diff --git a/docs/lite/docs/source_en/tools/benchmark_train_tool.md b/docs/lite/docs/source_en/tools/benchmark_train_tool.md index f6c3a51e0411dde26c9092adffcba97667dfa0e5..75bd5a3e09476703fc66173c518ad391bfb5d64f 100644 --- a/docs/lite/docs/source_en/tools/benchmark_train_tool.md +++ b/docs/lite/docs/source_en/tools/benchmark_train_tool.md @@ -72,7 +72,7 @@ Model = test_benchmark.ms, numThreads = 1, MinRunTime = 72.228996 ms, MaxRuntime ./benchmark_train --modelFile=./models/test_benchmark.ms --epochs=10 --timeProfiling=true ``` -This command uses a random input, sets the parameter `timeProfiling` as true, times and other parameters use default values. After this command is executed, the statistics on the running time of the model at the network layer will be displayed as follows. In this case, the statistics are displayed by `opName` and `optype`. `opName` indicates the operator name, `optype` indicates the operator type, and `avg` indicates the average running time of the operator per single run, `percent` indicates the ratio of the operator running time to the total operator running time, `calledTimes` indicates the number of times that the operator is run, and `opTotalTime` indicates the total time that the operator is run for a specified number of times. Finally, `total time` and `kernel cost` show the average time consumed by a single inference operation of the model and the sum of the average time consumed by all operators in the model inference, respectively. +This command uses a random input, sets the parameter `timeProfiling` as true, times and other parameters use default values. After this command is executed, the statistics on the running time of the model at the network layer will be displayed as follows. In this case, the statistics are displayed by `opName` and `optype`. `opName` indicates the operator name, `optype` indicates the operator type, and `avg` indicates the average running time of the operator per single run, `percent` indicates the ratio of the operator running time to the total operator running time, `calledTimes` indicates the number of times that the operator is run, and `opTotalTime` indicates the total time that the operator is run for a specified number of times. Finally, `total time` and `kernel cost` show the average time consumed by a single training operation of the model and the sum of the average time consumed by all operators in the model training, respectively. ```text ----------------------------------------------------------------------------------------- diff --git a/docs/lite/docs/source_zh_cn/tools/benchmark_train_tool.md b/docs/lite/docs/source_zh_cn/tools/benchmark_train_tool.md index 365f098a6c343d4809ae08d0aab8dacf379628cb..f6a574bdcbcbea9a26cf87a53b15928a87a07fcf 100644 --- a/docs/lite/docs/source_zh_cn/tools/benchmark_train_tool.md +++ b/docs/lite/docs/source_zh_cn/tools/benchmark_train_tool.md @@ -72,7 +72,7 @@ Model = test_benchmark.ms, numThreads = 1, MinRunTime = 72.228996 ms, MaxRuntime ./benchmark_train --modelFile=./models/test_benchmark.ms --epochs=10 --timeProfiling=true ``` -这条命令使用随机输入，并且输出模型网络层的耗时信息，其他参数使用默认值。该命令执行后，模型网络层的耗时会输出如下统计信息，在该例中，该统计信息按照`opName`和`optype`两种划分方式分别显示，`opName`表示算子名，`optype`表示算子类别，`avg`表示该算子的平均单次运行时间，`percent`表示该算子运行耗时占所有算子运行总耗时的比例，`calledTimes`表示该算子的运行次数，`opTotalTime`表示该算子运行指定次数的总耗时。最后，`total time`和`kernel cost`分别显示了该模型单次推理的平均耗时和模型推理中所有算子的平均耗时之和。 +这条命令使用随机输入，并且输出模型网络层的耗时信息，其他参数使用默认值。该命令执行后，模型网络层的耗时会输出如下统计信息，在该例中，该统计信息按照`opName`和`optype`两种划分方式分别显示，`opName`表示算子名，`optype`表示算子类别，`avg`表示该算子的平均单次运行时间，`percent`表示该算子运行耗时占所有算子运行总耗时的比例，`calledTimes`表示该算子的运行次数，`opTotalTime`表示该算子运行指定次数的总耗时。最后，`total time`和`kernel cost`分别显示了该模型单次训练的平均耗时和模型训练中所有算子的平均耗时之和。 ```text -----------------------------------------------------------------------------------------