Skip to content

Fix pipeline tests #18487

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
sgugger merged 2 commits into from
Aug 5, 2022
Merged

Fix pipeline tests #18487

Show file tree
Hide file tree
Changes from 1 commit
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
9c5ffc0
Fix pipeline tests
sgugger Aug 5, 2022
74e65c0
Make sure all pipelines tests run with init changes
sgugger Aug 5, 2022
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
1 change: 1 addition & 0 deletions src/transformers/pipelines/__init__.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -606,6 +606,7 @@ def pipeline(

# Retrieve the task
if task in custom_tasks:
normalized_task = task
targeted_task, task_options = clean_custom_task(custom_tasks[task])
if pipeline_class is None:
if not trust_remote_code:
Expand Down
4 changes: 2 additions & 2 deletions tests/pipelines/test_pipelines_common.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -795,7 +795,7 @@ def test_warning_logs(self):
alias = "text-classification"
# Get the original task, so we can restore it at the end.
# (otherwise the subsequential tests in `TextClassificationPipelineTests` will fail)
original_task, original_task_options = PIPELINE_REGISTRY.check_task(alias)
_, original_task, _ = PIPELINE_REGISTRY.check_task(alias)

try:
with CaptureLogger(logger_) as cm:
Expand All @@ -816,7 +816,7 @@ def test_register_pipeline(self):
)
assert "custom-text-classification" in PIPELINE_REGISTRY.get_supported_tasks()

task_def, _ = PIPELINE_REGISTRY.check_task("custom-text-classification")
_, task_def, _ = PIPELINE_REGISTRY.check_task("custom-text-classification")
self.assertEqual(task_def["pt"], (AutoModelForSequenceClassification,) if is_torch_available() else ())
self.assertEqual(task_def["tf"], (TFAutoModelForSequenceClassification,) if is_tf_available() else ())
self.assertEqual(task_def["type"], "text")
Expand Down