u99127 commented on a change in pull request #4258: [WIP][TVM] Bring Your Own 
Codegen to TVM
URL: https://github.com/apache/incubator-tvm/pull/4258#discussion_r345448429
 
 

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 File path: tutorials/dev/custom_relay_backend.py
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 @@ -0,0 +1,291 @@
+# 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.
+"""
+
+.. _tutorial-custom-relay-backend
+
+Bring Your Own Codegen To TVM
+============================================
+**Author**: `Zhi Chen <https://github.com/zhiics>`_, `Cody Hao Yu 
<https:://github.com/comaniac>`_
+
+As the hardware devices targeted by deep learning workloads keep increasing, 
the required knowledge
+for users to achieve high performance on various devices keeps increasing as 
well. To free data
+scientists from worrying about the performance when developing a new model, 
hardware vendors either
+provide libraries such as MKLDNN or cuDNN with many commonly used deep 
learning operators,
+or provide frameworks such as TensorRT to let users describle their models in 
a certain way to
+achieve high performance. However, users have to learn a new programming 
interface when they
+attempt to work on a new libaray or device. As a result, the demand of a 
unified programming
 
 Review comment:
   libaray? should it be library ? 

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