[plugin] add cast inputs option for zero (#6003) (#6022)

colossalai/booster/plugin/low_level_zero_plugin.py

@@ -61,7 +61,9 @@ class OptimizerParamCheckState(enum.Enum):
 
 
 class LowLevelZeroModel(ModelWrapper, AMPModelMixin):
-    def __init__(self, module: nn.Module, precision: str, overlap_allgather: bool = False) -> None:
+    def __init__(
+        self, module: nn.Module, precision: str, overlap_allgather: bool = False, cast_inputs: bool = True
+    ) -> None:
         super().__init__(module)
         self.dtype = None
         if precision == "fp16":
@@ -73,7 +75,7 @@ class LowLevelZeroModel(ModelWrapper, AMPModelMixin):
         module = module.to(get_accelerator().get_current_device())
         self.module = module
         self.convert_fn = None
-        if self.dtype is not None:
+        if self.dtype is not None and cast_inputs:
             self.convert_fn = partial(_convert_floating_point, dtype=self.dtype)
         self.overlap_allgather = overlap_allgather
         if overlap_allgather:
@@ -334,6 +336,7 @@ class LowLevelZeroPlugin(DPPluginBase):
         cpu_offload: bool = False,
         master_weights: bool = True,
         verbose: bool = False,
+        cast_inputs: bool = True,
     ) -> None:
         super().__init__()
         assert stage in (1, 2), f"LowLevelZeroPlugin only supports stage 1/2 training"
@@ -361,6 +364,8 @@ class LowLevelZeroPlugin(DPPluginBase):
         self.lora_enabled = False
         self.verbose = verbose
         self.logger = get_dist_logger()
+        self.cast_inputs = cast_inputs
+
         # set class name with stage, for better error message
         setattr(self.__class__, "__name__", f"LowLevelZeroPlugin_ZeRO-{stage}")
 
@@ -475,7 +480,10 @@ class LowLevelZeroPlugin(DPPluginBase):
 
         if not isinstance(model, ModelWrapper):
             model = LowLevelZeroModel(
-                model, self.precision, overlap_allgather=self.zero_optim_kwargs["overlap_allgather"]
+                model,
+                self.precision,
+                overlap_allgather=self.zero_optim_kwargs["overlap_allgather"],
+                cast_inputs=self.cast_inputs,
             )
 
         # TODO: Support Galore + ZeRO