Initial commit

verl/models/llama/megatron/layers/parallel_rmsnorm.py

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+# Copyright 2024 Bytedance Ltd. and/or its affiliates
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import numbers
+import torch
+from megatron.core import ModelParallelConfig
+from torch import nn
+from transformers import LlamaConfig
+
+from apex.normalization.fused_layer_norm import fused_rms_norm_affine
+from verl.utils.megatron import sequence_parallel as sp_utils
+
+
+class ParallelLlamaRMSNorm(nn.Module):
+
+    def __init__(self, config: LlamaConfig, megatron_config: ModelParallelConfig):
+        """
+        LlamaRMSNorm is equivalent to T5LayerNorm
+        """
+        super().__init__()
+        if isinstance(config.hidden_size, numbers.Integral):
+            normalized_shape = (config.hidden_size,)
+        self.normalized_shape = torch.Size(normalized_shape)
+        self.weight = nn.Parameter(torch.ones(self.normalized_shape))
+        self.variance_epsilon = config.rms_norm_eps
+
+        if megatron_config.sequence_parallel:
+            sp_utils.mark_parameter_as_sequence_parallel(self.weight)
+
+    def forward(self, hidden_states):
+        return fused_rms_norm_affine(input=hidden_states,
+                                     weight=self.weight,
+                                     normalized_shape=self.normalized_shape,
+                                     eps=self.variance_epsilon,
+                                     memory_efficient=True)