[feature] support no master weights option for low level zero plugin (#4816)

* [feature] support no master weights for low level zero plugin

* [feature] support no master weights for low level zero plugin, remove data copy when no master weights

* remove data copy and typecasting when no master weights

* not load weights to cpu when using no master weights

* fix grad: use fp16 grad when no master weights

* only do not update working param when no master weights

* fix: only do not update working param when no master weights

* fix: passing params in dict format in hybrid plugin

* fix: remove extra params (tp_process_group) in hybrid_parallel_plugin

colossalai/booster/plugin/low_level_zero_plugin.py

@@ -262,6 +262,7 @@ class LowLevelZeroPlugin(DPPluginBase):
         communication_dtype: Optional[torch.dtype] = None,
         overlap_communication: bool = True,
         cpu_offload: bool = False,
+        master_weights: bool = True,
         verbose: bool = False,
     ) -> None:
         super().__init__()
@@ -272,18 +273,19 @@ class LowLevelZeroPlugin(DPPluginBase):
         self.precision = precision
         self.zero_optim_kwargs = dict(
             initial_scale=initial_scale,
+            min_scale=min_scale,
             growth_factor=growth_factor,
             backoff_factor=backoff_factor,
             growth_interval=growth_interval,
             hysteresis=hysteresis,
-            min_scale=min_scale,
             max_scale=max_scale,
             clip_grad_norm=max_norm,
             reduce_bucket_size=reduce_bucket_size_in_m * 1024 * 1024,
             communication_dtype=communication_dtype,
             overlap_communication=overlap_communication,
-            cpu_offload=cpu_offload,
             partition_grad=(stage == 2),
+            cpu_offload=cpu_offload,
+            master_weights=master_weights,
         )
         self.verbose = verbose