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Fix flaky tests and tests on Windows (#9059)

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* fixes

* fix external tests

* lint

* add changeset

* comment

* fix client

* add changeset

* run on pull request label changes

* lint

* file explorer

* format

* format

* fix windows

* changes

* test

* format backend

* fix

* fix test

* fix tests

* fix

* rate limit

* fix

* trigger

* fix flakiness

* test

* reruns

* reqs

* fix functional tests

* fix test

---------

Co-authored-by: gradio-pr-bot <gradio-pr-bot@users.noreply.github.com>
This commit is contained in:
Abubakar Abid 2024-08-08 01:41:16 -07:00 committed by GitHub
parent 9fa635a8fd
commit 981731acb7
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16 changed files with 85 additions and 69 deletions
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6
.changeset/mighty-socks-clean.md Normal file
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@ -0,0 +1,6 @@
---
"gradio": minor
"gradio_client": minor
---
feat:Fix flaky tests and tests on Windows

1
.github/workflows/test-python.yml vendored
View File

@ -2,6 +2,7 @@ name: "python"
on:
pull_request:
types: [opened, synchronize, reopened, edited, labeled, unlabeled]
push:
branches:
- main

4
client/python/gradio_client/compatibility.py
View File

@ -101,7 +101,7 @@ class EndpointV3Compatibility:
headers=self.client.headers,
json=data,
verify=self.client.ssl_verify,
auth=self.client.httpx_auth,
**self.client.httpx_kwargs,
)
result = json.loads(response.content.decode("utf-8"))
try:
@ -155,7 +155,7 @@ class EndpointV3Compatibility:
headers=self.client.headers,
files=files,
verify=self.client.ssl_verify,
auth=self.client.httpx_auth,
**self.client.httpx_kwargs,
)
if r.status_code != 200:
uploaded = file_paths

4
client/python/test/test_client.py
View File

@ -340,7 +340,7 @@ class TestClientPredictions:
)
assert output["orig_name"] == "bus.png"
@pytest.mark.flaky
@pytest.mark.flaky(reruns=5)
def test_cancel_from_client_queued(self, cancel_from_client_demo):
with connect(cancel_from_client_demo) as client:
start = time.time()
@ -367,7 +367,7 @@ class TestClientPredictions:
break
time.sleep(0.5)
# Result for iterative jobs will raise there is an exception
with pytest.raises(CancelledError):
with pytest.raises(Exception):
job.result()
# The whole prediction takes 10 seconds to run
# and does not iterate. So this tests that we can cancel

1
gradio/blocks.py
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@ -1232,6 +1232,7 @@ class Blocks(BlockContext, BlocksEvents, metaclass=BlocksMeta):
dependency.pop("zerogpu", None)
dependency.pop("id", None)
dependency.pop("rendered_in", None)
dependency.pop("every", None)
dependency["preprocess"] = False
dependency["postprocess"] = False
if is_then_event:

3
gradio/components/__init__.py
View File

@ -37,7 +37,7 @@ from gradio.components.logout_button import LogoutButton
from gradio.components.markdown import Markdown
from gradio.components.model3d import Model3D
from gradio.components.multimodal_textbox import MultimodalTextbox
from gradio.components.native_plot import BarPlot, LinePlot, ScatterPlot
from gradio.components.native_plot import BarPlot, LinePlot, NativePlot, ScatterPlot
from gradio.components.number import Number
from gradio.components.paramviewer import ParamViewer
from gradio.components.plot import Plot
@ -120,4 +120,5 @@ __all__ = [
"ImageEditor",
"ParamViewer",
"MultimodalTextbox",
"NativePlot",
]

14
gradio/components/dataset.py
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@ -99,16 +99,20 @@ class Dataset(Component):
self.samples: list[list] = []
for example in self.raw_samples:
self.samples.append([])
for i, (component, ex) in enumerate(zip(self._components, example)):
for component, ex in zip(self._components, example):
# If proxy_url is set, that means it is being loaded from an external Gradio app
# which means that the example has already been processed.
if self.proxy_url is None:
# The `as_example()` method has been renamed to `process_example()` but we
# We do not need to process examples if the Gradio app is being loaded from
# an external Space because the examples have already been processed. Also,
# the `as_example()` method has been renamed to `process_example()` but we
# use the previous name to be backwards-compatible with previously-created
# custom components
self.samples[-1].append(component.as_example(ex))
self.samples[-1][i] = processing_utils.move_files_to_cache(
self.samples[-1][i], component, keep_in_cache=True
ex = component.as_example(ex)
self.samples[-1].append(
processing_utils.move_files_to_cache(
ex, component, keep_in_cache=True
)
)
self.type = type
self.label = label

