGGER.info("Creating report for the first time!") report_path = report.export( @@ -198,7 +203,7 @@ def _eval(df: pd.DataFrame) -> None: metrics = [ create_metric(metric_name, experimental=True) for metric_name in metric_names ] - metric_collection = MetricDict(metrics) + metric_collection = MetricDict(metrics) # type: ignore spec_list = [ { "Age": { diff --git a/poetry.lock b/poetry.lock index 87847437c..efebd9b6e 100644 --- a/poetry.lock +++ b/poetry.lock @@ -149,13 +149,13 @@ files = [ [[package]] name = "alibi" -version = "0.9.5" +version = "0.9.6" description = "Algorithms for monitoring and explaining machine learning models" optional = false python-versions = ">=3.8" files = [ - {file = "alibi-0.9.5-py3-none-any.whl", hash = "sha256:88ac97ff00e06d7686f82480d6cdba86109245f0dd2bb7b311b1a95f8162fcd1"}, - {file = "alibi-0.9.5.tar.gz", hash = "sha256:7797e480285338eb24eea606d620b9b74ccddfd32c366b4c73076cfd57e46096"}, + {file = "alibi-0.9.6-py3-none-any.whl", hash = "sha256:206416e297f927f6028f3ffcc286b16227a11b26ce99581f533ecf9efdc86a14"}, + {file = "alibi-0.9.6.tar.gz", hash = "sha256:7a5075baf62b693c4489752281c58814efca1dcd08cfe353242da9a9da9ed6c1"}, ] [package.dependencies] @@ -163,11 +163,10 @@ attrs = ">=19.2.0,<24.0.0" blis = "<0.8.0" dill = ">=0.3.0,<0.4.0" matplotlib = ">=3.0.0,<4.0.0" -numba = {version = ">=0.50.0,<0.54.0 || >0.54.0,<0.59.0", optional = true, markers = "extra == \"shap\""} +numba = {version = ">=0.50.0,<0.54.0 || >0.54.0,<0.60.0", optional = true, markers = "extra == \"shap\""} numpy = ">=1.16.2,<2.0.0" pandas = ">=1.0.0,<3.0.0" Pillow = ">=5.4.1,<11.0" -pydantic = "<2.0.0" requests = ">=2.21.0,<3.0.0" scikit-image = ">=0.17.2,<0.23" scikit-learn = ">=1.0.0,<2.0.0" @@ -179,33 +178,33 @@ transformers = ">=4.7.0,<5.0.0" typing-extensions = ">=3.7.4.3" [package.extras] -all = ["numba (>=0.50.0,!=0.54.0,<0.59.0)", "ray (>=0.8.7,<3.0.0)", "shap (>=0.40.0,<0.44.0)", "tensorflow (>=2.0.0,!=2.6.0,!=2.6.1,<2.15.0)", "torch (>=1.9.0,<3.0.0)"] +all = ["numba (>=0.50.0,!=0.54.0,<0.60.0)", "ray (>=0.8.7,<3.0.0)", "shap (>=0.40.0,<0.44.0)", "tensorflow (>=2.0.0,!=2.6.0,!=2.6.1,<2.15.0)", "torch (>=1.9.0,<3.0.0)"] ray = ["ray (>=0.8.7,<3.0.0)"] -shap = ["numba (>=0.50.0,!=0.54.0,<0.59.0)", "shap (>=0.40.0,<0.44.0)"] +shap = ["numba (>=0.50.0,!=0.54.0,<0.60.0)", "shap (>=0.40.0,<0.44.0)"] tensorflow = ["tensorflow (>=2.0.0,!=2.6.0,!=2.6.1,<2.15.0)"] torch = ["torch (>=1.9.0,<3.0.0)"] [[package]] name = "alibi-detect" -version = "0.11.5" +version = "0.12.0" description = "Algorithms for outlier detection, concept drift and metrics." optional = false python-versions = ">=3.8" files = [ - {file = "alibi-detect-0.11.5.tar.gz", hash = "sha256:b6018021d82d36c01856fc4e7b3b2f92aa9aa46e4c4621aaf2e649c2e932129d"}, - {file = "alibi_detect-0.11.5-py3-none-any.whl", hash = "sha256:fd65eb0451d3ac4cc676181c65ec4aafffe855cce16bc218dd00216ae317e58a"}, + {file = "alibi-detect-0.12.0.tar.gz", hash = "sha256:d17615e39370764d27864c97bbcd72865ce32371c85137e0ecf858c5e841ed4c"}, + {file = "alibi_detect-0.12.0-py3-none-any.whl", hash = "sha256:c09900416c263029d1a6cecabe7c6d46adda736343581867ec085cc7e80fbc1b"}, ] [package.dependencies] catalogue = ">=2.0.0,<3.0.0" dill = ">=0.3.0,<0.4.0" matplotlib = ">=3.0.0,<4.0.0" -numba = ">=0.50.0,<0.54.0 || >0.54.0,<0.59.0" +numba = ">=0.50.0,<0.54.0 || >0.54.0,<0.60.0" numpy = ">=1.16.2,<2.0.0" opencv-python = ">=3.2.0,<5.0.0" pandas = ">=1.0.0,<3.0.0" Pillow = ">=5.4.1,<11.0.0" -pydantic = ">=1.8.0,<2.0.0" +pydantic = ">=1.8.0,<3.0.0" requests = ">=2.21.0,<3.0.0" scikit-image = ">=0.19,<0.23" scikit-learn = ">=0.20.2,<2.0.0" @@ -217,12 +216,23 @@ transformers = ">=4.0.0,<5.0.0" typing-extensions 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= { version = "^1.2.0", optional = true } xgboost = { version = "^1.5.2", optional = true } alibi = { version = "^0.9.4", optional = true, extras = ["shap"] } -alibi-detect = { version = "^0.11.0", optional = true, extras = ["torch"] } +alibi-detect = { version = "^0.12.0", optional = true, extras = ["torch"] } llvmlite = { version = "^0.40.0", optional = true } [tool.poetry.group.xgboost] @@ -87,7 +87,7 @@ optional = true [tool.poetry.group.alibi-detect.dependencies] llvmlite = "^0.40.0" torch = "^1.11.0" -alibi-detect = { version = "^0.11.0", extras = ["torch"] } +alibi-detect = { version = "^0.12.0", extras = ["torch"] } [tool.poetry.group.test] optional = true From 717c7ff6c17b7bbb9e530c62f5e5faaddf6579d2 Mon Sep 17 00:00:00 2001 From: Amrit Krishnan Date: Wed, 26 Jun 2024 18:53:12 -0400 Subject: [PATCH 06/10] Final fixes, revert to pydanticv1 --- cyclops/report/model_card/base.py | 2 - cyclops/report/model_card/fields.py | 13 +- cyclops/report/model_card/model_card.py | 2 - deploy/report/README.md | 11 +- deploy/report/api/main.py | 75 +++++----- poetry.lock | 178 ++++++++---------------- pyproject.toml | 3 +- 7 files changed, 102 insertions(+), 182 deletions(-) diff --git a/cyclops/report/model_card/base.py b/cyclops/report/model_card/base.py index b6178d52e..235f37fba 100644 --- a/cyclops/report/model_card/base.py +++ b/cyclops/report/model_card/base.py @@ -60,8 +60,6 @@ class BaseModelCardConfig(BaseConfig): class BaseModelCardField(BaseModel): """Base class for model card fields.""" - # TODO[pydantic]: The `Config` class inherits from another class, please create the `model_config` manually. - # Check https://docs.pydantic.dev/dev-v2/migration/#changes-to-config for more information. class Config(BaseModelCardConfig): """Global config for model card fields. diff --git a/cyclops/report/model_card/fields.py b/cyclops/report/model_card/fields.py index 892126ed3..12dd29497 100644 --- a/cyclops/report/model_card/fields.py +++ b/cyclops/report/model_card/fields.py @@ -17,8 +17,8 @@ StrictFloat, StrictInt, StrictStr, - field_validator, - model_validator, + root_validator, + validator, ) from cyclops.report.model_card.base import BaseModelCardField @@ -90,8 +90,7 @@ class License( ) text_url: Optional[AnyUrl] = Field(None, description="A URL to the license text.") - @model_validator(skip_on_failure=True) - @classmethod + @root_validator(skip_on_failure=True) def validate_spdx_identifier( cls: "License", # noqa: N805 values: Dict[str, StrictStr], @@ -155,8 +154,7 @@ class Citation( description="The citation content in BibTeX format.", ) - @field_validator("content") - @classmethod + @validator("content") def parse_content( cls: "Citation", # noqa: N805 value: StrictStr, @@ -416,8 +414,7 @@ class UseCase( ), ) - @field_validator("kind") - @classmethod + @validator("kind") def kind_must_be_valid( cls: "UseCase", # noqa: N805 value: str, diff --git a/cyclops/report/model_card/model_card.py b/cyclops/report/model_card/model_card.py index 99db0c119..dc75640ef 100644 --- a/cyclops/report/model_card/model_card.py +++ b/cyclops/report/model_card/model_card.py @@ -26,8 +26,6 @@ class ModelCard(BaseModel): """ - # TODO[pydantic]: The `Config` class inherits from another class, please create the `model_config` manually. - # Check https://docs.pydantic.dev/dev-v2/migration/#changes-to-config for more information. class Config(BaseModelCardConfig): """Model Card configuration.""" diff --git a/deploy/report/README.md b/deploy/report/README.md index f1df34c3d..1ea891069 100644 --- a/deploy/report/README.md +++ b/deploy/report/README.md @@ -6,18 +6,11 @@ poetry install --with deploy_report ``` -2. Run the evaluation server (development). +2. Run the evaluation server. ```bash cd api/ -fastapi dev main.py --host --port -``` - -If running in production, - -```bash -cd api/ -fastapi run main.py --host --port +uvicorn api.main:app --reload --host --port ``` The end points you can access are: diff --git a/deploy/report/api/main.py