I have a microservice (fastapi) that serves predictions from a model that was pre-trained in a separate repo. Ideally, this microservice only has one job: given an input X, a pre-trained model, and a pickled my_transformer: serve predictions y. The microservice shouldn't know/care about what the model or my_transformer are or how they work. my_transformer = sklearn.preprocessing.FunctionTransformer( func = lambda y: -np.log(y / 100), inverse_func = lambda y_transformed: np.exp(-y_transformed) * 100, ) y_transformed = my_transformer.transform(y) model.fit(X,y_transformed) The API should just be able to load the transformer (via dill -- because lambda functions aren't pickleable via pickle or joblib), and call inverse_transform. For the most part, this works as expected... that is until I start using fastapi and/or uvicorn. The error/stack trace I'm getting is Traceback (most recent call last): File "/Users/[me]/.local/share/virtualenvs/[my_venv]/lib/python3.9/site-packages/uvicorn/protocols/http/h11_impl.py", line 428, in run_asgi result = await app( # type: ignore[func-returns-value] File "/Users/[me]/.local/share/virtualenvs/[my_venv]/lib/python3.9/site-packages/uvicorn/middleware/proxy_headers.py", line 78, in __call__ return await self.app(scope, receive, send) File "/Users/[me]/.local/share/virtualenvs/[my_venv]/lib/python3.9/site-packages/fastapi/applications.py", line 276, in __call__ await super().__call__(scope, receive, send) File "/Users/[me]/.local/share/virtualenvs/[my_venv]/lib/python3.9/site-packages/starlette/applications.py", line 122, in __call__ await self.middleware_stack(scope, receive, send) File "/Users/[me]/.local/share/virtualenvs/[my_venv]/lib/python3.9/site-packages/starlette/middleware/errors.py", line 184, in __call__ raise exc File "/Users/[me]/.local/share/virtualenvs/[my_venv]/lib/python3.9/site-packages/starlette/middleware/errors.py", line 162, in __call__ await self.app(scope, receive, _send) File "/Users/[me]/.local/share/virtualenvs/[my_venv]/lib/python3.9/site-packages/starlette/middleware/exceptions.py", line 79, in __call__ raise exc File "/Users/[me]/.local/share/virtualenvs/[my_venv]/lib/python3.9/site-packages/starlette/middleware/exceptions.py", line 68, in __call__ await self.app(scope, receive, sender) File "/Users/[me]/.local/share/virtualenvs/[my_venv]/lib/python3.9/site-packages/fastapi/middleware/asyncexitstack.py", line 21, in __call__ raise e File "/Users/[me]/.local/share/virtualenvs/[my_venv]/lib/python3.9/site-packages/fastapi/middleware/asyncexitstack.py", line 18, in __call__ await self.app(scope, receive, send) File "/Users/[me]/.local/share/virtualenvs/[my_venv]/lib/python3.9/site-packages/starlette/routing.py", line 718, in __call__ await route.handle(scope, receive, send) File "/Users/[me]/.local/share/virtualenvs/[my_venv]/lib/python3.9/site-packages/starlette/routing.py", line 276, in handle await self.app(scope, receive, send) File "/Users/[me]/.local/share/virtualenvs/[my_venv]/lib/python3.9/site-packages/starlette/routing.py", line 66, in app response = await func(request) File "/Users/[me]/.local/share/virtualenvs/[my_venv]/lib/python3.9/site-packages/fastapi/routing.py", line 237, in app raw_response = await run_endpoint_function( File "/Users/[me]/.local/share/virtualenvs/[my_venv]/lib/python3.9/site-packages/fastapi/routing.py", line 165, in run_endpoint_function return await run_in_threadpool(dependant.call, **values) File "/Users/[me]/.local/share/virtualenvs/[my_venv]/lib/python3.9/site-packages/starlette/concurrency.py", line 41, in run_in_threadpool return await anyio.to_thread.run_sync(func, *args) File "/Users/[me]/.local/share/virtualenvs/[my_venv]/lib/python3.9/site-packages/anyio/to_thread.py", line 33, in run_sync return await get_asynclib().run_sync_in_worker_thread( File "/Users/[me]/.local/share/virtualenvs/[my_venv]/lib/python3.9/site-packages/anyio/_backends/_asyncio.py", line 877, in run_sync_in_worker_thread return await future File "/Users/[me]/.local/share/virtualenvs/[my_venv]/lib/python3.9/site-packages/anyio/_backends/_asyncio.py", line 807, in run result = context.run(func, *args) File "/Users/[me]/repos/perpetua1/kpi_predictor/basic_app.py", line 23, in root my_transformer.transform(arr), File "/Users/[me]/.local/share/virtualenvs/[my_venv]/lib/python3.9/site-packages/sklearn/utils/_set_output.py", line 140, in wrapped data_to_wrap = f(self, X, *args, **kwargs) File "/Users/[me]/.local/share/virtualenvs/[my_venv]/lib/python3.9/site-packages/sklearn/preprocessing/_function_transformer.py", line 238, in transform return self._transform(X, func=self.func, kw_args=self.kw_args) File "/Users/[me]/.local/share/virtualenvs/[my_venv]/lib/python3.9/site-packages/sklearn/preprocessing/_function_transformer.py", line 310, in _transform return func(X, **(kw_args if kw_args else {})) File "/var/folders/td/_z1v0f3x703gj0wdnfms4h7c0000gp/T/ipykernel_9600/434310704.py", line 4, in <lambda> NameError: name 'np' is not defined I've narrowed it down to potentially be related to how uvicorn is run, but don't understand why it breaks. Applying the following fix to my (more complicated) project also doesn't work, so I'm HOPING that understanding why it's breaking will help inform how to solve the more complicated case. A basic version of my app looks like: import dill import numpy as np import pandas as pd import uvicorn from fastapi import FastAPI from pydantic import BaseModel class ReturnValue(BaseModel): value: float app = FastAPI() @app.post("/", response_model=list[ReturnValue]) def root(): with open("my_transformer.dill", "rb") as io: my_transformer = dill.load(io) arr = np.random.uniform(0, 100, 10) return pd.DataFrame( my_transformer.transform(arr), columns=["value"], ).to_dict(orient="records") if __name__ == "__main__": # uvicorn.run("basic_app:app", reload=True) # NameError uvicorn.run(app) # runs as expected for this simple case, doesn't work for the more complicated app Continue reading...