19
gradio/components/file_explorer.py
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@ -19,6 +19,8 @@ if TYPE_CHECKING:
class FileExplorerData(GradioRootModel):
# The outer list is the list of files selected, and the inner list
# is the path to the file as a list, split by the os.sep.
root: List[List[str]]
@ -115,10 +117,10 @@ class FileExplorer(Component):
)
def example_payload(self) -> Any:
return [["Users", "gradio", "app.py"]]
return [["gradio", "app.py"]]
def example_value(self) -> Any:
return ["Users", "gradio", "app.py"]
return os.sep.join(["gradio", "app.py"])
def preprocess(self, payload: FileExplorerData | None) -> list[str] | str | None:
"""
@ -138,14 +140,14 @@ class FileExplorer(Component):
elif len(payload.root) == 0:
return None
else:
return self._safe_join(payload.root[0])
return os.path.normpath(os.path.join(self.root_dir, *payload.root[0]))
files = []
for file in payload.root:
file_ = self._safe_join(file)
file_ = os.path.normpath(os.path.join(self.root_dir, *file))
files.append(file_)
return files
def _strip_root(self, path):
def _strip_root(self, path: str) -> str:
if path.startswith(self.root_dir):
return path[len(self.root_dir) + 1 :]
return path
@ -168,7 +170,7 @@ class FileExplorer(Component):
return FileExplorerData(root=root)
@server
def ls(self, subdirectory: list | None = None) -> list[dict[str, str]] | None:
def ls(self, subdirectory: list[str] | None = None) -> list[dict[str, str]] | None:
"""
Returns:
a list of dictionaries, where each dictionary represents a file or subdirectory in the given subdirectory
@ -203,8 +205,9 @@ class FileExplorer(Component):
return folders + files
def _safe_join(self, folders: list[str]):
def _safe_join(self, folders: list[str]) -> str:
if not folders or len(folders) == 0:
return self.root_dir
combined_path = UserProvidedPath(os.path.join(*folders))
return safe_join(self.root_dir, combined_path)
x = safe_join(self.root_dir, combined_path)
return x

28
gradio/external.py
View File

@ -9,7 +9,7 @@ import re
import tempfile
import warnings
from pathlib import Path
from typing import TYPE_CHECKING, Callable
from typing import TYPE_CHECKING, Callable, Literal
import httpx
import huggingface_hub
@ -37,7 +37,7 @@ if TYPE_CHECKING:
def load(
name: str,
src: str | None = None,
hf_token: str | None = None,
hf_token: str | Literal[False] | None = None,
alias: str | None = None,
**kwargs,
) -> Blocks:
@ -48,7 +48,7 @@ def load(
Parameters:
name: the name of the model (e.g. "gpt2" or "facebook/bart-base") or space (e.g. "flax-community/spanish-gpt2"), can include the `src` as prefix (e.g. "models/facebook/bart-base")
src: the source of the model: `models` or `spaces` (or leave empty if source is provided as a prefix in `name`)
hf_token: optional access token for loading private Hugging Face Hub models or spaces. Find your token here: https://huggingface.co/settings/tokens. Warning: only provide this if you are loading a trusted private Space as it can be read by the Space you are loading.
hf_token: optional access token for loading private Hugging Face Hub models or spaces. Will default to the locally saved token if not provided. Pass `token=False` if you don't want to send your token to the server. Find your token here: https://huggingface.co/settings/tokens. Warning: only provide a token if you are loading a trusted private Space as it can be read by the Space you are loading.
alias: optional string used as the name of the loaded model instead of the default name (only applies if loading a Space running Gradio 2.x)
Returns:
a Gradio Blocks object for the given model
@ -65,7 +65,7 @@ def load(
def load_blocks_from_repo(
name: str,
src: str | None = None,
hf_token: str | None = None,
hf_token: str | Literal[False] | None = None,
alias: str | None = None,
**kwargs,
) -> Blocks:
@ -89,7 +89,7 @@ def load_blocks_from_repo(
if src.lower() not in factory_methods:
raise ValueError(f"parameter: src must be one of {factory_methods.keys()}")
if hf_token is not None:
if hf_token is not None and hf_token is not False:
if Context.hf_token is not None and Context.hf_token != hf_token:
warnings.warn(
"""You are loading a model/Space with a different access token than the one you used to load a previous model/Space. This is not recommended, as it may cause unexpected behavior."""
@ -100,12 +100,16 @@ def load_blocks_from_repo(
return blocks
def from_model(model_name: str, hf_token: str | None, alias: str | None, **kwargs):
def from_model(
model_name: str, hf_token: str | Literal[False] | None, alias: str | None, **kwargs
):
model_url = f"https://huggingface.co/{model_name}"
api_url = f"https://api-inference.huggingface.co/models/{model_name}"
print(f"Fetching model from: {model_url}")
headers = {"Authorization": f"Bearer {hf_token}"} if hf_token is not None else {}
headers = (
{} if hf_token in [False, None] else {"Authorization": f"Bearer {hf_token}"}
)
response = httpx.request("GET", api_url, headers=headers)
if response.status_code != 200:
raise ModelNotFoundError(
@ -368,7 +372,11 @@ def from_model(model_name: str, hf_token: str | None, alias: str | None, **kwarg
def query_huggingface_inference_endpoints(*data):
if preprocess is not None:
data = preprocess(*data)
data = fn(*data) # type: ignore
try:
data = fn(*data) # type: ignore
except huggingface_hub.utils.HfHubHTTPError as e:
if "429" in str(e):
raise TooManyRequestsError() from e
if postprocess is not None:
data = postprocess(data) # type: ignore
return data
@ -396,7 +404,7 @@ def from_spaces(
print(f"Fetching Space from: {space_url}")
headers = {}
if hf_token is not None:
if hf_token not in [False, None]:
headers["Authorization"] = f"Bearer {hf_token}"
iframe_url = (
@ -478,7 +486,7 @@ def from_spaces_interface(
config = external_utils.streamline_spaces_interface(config)
api_url = f"{iframe_url}/api/predict/"
headers = {"Content-Type": "application/json"}
if hf_token is not None:
if hf_token not in [False, None]:
headers["Authorization"] = f"Bearer {hf_token}"
# The function should call the API with preprocessed data