b/deploy/report/api/main.py index 5dbea0d62..67a6158fb 100644 --- a/deploy/report/api/main.py +++ b/deploy/report/api/main.py @@ -11,7 +11,7 @@ from fastapi import FastAPI, HTTPException from fastapi.responses import HTMLResponse from fastapi.templating import Jinja2Templates -from pydantic import BaseModel, Field, ValidationInfo, field_validator +from pydantic import BaseModel, Field, validator from cyclops.data.slicer import SliceSpec from cyclops.evaluate import evaluator @@ -35,26 +35,28 @@ class EvaluationInput(BaseModel): """Input data for evaluation.""" - preds_prob: List[float] = Field(..., min_length=1) - target: List[float] = Field(..., min_length=1) + preds_prob: List[float] = Field(..., min_items=1) + target: List[float] = Field(..., min_items=1) metadata: Dict[str, List[Any]] = Field(default_factory=dict) - @field_validator("target") @classmethod - def check_list_length(cls, v: List[float], info: ValidationInfo) -> List[float]: + @validator("preds_prob", "target") + def check_list_length( + cls, v: List[float], values: Dict[str, List[Any]], **kwargs: Any + ) -> List[float]: """Check if preds_prob and target have the same length. Parameters ---------- v : List[float] - List of target values. - info : ValidationInfo - Validation information. + List of values. + values : Dict[str, List[Any]] + Dictionary of values. Returns ------- List[float] - List of target values. + List of values. Raises ------ @@ -62,30 +64,28 @@ def check_list_length(cls, v: List[float], info: ValidationInfo) -> List[float]: If preds_prob and target have different lengths. """ - preds_prob = info.data.get("preds_prob", []) - if len(v) != len(preds_prob): + if "preds_prob" in values and len(v) != len(values["preds_prob"]): raise ValueError("preds_prob and target must have the same length") return v - @field_validator("metadata") @classmethod + @validator("metadata") def check_metadata_length( - cls, v: Dict[str, List[Any]], info: ValidationInfo + cls, v: Dict[str, List[Any]], values: Dict[str, List[Any]], **kwargs: Any ) -> Dict[str, List[Any]]: """Check if metadata columns have the same length as preds_prob and target. Parameters ---------- v : Dict[str, List[Any]] - Dictionary of metadata columns. - - info : ValidationInfo - Validation information. + Dictionary of values. + values : Dict[str, List[Any]] + Dictionary of values. Returns ------- Dict[str, List[Any]] - Dictionary of metadata columns. + Dictionary of values. Raises ------ @@ -93,12 +93,12 @@ def check_metadata_length( If metadata columns have different lengths than preds_prob and target. """ - preds_prob = info.data.get("preds_prob", []) - for column in v.values(): - if len(column) != len(preds_prob): - raise ValueError( - "All metadata columns must have the same length as preds_prob and target" - ) + if "preds_prob" in values: + for column in v.values(): + if len(column) != len(values["preds_prob"]): + raise ValueError( + "All metadata columns must have the same length as preds_prob and target" + ) return v @@ -134,14 +134,16 @@ async def evaluate_result(data: EvaluationInput) -> None: """ try: - # Create dataframe with target, preds_prob and metadata columns - df = pd.DataFrame( - { - "target": data.target, - "preds_prob": data.preds_prob, - **data.metadata, - } - ) + # Create a dictionary with all data + df_dict = { + "target": data.target, + "preds_prob": data.preds_prob, + **data.metadata, + } + + # Create DataFrame + df = pd.DataFrame(df_dict) + _eval(df) LOGGER.info("Generated report.") except Exception as e: @@ -165,14 +167,7 @@ async def get_report() -> 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[tool.poetry.extras] torch = ["torch"] From d2117485849defb7fbe8974cb1ddd56125f09434 Mon Sep 17 00:00:00 2001 From: Amrit Krishnan Date: Wed, 26 Jun 2024 19:10:49 -0400 Subject: [PATCH 07/10] Fix mypy issue --- deploy/report/api/main.py | 108 +++++--------------------------------- 1 file changed, 13 insertions(+), 95 deletions(-) diff --git a/deploy/report/api/main.py b/deploy/report/api/main.py index 67a6158fb..92ac36cb2 100644 --- a/deploy/report/api/main.py +++ b/deploy/report/api/main.py @@ -8,7 +8,7 @@ import pandas as pd from datasets.arrow_dataset import Dataset -from fastapi import FastAPI, HTTPException +from fastapi import FastAPI, HTTPException, Request from fastapi.responses import HTMLResponse from fastapi.templating import Jinja2Templates from pydantic import BaseModel, Field, validator @@ -26,7 +26,6 @@ LOGGER = logging.getLogger(__name__) setup_logging(print_level="WARN", logger=LOGGER) - app = FastAPI() TEMPLATES_PATH = os.path.join(os.path.dirname(os.path.abspath(__file__)), "templates") templates = Jinja2Templates(directory=TEMPLATES_PATH) @@ -44,26 +43,7 @@ class EvaluationInput(BaseModel): def check_list_length( cls, v: List[float], values: Dict[str, List[Any]], **kwargs: Any ) -> List[float]: - """Check if preds_prob and target have the same length. - - Parameters - ---------- - v : List[float] - List of values. - values : Dict[str, List[Any]] - Dictionary of values. - - Returns - ------- - List[float] - List of values. - - Raises - ------ - ValueError - If preds_prob and target have different lengths. - - """ + """Check if preds_prob and target have the same length.""" if "preds_prob" in values and len(v) != len(values["preds_prob"]): raise ValueError("preds_prob and target must have the same length") return v @@ -73,26 +53,7 @@ def check_list_length( def check_metadata_length( cls, v: Dict[str, List[Any]], values: Dict[str, List[Any]], **kwargs: Any ) -> Dict[str, List[Any]]: - """Check if metadata columns have the same length as preds_prob and target. - - Parameters - ---------- - v : Dict[str, List[Any]] - Dictionary of values. - values : Dict[str, List[Any]] - Dictionary of values. - - Returns - ------- - Dict[str, List[Any]] - Dictionary of values. - - Raises - ------ - ValueError - If metadata columns have different lengths than preds_prob and target. - - """ + """Check if metadata columns have the same length as preds_prob and target.""" if "preds_prob" in values: for column in v.values(): if len(column) != len(values["preds_prob"]): @@ -104,35 +65,14 @@ def check_metadata_length( # This endpoint serves the UI @app.get("/", response_class=HTMLResponse) -async def get_home() -> HTMLResponse: - """Return home page for cyclops model report app. - - Returns - ------- - HTMLResponse - Home page for cyclops model report app. - - """ - return templates.TemplateResponse( - "test_report.html", {"request": {"method": "POST"}} - ) +async def get_home(request: Request) -> HTMLResponse: + """Return home page for cyclops model report app.""" + return templates.TemplateResponse("test_report.html", {"request": request}) @app.post("/evaluate") async def evaluate_result(data: EvaluationInput) -> None: - """Calculate metric and return result from request body. - - Parameters - ---------- - data : EvaluationInput - Input data for evaluation. - - Raises - ------ - HTTPException - If there is an internal server error. - - """ + """Calculate metric and return result from request body.""" try: # Create a dictionary with all data df_dict = { @@ -140,10 +80,8 @@ async def evaluate_result(data: EvaluationInput) -> None: "preds_prob": data.preds_prob, **data.metadata, } - # Create DataFrame df = pd.DataFrame(df_dict) - _eval(df) LOGGER.info("Generated report.") except Exception as e: @@ -151,19 +89,10 @@ async def evaluate_result(data: EvaluationInput) -> None: raise HTTPException(status_code=500, detail="Internal server error") from e -@app.get("/evaluate") -async def get_report() -> HTMLResponse: - """Return latest updated model report. - - Returns - ------- - HTMLResponse - Latest updated model report as HTML response. - - """ - return