[shardformer] fix pipeline grad ckpt (#5620)

* [shardformer] fix pipeline grad ckpt

colossalai/shardformer/shard/grad_ckpt_config.py

@@ -22,6 +22,7 @@ class PipelineGradientCheckpointConfig(GradientCheckpointConfig):
         2. Customize # ckpt layers assigned to each stage. This takes precedence over `gradient_checkpointing_ratio`.
 
     """
+
     """
     Args:
         gradient_checkpointing_ratio (Optional[float]): The ratio of gradient checkpointing. It can only be used in pipeline parallelism. Defaults to None.
@@ -49,6 +50,7 @@ class PipelineGradientCheckpointConfig(GradientCheckpointConfig):
     num_stages: Optional[int] = None
     num_model_chunks: Optional[int] = None
     num_model_layers: Optional[int] = None
+    num_layers_per_stage: Optional[List[int]] = None
     num_ckpt_layers_per_stage: Optional[List[int]] = None
 
     def __post_init__(self):
@@ -70,6 +72,10 @@ class PipelineGradientCheckpointConfig(GradientCheckpointConfig):
     def _enable_gradient_checkpointing_ratio(self) -> bool:
         return self.gradient_checkpointing_ratio is not None
 
+    @property
+    def _customize_num_layers_per_stage(self) -> bool:
+        return self.num_layers_per_stage is not None and self.num_model_layers is not None
+
     @property
     def _enable_customized_ckpt_layers_per_stage(self) -> bool:
         return self.num_ckpt_layers_per_stage is not None

colossalai/shardformer/shard/shard_config.py

@@ -7,7 +7,7 @@ from torch.distributed import ProcessGroup
 
 from colossalai.pipeline.stage_manager import PipelineStageManager
 
-from .grad_ckpt_config import GradientCheckpointConfig
+from .grad_ckpt_config import GradientCheckpointConfig, PipelineGradientCheckpointConfig
 
 __all__ = ["ShardConfig"]
 SUPPORT_SP_MODE = ["split_gather", "ring", "all_to_all"]
@@ -30,6 +30,7 @@ class ShardConfig:
         gradient_checkpoint_config (Optional[GradientCheckpointConfig]): The gradient checkpoint config. Defaults to None.
         enable_all_optimization (bool): Whether to turn on all optimization tools including 'fused normalization', 'flash attention', 'JIT fused operators', 'sequence parallelism' and 'sequence overlap'. Defaults to False.
     """
+
     tensor_parallel_process_group: Optional[ProcessGroup] = None
     sequence_parallel_process_group: Optional[ProcessGroup] = None
     pipeline_stage_manager: Optional[PipelineStageManager] = None
@@ -104,6 +105,16 @@ class ShardConfig:
         else:
             self._sequence_parallel_size = dist.get_world_size(self.sequence_parallel_process_group)
 
+        if (
+            self.pipeline_stage_manager is not None
+            and isinstance(self.gradient_checkpoint_config, PipelineGradientCheckpointConfig)
+            and self.gradient_checkpoint_config._customize_num_layers_per_stage
+        ):
+            self.pipeline_stage_manager.set_distribution_config(
+                self.gradient_checkpoint_config.num_model_layers,
+                self.gradient_checkpoint_config.num_layers_per_stage,
+            )
+
     def _turn_on_all_optimization(self):
         """
         Turn on all optimization.