[Feature] Support Adafactor Optimizer (#1361)

docs/en/common_usage/better_optimizers.md

@@ -121,3 +121,35 @@ runner = Runner(
 )
 runner.train()
 ```
+
+## transformers
+
+[transformers](https://github.com/huggingface/transformers) provides `Adafactor` optimzier。
+
+```{note}
+If you use the optimizer provided by transformers, you need to upgrade mmengine to `0.8.5`.
+```
+
+- Installation
+
+```bash
+pip install transformers
+```
+
+- Usage
+
+Take the `Adafactor` as an example.
+
+```python
+runner = Runner(
+    model=ResNet18(),
+    work_dir='./work_dir',
+    train_dataloader=train_dataloader_cfg,
+    # To view the input parameters for Adafactor, you can refer to
+    # https://github.com/huggingface/transformers/blob/v4.33.2/src/transformers/optimization.py#L492
+    optim_wrapper=dict(optimizer=dict(type='Adafactor', lr=1e-5,
+        weight_decay=1e-2, scale_parameter=False, relative_step=False)),
+    train_cfg=dict(by_epoch=True, max_epochs=3),
+)
+runner.train()
+```

mmengine/optim/optimizer/builder.py

@@ -157,6 +157,21 @@ def register_bitsandbytes_optimizers() -> List[str]:
 BITSANDBYTES_OPTIMIZERS = register_bitsandbytes_optimizers()
 
 
+def register_transformers_optimizers():
+    transformer_optimizers = []
+    try:
+        from transformers import Adafactor
+    except ImportError:
+        pass
+    else:
+        OPTIMIZERS.register_module(name='Adafactor', module=Adafactor)
+        transformer_optimizers.append('Adafactor')
+    return transformer_optimizers
+
+
+TRANSFORMERS_OPTIMIZERS = register_transformers_optimizers()
+
+
 def build_optim_wrapper(model: nn.Module,
                         cfg: Union[dict, Config, ConfigDict]) -> OptimWrapper:
     """Build function of OptimWrapper.

requirements/tests.txt

@@ -11,3 +11,4 @@ neptune
 parameterized
 pydantic==1.10.9
 pytest
+transformers

tests/test_optim/test_optimizer/test_optimizer.py

@@ -17,7 +17,8 @@
 from mmengine.optim.optimizer.builder import (BITSANDBYTES_OPTIMIZERS,
                                               DADAPTATION_OPTIMIZERS,
                                               LION_OPTIMIZERS,
-                                              TORCH_OPTIMIZERS)
+                                              TORCH_OPTIMIZERS,
+                                              TRANSFORMERS_OPTIMIZERS)
 from mmengine.registry import DefaultScope, Registry, build_from_cfg
 from mmengine.testing._internal import MultiProcessTestCase
 from mmengine.utils.dl_utils import TORCH_VERSION, mmcv_full_available
@@ -53,6 +54,14 @@ def has_bitsandbytes() -> bool:
         return False
 
 
+def has_transformers() -> bool:
+    try:
+        import transformers  # noqa: F401
+        return True
+    except ImportError:
+        return False
+
+
 class ExampleModel(nn.Module):
 
     def __init__(self):
@@ -244,7 +253,7 @@ def test_dadaptation_optimizers(self):
     def test_lion_optimizers(self):
         assert 'Lion' in LION_OPTIMIZERS
 
-    @unittest.skipIf(not has_bitsandbytes(), 'dadaptation is not installed')
+    @unittest.skipIf(not has_bitsandbytes(), 'bitsandbytes is not installed')
     def test_bitsandbytes_optimizers(self):
         bitsandbytes_optimizers = [
             'AdamW8bit', 'Adam8bit', 'Adagrad8bit', 'PagedAdam8bit',
@@ -254,6 +263,12 @@ def test_bitsandbytes_optimizers(self):
         assert set(bitsandbytes_optimizers).issubset(
             set(BITSANDBYTES_OPTIMIZERS))
 
+    @unittest.skipIf(not has_transformers(), 'transformers is not installed')
+    def test_transformers_optimizers(self):
+        transformers_optimizers = ['Adafactor']
+        assert set(transformers_optimizers).issubset(
+            set(TRANSFORMERS_OPTIMIZERS))
+
     def test_build_optimizer(self):
         # test build function without ``constructor`` and ``paramwise_cfg``
         optim_wrapper_cfg = dict(