aaronmarkham commented on a change in pull request #14891: [Doc] Add MKL-DNN operator list URL: https://github.com/apache/incubator-mxnet/pull/14891#discussion_r281781454
########## File path: docs/tutorials/mkldnn/operator_list.md ########## @@ -0,0 +1,77 @@ +<!--- 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. --> + +# MKL-DNN Operator list + +MXNet MKL-DNN backend provides optimized implementations for various opertors covering a broad range of applications including image classification, object detection, natural language processing. We also provide the lower precision version for part of these operators on CPU leveraging the DL Boost technology from Intel. On computation graph level, a set of graph fusion pass and quantization pass is implemneted based on the sugraph feature of MXNet. To help users understanding MKL-DNN backend better, the tables below summarize the list of supported operators, data types and functionalities. As the community keeps working on more new features for MKL-DNN backend, the tables will be updated continuously. Review comment: ```suggestion MXNet MKL-DNN backend provides optimized implementations for various operators covering a broad range of applications including image classification, object detection, natural language processing. To help users understanding MKL-DNN backend better, the following table summarizes the list of supported operators, data types and functionalities. A subset of operators support faster training and inference by using a lower precision version. Refer to the following table's `INT8 Inference` column to see which operators are supported. ``` I think the implementation details should go in the index/readme page. ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: [email protected] With regards, Apache Git Services
