修改lightop的rmsnorm

dcu_megatron/legacy/model/rms_norm.py

+# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
+
+import torch
+from torch import nn
+
+class RMSNorm(torch.nn.Module):
+
+    def __init__(self,
+                 dim: int,
+                 eps: float = 1e-6,
+                 sequence_parallel: bool = False,
+                 config: dict = None):
+        """RMS Normaliation module
+
+        Args:
+            dim (int): The width of input, i.e. hidden size
+            eps (float): epsilon to use for the norm, default to 1e-6
+            sequence_parallel (bool): Set to true if sequence parallelism is being used,
+              this marks the weights as needing to be allreduced.
+        """
+        super().__init__()
+        self.eps = eps
+        self.weight = nn.Parameter(torch.ones(dim))
+
+        setattr(self.weight, 'sequence_parallel', sequence_parallel)
+
+    def _norm(self, x):
+        return x * torch.rsqrt(x.pow(2).mean(-1, keepdim=True) + self.eps)
+
+    @torch.compile(mode="max-autotune-no-cudagraphs")
+    def forward(self, x):
+        output = self._norm(x.float()).type_as(x)
+        return output * self.weight
+
 import torch
 
 from typing import Any, Callable, Dict, Optional, Tuple, Union

dcu_megatron/legacy/model/utils.py

 from megatron.training import get_args
 from megatron.legacy.model import LayerNorm
-from .rms_norm import LightopRMSNorm
+from .rms_norm import RMSNorm, LightopRMSNorm
 
 
 def get_norm(config):
@@ -15,8 +15,12 @@ def get_norm(config):
     elif args.normalization == "RMSNorm":
         if args.apply_layernorm_1p:
             raise NotImplementedError('RMSNorm does not currently support the layernorm_1p formulation.')
-
+    
+        return RMSNorm(dim=config.hidden_size,
+                       eps=config.layernorm_epsilon,
+                       sequence_parallel=config.sequence_parallel)
+    elif args.normalization == "LightopRMSNorm":
         return LightopRMSNorm(dim=config.hidden_size,
-                              eps=config.layernorm_epsilon)
+                       eps=config.layernorm_epsilon)
     else:
         raise Exception(f"unsupported norm type '{args.normalization}'.")

dcu_megatron/training/arguments.py

@@ -51,6 +51,7 @@ def parse_args(extra_args_provider=None, ignore_unknown_args=False):
 
     # Standard arguments.
     parser = _add_network_size_args(parser)
+    parser = _add_extra_network_size_args(parser)
     parser = _add_regularization_args(parser)
     parser = _add_training_args(parser)
     parser = _add_extra_training_args(parser)
@@ -106,6 +107,18 @@ def parse_args(extra_args_provider=None, ignore_unknown_args=False):
     return args
 
 
+def _add_extra_network_size_args(parser):
+    # 删除原参数
+    remove_original_params(parser, ["normalization"])
+
+    # 重定义参数
+    group = parser.add_argument_group(title='extra network size args')
+    group.add_argument('--normalization', default='LayerNorm',
+                       choices=['LayerNorm', 'RMSNorm', 'LightopRMSNorm'],
+                       help='Which normalization technique to use.')
+    return parser
+
+
 def _add_extra_distributed_args(parser):
     group = parser.add_argument_group(title='extra distributed args')
     group.add_argument('--rank', default=-1, type=int,