2
test/components/test_file_explorer.py
View File

@ -69,4 +69,4 @@ class TestFileExplorer:
file_explorer = gr.FileExplorer(glob="*.txt", root_dir=Path(tmpdir))
with pytest.raises(InvalidPathError):
file_explorer.preprocess(FileExplorerData(root=[["../file.txt"]]))
file_explorer.ls(["../file.txt"])

1
test/requirements.in
View File

@ -13,6 +13,7 @@ pydantic[email]
pytest
pytest-asyncio
pytest-cov
pytest-rerunfailures
ruff>=0.1.13
respx
scikit-image

6
test/requirements.txt
View File

@ -201,7 +201,7 @@ pillow==9.2.0
# imageio
# matplotlib
# scikit-image
pluggy==1.0.0
pluggy==1.5.0
# via pytest
polars==0.20.5
# via -r requirements.in
@ -228,7 +228,7 @@ pyparsing==3.0.9
# via matplotlib
pyrsistent==0.18.1
# via jsonschema
pytest==7.1.2
pytest==8.3.2
# via
# -r requirements.in
# pytest-asyncio
@ -237,6 +237,8 @@ pytest-asyncio==0.19.0
# via -r requirements.in
pytest-cov==3.0.0
# via -r requirements.in
pytest-rerunfailures==14.0
# via -r requirements.in
python-dateutil==2.8.2
# via
# botocore

6
test/test_components.py
View File

@ -124,8 +124,10 @@ def test_component_example_payloads(io_components):
for component in io_components:
if component == PDF:
continue
elif component in [gr.BarPlot, gr.LinePlot, gr.ScatterPlot]:
elif issubclass(component, gr.components.NativePlot):
c: Component = component(x="x", y="y")
elif component == gr.FileExplorer:
c: Component = component(root_dir="gradio")
else:
c: Component = component()
data = c.example_payload()
@ -140,4 +142,4 @@ def test_component_example_payloads(io_components):
data = c.data_model(**data) # type: ignore
elif issubclass(c.data_model, GradioRootModel): # type: ignore
data = c.data_model(root=data) # type: ignore
c.preprocess(data)
c.preprocess(data) # type: ignore

