[GitHub] [tvm] junrushao commented on a diff in pull request #15326: [OP] Add `rms_norm` into TOPI

["junrushao (via GitHub)" <gi...@apache.org>]

junrushao commented on code in PR #15326:
URL: https://github.com/apache/tvm/pull/15326#discussion_r1264491720


##########
include/tvm/topi/nn/rms_norm.h:
##########
@@ -0,0 +1,94 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you 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.
+ */
+
+/*!
+ * \brief root mean square normalization op constructions
+ * \file nn/rms_norm.h
+ */
+#ifndef TVM_TOPI_NN_RMS_NORM_H_
+#define TVM_TOPI_NN_RMS_NORM_H_
+
+#include <tvm/te/operation.h>
+#include <tvm/topi/reduction.h>
+#include <tvm/topi/tags.h>
+
+#include <string>
+
+namespace tvm {
+namespace topi {
+namespace nn {
+
+using namespace tvm::te;
+
+/*!
+ * \brief Root mean square normalization.
+ * \param data N-D tensor with shape [d_0, d_1, ..., d_{N-1}]
+ * \param weight K-D tensor with shape [r_0, r_1, ..., r_{K-1}] where K == len(axis) and
+ *               d_{axis_k} == r_k
+ * \param axis The axis to normalize over.
+ * \param epsilon The epsilon value to avoid division by zero.
+ * \param name The name of the operation.
+ * \param tag The tag to mark the operation.
+ * \return The normalized tensor, with the same shape as data.
+ */
+inline Tensor rms_norm(const Tensor& data, const Tensor& weight, const Array<Integer>& axis,

Review Comment:
   NOTE: the `bias` term is missing



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