Fix lr scheduler state not being dumped to checkpoint in deepspeed strategy (#11307)

CHANGELOG.md

@@ -403,6 +403,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Fixed a race condition that could result in incorrect (zero) values being observed in prediction writer callbacks ([#11288](https://github.com/PyTorchLightning/pytorch-lightning/pull/11288))
 
 
+- Fixed the lr-scheduler state not being dumped to checkpoint when using the deepspeed strategy ([#11307](https://github.com/PyTorchLightning/pytorch-lightning/pull/11307))
+
+
 ## [1.5.7] - 2021-12-21
 
 ### Fixed

pytorch_lightning/strategies/deepspeed.py

@@ -741,7 +741,7 @@ class DeepSpeedStrategy(DDPStrategy):
             )
         # Use deepspeed's internal checkpointing function to handle partitioned weights across processes
         # dump states as a checkpoint dictionary object
-        _exclude_keys = ["state_dict", "optimizer_states", "lr_schedulers"]
+        _exclude_keys = ["state_dict", "optimizer_states"]
         checkpoint = {k: v for k, v in checkpoint.items() if k not in _exclude_keys}
         self.deepspeed_engine.save_checkpoint(filepath, client_state=checkpoint)
 

tests/strategies/test_deepspeed_strategy.py

@@ -558,6 +558,10 @@ class ModelParallelClassificationModel(LightningModule):
         if not hasattr(self, "model"):
             self.configure_sharded_model()
 
+        # Lightning saves the lr schedulers, but DeepSpeed saves the optimizer states separately
+        assert len(checkpoint["lr_schedulers"]) == 1
+        assert "optimizer_states" not in checkpoint
+
 
 class ManualModelParallelClassificationModel(ModelParallelClassificationModel):
     @property