44
test/test_external.py
View File

@ -202,21 +202,23 @@ class TestLoadInterface:
assert isinstance(io.output_components[0], gr.Textbox)
def test_sentiment_model(self):
io = gr.load("models/distilbert-base-uncased-finetuned-sst-2-english")
io = gr.load(
"models/distilbert-base-uncased-finetuned-sst-2-english", hf_token=False
)
try:
assert io("I am happy, I love you")["label"] == "POSITIVE"
except TooManyRequestsError:
pass
def test_image_classification_model(self):
io = gr.load(name="models/google/vit-base-patch16-224")
io = gr.load(name="models/google/vit-base-patch16-224", hf_token=False)
try:
assert io("gradio/test_data/lion.jpg")["label"].startswith("lion")
except TooManyRequestsError:
pass
def test_translation_model(self):
io = gr.load(name="models/t5-base")
io = gr.load(name="models/t5-base", hf_token=False)
try:
output = io("My name is Sarah and I live in London")
assert output == "Mein Name ist Sarah und ich lebe in London"
@ -236,7 +238,7 @@ class TestLoadInterface:
pass
def test_visual_question_answering(self):
io = gr.load("models/dandelin/vilt-b32-finetuned-vqa")
io = gr.load("models/dandelin/vilt-b32-finetuned-vqa", hf_token=False)
try:
output = io("gradio/test_data/lion.jpg", "What is in the image?")
assert isinstance(output, dict) and "label" in output
@ -244,29 +246,15 @@ class TestLoadInterface:
pass
def test_image_to_text(self):
io = gr.load("models/nlpconnect/vit-gpt2-image-captioning")
io = gr.load("models/nlpconnect/vit-gpt2-image-captioning", hf_token=False)
try:
output = io("gradio/test_data/lion.jpg")
assert isinstance(output, str)
except TooManyRequestsError:
pass
def test_conversational_in_blocks(self):
with gr.Blocks() as io:
gr.load("models/microsoft/DialoGPT-medium")
app, _, _ = io.launch(prevent_thread_lock=True)
client = TestClient(app)
response = client.post(
"/api/predict/",
json={"session_hash": "foo", "data": ["Hi!"], "fn_index": 0},
)
output = response.json()
assert isinstance(output["data"], list)
assert isinstance(output["data"][0], str)
assert "foo" in app.state_holder # type: ignore
def test_speech_recognition_model(self):
io = gr.load("models/facebook/wav2vec2-base-960h")
io = gr.load("models/facebook/wav2vec2-base-960h", hf_token=False)
try:
output = io("gradio/test_data/test_audio.wav")
assert output is not None
@ -365,11 +353,15 @@ class TestLoadInterfaceWithExamples:
with patch(
"gradio.utils.get_cache_folder", return_value=Path(tempfile.mkdtemp())
):
gr.load(
name="models/google/vit-base-patch16-224",
examples=[Path(test_file_dir, "cheetah1.jpg")],
cache_examples=True,
)
try:
gr.load(
name="models/google/vit-base-patch16-224",
examples=[Path(test_file_dir, "cheetah1.jpg")],
cache_examples=True,
hf_token=False,
)
except TooManyRequestsError:
pass
def test_proxy_url(self):
demo = gr.load("spaces/gradio/test-loading-examplesv4-sse")
@ -515,6 +507,8 @@ def test_use_api_name_in_call_method():
def test_load_custom_component():
from gradio_pdf import PDF # noqa
demo = gr.load("spaces/freddyaboulton/gradiopdf")
output = demo(
"test/test_files/sample_file.pdf", "What does this say?", api_name="predict"

13
test/test_helpers.py
View File

@ -820,13 +820,13 @@ class TestProgressBar:
]
@pytest.mark.asyncio
@pytest.mark.flaky
@pytest.mark.flaky(reruns=5)
async def test_progress_bar_track_tqdm_without_iterable(self):
def greet(s, _=gr.Progress(track_tqdm=True)):
with tqdm(total=len(s)) as progress_bar:
for _c in s:
progress_bar.update()
time.sleep(0.15)
time.sleep(0.1)
return f"Hello, {s}!"
demo = gr.Interface(greet, "text", "text")
@ -849,14 +849,7 @@ class TestProgressBar:
status_updates.append(update)
time.sleep(0.05)
assert status_updates == [
(1, "steps"),
(2, "steps"),
(3, "steps"),
(4, "steps"),
(5, "steps"),
(6, "steps"),
]
assert status_updates[-1] == (6, "steps")
@pytest.mark.asyncio
async def test_info_and_warning_alerts(self):

2
test/test_routes.py
View File

@ -1383,7 +1383,7 @@ def test_file_access():
r = test_client.get(f"/file={allowed_dir}/allowed.txt")
assert r.status_code == 200
r = test_client.get(f"/file={allowed_dir}/../not_allowed.txt")
assert r.status_code == 403
assert r.status_code in [403, 404] # 403 in Linux, 404 in Windows
r = test_client.get("/file=//test/test_files/cheetah1.jpg")
assert r.status_code == 403
r = test_client.get("/file=test/test_files/cheetah1.jpg")