templates.TemplateResponse( - "test_report.html", {"request": {"method": "GET"}} - ) +@app.get("/evaluate", response_class=HTMLResponse) +async def get_report(request: Request) -> HTMLResponse: + """Return latest updated model report.""" + return templates.TemplateResponse("test_report.html", {"request": request}) def _export(report: ModelCardReport) -> None: @@ -179,14 +108,7 @@ def _export(report: ModelCardReport) -> None: def _eval(df: pd.DataFrame) -> None: - """Evaluate and return report. - - Parameters - ---------- - df : pd.DataFrame - DataFrame containing target, preds_prob and metadata columns. - - """ + """Evaluate and return report.""" report = ModelCardReport() data = Dataset.from_pandas(df) metric_names = [ @@ -226,7 +148,6 @@ def _eval(df: pd.DataFrame) -> None: prediction_columns="preds_prob", ) results_flat = flatten_results_dict(results=result) - # Log into report for name, metric in results_flat["model_for_preds_prob"].items(): split, name = name.split("/") # noqa: PLW2901 @@ -245,11 +166,9 @@ def _eval(df: pd.DataFrame) -> None: pass_fail_thresholds=0.6, pass_fail_threshold_fns=lambda x, threshold: bool(x >= threshold), ) - # Log plot in report plotter = ClassificationPlotter(task_type="binary", class_names=["0", "1"]) plotter.set_template("plotly_white") - # Extracting the overall classification metric values. overall_performance = { metric_name: metric_value @@ -271,8 +190,7 @@ def _eval(df: pd.DataFrame) -> None: report.log_from_dict( data={ "name": "Heart Failure Prediction Model", - "description": "The model was trained on the Kaggle Heart Failure \ - Prediction Dataset to predict risk of heart failure.", + "description": "The model was trained on the Kaggle Heart Failure Prediction Dataset to predict risk of heart failure.", }, section_name="model_details", ) From fbf79cc6b7c0141ebcc4d12ebb9125d34993084e Mon Sep 17 00:00:00 2001 From: Amrit Krishnan Date: Wed, 26 Jun 2024 19:14:40 -0400 Subject: [PATCH 08/10] Add docstrings --- deploy/report/api/main.py | 102 +++++++++++++++++++++++++++++++++++--- 1 file changed, 95 insertions(+), 7 deletions(-) diff --git a/deploy/report/api/main.py b/deploy/report/api/main.py index 92ac36cb2..17796999e 100644 --- a/deploy/report/api/main.py +++ b/deploy/report/api/main.py @@ -43,7 +43,26 @@ class EvaluationInput(BaseModel): def check_list_length( cls, v: List[float], values: Dict[str, List[Any]], **kwargs: Any ) -> List[float]: - """Check if preds_prob and target have the same length.""" + """Check if preds_prob and target have the same length. + + Parameters + ---------- + v : List[float] + List of values. + values : Dict[str, List[Any]] + Dictionary of values. + + Returns + ------- + List[float] + List of values. + + Raises + ------ + ValueError + If preds_prob and target have different lengths. + + """ if "preds_prob" in values and len(v) != len(values["preds_prob"]): raise ValueError("preds_prob and target must have the same length") return v @@ -53,7 +72,26 @@ def check_list_length( def check_metadata_length( cls, v: Dict[str, List[Any]], values: Dict[str, List[Any]], **kwargs: Any ) -> Dict[str, List[Any]]: - """Check if metadata columns have the same length as preds_prob and target.""" + """Check if metadata columns have the same length as preds_prob and target. + + Parameters + ---------- + v : Dict[str, List[Any]] + Dictionary of values. + values : Dict[str, List[Any]] + Dictionary of values. + + Returns + ------- + Dict[str, List[Any]] + Dictionary of values. + + Raises + ------ + ValueError + If metadata columns have different lengths than preds_prob and target. + + """ if "preds_prob" in values: for column in v.values(): if len(column) != len(values["preds_prob"]): @@ -66,13 +104,37 @@ def check_metadata_length( # This endpoint serves the UI @app.get("/", response_class=HTMLResponse) async def get_home(request: Request) -> HTMLResponse: - """Return home page for cyclops model report app.""" + """Return home page for cyclops model report app. + + Parameters + ---------- + request : Request + Request object. + + Returns + ------- + HTMLResponse + HTML response for home page + + """ return templates.TemplateResponse("test_report.html", {"request": request}) @app.post("/evaluate") async def evaluate_result(data: EvaluationInput) -> None: - """Calculate metric and return result from request body.""" + """Calculate metric and return result from request body. + + Parameters + ---------- + data : EvaluationInput + Evaluation input data. + + Raises + ------ + HTTPException + If there is an internal server error. + + """ try: # Create a dictionary with all data df_dict = { @@ -91,12 +153,31 @@ async def evaluate_result(data: EvaluationInput) -> None: @app.get("/evaluate", response_class=HTMLResponse) async def get_report(request: Request) -> HTMLResponse: - """Return latest updated model report.""" + """Return latest updated model report. + + Parameters + ---------- + request : Request + Request object. + + Returns + ------- + HTMLResponse + HTML response for model report + + """ return templates.TemplateResponse("test_report.html", {"request": request}) def _export(report: ModelCardReport) -> None: - """Prepare and export report file.""" + """Prepare and export report file. + + Parameters + ---------- + report : ModelCardReport + ModelCardReport object + + """ if not os.path.exists("./cyclops_report"): LOGGER.info("Creating report for the first time!") report_path = report.export( @@ -108,7 +189,14 @@ def _export(report: ModelCardReport) -> None: def _eval(df: pd.DataFrame) -> None: - """Evaluate and return report.""" + """Evaluate and return report. + + Parameters + ---------- + df : pd.DataFrame + DataFrame with target, preds_prob and metadata columns + + """ report = ModelCardReport() data = Dataset.from_pandas(df) metric_names = [ From e566505fca38169c5895986e1e3e55adb8d2366a Mon Sep 17 00:00:00 2001 From: Amrit Krishnan Date: Thu, 27 Jun 2024 08:42:07 -0400 Subject: [PATCH 09/10] Add type ignore --- deploy/report/api/main.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/deploy/report/api/main.py b/deploy/report/api/main.py index 17796999e..8e6b4d00c 100644 --- a/deploy/report/api/main.py +++ b/deploy/report/api/main.py @@ -102,7 +102,7 @@ def check_metadata_length( # This endpoint serves the UI -@app.get("/", response_class=HTMLResponse) +@app.get("/", response_class=HTMLResponse) # type: ignore[misc] async def get_home(request: Request) -> HTMLResponse: """Return home page for cyclops model report app. @@ -120,7 +120,7 @@ async def get_home(request: Request) -> HTMLResponse: return templates.TemplateResponse("test_report.html", {"request": request}) -@app.post("/evaluate") +@app.post("/evaluate") # type: ignore[misc] async def evaluate_result(data: EvaluationInput) -> None: """Calculate metric and return result from request body. @@ -151,7 +151,7 @@ async def evaluate_result(data: EvaluationInput) -> None: raise HTTPException(status_code=500, detail="Internal server error") from e -@app.get("/evaluate", response_class=HTMLResponse) +@app.get("/evaluate", response_class=HTMLResponse) # type: ignore[misc] async def get_report(request: Request) -> HTMLResponse: """Return latest updated model report. From 65542483206e0fc2093e3bcec2e61486c0b05fa0 Mon Sep 17 00:00:00 2001 From: Amrit Krishnan Date: Thu, 27 Jun 2024 08:43:26 -0400 Subject: [PATCH 10/10] Fix README --- deploy/report/README.md | 1 - 1 file changed, 1 deletion(-) diff --git a/deploy/report/README.md b/deploy/report/README.md index 1ea891069..c760ee74e 100644 --- a/deploy/report/README.md +++ b/deploy/report/README.md @@ -9,7 +9,6 @@ poetry install --with deploy_report 2. Run the evaluation server. ```bash -cd api/ uvicorn api.main:app --reload --host --port ```