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