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tools/aws_benchmarking/README.md

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@@ -54,6 +54,7 @@ Training nodes will run your `ENTRYPOINT` script with the following environment
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- `TRAINERS`: trainer count
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- `SERVER_ENDPOINT`: current server end point if the node role is a pserver
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- `TRAINER_INDEX`: an integer to identify the index of current trainer if the node role is a trainer.
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- `PADDLE_INIT_TRAINER_ID`: same as above
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Now we have a working distributed training script which takes advantage of node environment variables and docker file to generate the training image. Run the following command:
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@@ -81,8 +82,7 @@ putcn/paddle_aws_client \
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--action create \
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--key_name <your key pare name> \
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--security_group_id <your security group id> \
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--pserver_image_id <your pserver image id> \
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--trainer_image_id <your trainer images id> \
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--docker_image myreponame/paddle_benchmark \
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--pserver_count 2 \
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--trainer_count 2
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```
@@ -146,7 +146,7 @@ When the training is finished, pservers and trainers will be terminated. All the
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Master exposes 4 major services:
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- GET `/status`: return master log
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- GET `/list_logs`: return list of log file names
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- GET `/logs`: return list of log file names
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- GET `/log/<logfile name>`: return a particular log by log file name
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- POST `/cleanup`: teardown the whole setup
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