feat: add pipeline registry abstraction (#17905)

* feat: add pipeline registry abstraction

- added `PipelineRegistry` abstraction
- updates `add_new_pipeline.mdx` (english docs) to reflect the api addition
- migrate `check_task` and `get_supported_tasks` from
  transformers/pipelines/__init__.py to
  transformers/pipelines/base.py#PipelineRegistry.{check_task,get_supported_tasks}

Signed-off-by: Aaron Pham <29749331+aarnphm@users.noreply.github.com>

* fix: update with upstream/main

chore: Apply suggestions from sgugger's code review

Signed-off-by: Aaron Pham <29749331+aarnphm@users.noreply.github.com>

Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* chore: PR updates

- revert src/transformers/dependency_versions_table.py from upstream/main
- updates pipeline registry to use global variables

Signed-off-by: Aaron Pham <29749331+aarnphm@users.noreply.github.com>

* tests: add tests for pipeline registry

Signed-off-by: Aaron Pham <29749331+aarnphm@users.noreply.github.com>

* tests: add test for output warning.

Signed-off-by: Aaron Pham <29749331+aarnphm@users.noreply.github.com>

* chore: fmt and cleanup unused imports

Signed-off-by: Aaron Pham <29749331+aarnphm@users.noreply.github.com>

* fix: change imports to top of the file and address comments

Signed-off-by: Aaron Pham <29749331+aarnphm@users.noreply.github.com>

Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

docs/source/en/add_new_pipeline.mdx

@@ -111,8 +111,35 @@ of arguments for ease of use (audio files, can be filenames, URLs or pure bytes)
 
 ## Adding it to the list of supported tasks
 
-Go to `src/transformers/pipelines/__init__.py` and fill in `SUPPORTED_TASKS` with your newly created pipeline.
-If possible it should provide a default model.
+To register your `new-task` to the list of supported tasks, provide the
+following task template:
+
+```python
+my_new_task = {
+    "impl": MyPipeline,
+    "tf": (),
+    "pt": (AutoModelForAudioClassification,) if is_torch_available() else (),
+    "default": {"model": {"pt": "user/awesome_model"}},
+    "type": "audio",  # current support type: text, audio, image, multimodal
+}
+```
+
+<Tip>
+
+Take a look at the `src/transformers/pipelines/__init__.py` and the dictionary `SUPPORTED_TASKS` to see how a task is defined.
+If possible your custom task should provide a default model.
+
+</Tip>
+
+Then add your custom task to the list of supported tasks via
+`PIPELINE_REGISTRY.register_pipeline()`:
+
+```python
+from transformers.pipelines import PIPELINE_REGISTRY
+
+PIPELINE_REGISTRY.register_pipeline("new-task", my_new_task)
+```
+
 
 ## Adding tests