hotfix import torch

.github/workflows/ci-pkg-install.yml

@@ -46,7 +46,7 @@ jobs:
       - name: DocTests actions
         working-directory: .actions/
         run: |
-          pip install pytest -q
+          pip install -q pytest
           python -m pytest setup_tools.py
 
       - run: python -c "print('NB_DIRS=' + str(2 if '${{ matrix.pkg-name }}' == 'pytorch' else 1))" >> $GITHUB_ENV
@@ -69,5 +69,7 @@ jobs:
         env:
           PY_IGNORE_IMPORTMISMATCH: 1
         run: |
+          pip install -q "pytest-doctestplus>=0.9.0"
+          pip list
           PKG_NAME=$(python -c "print({'app': 'lightning_app', 'lite': 'lightning_lite', 'pytorch': 'pytorch_lightning', 'lightning': 'lightning'}['${{matrix.pkg-name}}'])")
           python -m pytest src/${PKG_NAME} --ignore-glob="**/cli/*-template/**"

requirements/app/test.txt

@@ -3,6 +3,7 @@ codecov==2.1.12
 pytest==7.2.0
 pytest-timeout==2.1.0
 pytest-cov==4.0.0
+pytest-doctestplus>=0.9.0
 playwright==1.27.1
 httpx
 trio<0.22.0

src/lightning_app/components/serve/python_server.py

@@ -4,7 +4,6 @@
 from pathlib import Path
 from typing import Any, Dict, Optional
 
-import torch
 import uvicorn
 from fastapi import FastAPI
 from pydantic import BaseModel
@@ -13,16 +12,21 @@
 from lightning_app.core.queues import MultiProcessQueue
 from lightning_app.core.work import LightningWork
 from lightning_app.utilities.app_helpers import Logger
+from lightning_app.utilities.imports import _is_torch_available, requires
 from lightning_app.utilities.proxies import _proxy_setattr, unwrap, WorkRunExecutor, WorkStateObserver
 
 logger = Logger(__name__)
 
+# Skip doctests if requirements aren't available
+if not _is_torch_available():
+    __doctest_skip__ = ["PythonServer", "PythonServer.*"]
+
 
 class _PyTorchSpawnRunExecutor(WorkRunExecutor):
 
     """This Executor enables to move PyTorch tensors on GPU.
 
-    Without this executor, it woud raise the following expection:
+    Without this executor, it would raise the following exception:
     RuntimeError: Cannot re-initialize CUDA in forked subprocess.
     To use CUDA with multiprocessing, you must use the 'spawn' start method
     """
@@ -86,6 +90,7 @@ def _get_sample_data() -> Dict[Any, Any]:
 
 
 class PythonServer(LightningWork, abc.ABC):
+    @requires("torch")
     def __init__(  # type: ignore
         self,
         host: str = "127.0.0.1",
@@ -199,11 +204,13 @@ def _get_sample_dict_from_datatype(datatype: Any) -> dict:
         return out
 
     def _attach_predict_fn(self, fastapi_app: FastAPI) -> None:
+        from torch import inference_mode
+
         input_type: type = self.configure_input_type()
         output_type: type = self.configure_output_type()
 
         def predict_fn(request: input_type):  # type: ignore
-            with torch.inference_mode():
+            with inference_mode():
                 return self.predict(request)
 
         fastapi_app.post("/predict", response_model=output_type)(predict_fn)

src/lightning_app/utilities/name_generator.py

@@ -1,5 +1,7 @@
 from random import choice, randint
 
+__doctest_skip__ = ["get_unique_name"]
+
 _adjectives = [
     # Appearance, sound, smell...
     "acrid",
@@ -1334,9 +1336,9 @@ def get_unique_name():
 
     Examples
     --------
-    >>> get_unique_name()  # doctest: +SKIP
+    >>> get_unique_name()
     'focused-turing-23'
-    >>> get_unique_name()  # doctest: +SKIP
+    >>> get_unique_name()
     'thirsty-allen-9200'
     """
     adjective, surname, i = choice(_adjectives), choice(_surnames), randint(0, 9999)