adding client and docker files

tools/aws_benchmarking/client/Dockerfile

@@ -0,0 +1,7 @@
+FROM python:2.7.14-stretch
+
+ENV HOME /root
+COPY ./ /root/
+WORKDIR /root
+RUN pip install -r /root/requirements.txt
+ENTRYPOINT ["python", "cluster_launcher.py"]

tools/aws_benchmarking/client/requirements.txt

@@ -0,0 +1,6 @@
+netaddr==0.7.19
+boto3==1.6.21
+namesgenerator==0.3
+paramiko==2.4.1
+scp
+requests

tools/aws_benchmarking/pserver.sh.template

@@ -1,2 +0,0 @@
-#!/bin/bash
-nvidia-docker run -p {PSERVER_PORT}:{PSERVER_PORT} -e "TRAINING_ROLE=PSERVER"  -e "PSERVER_HOSTS={PSERVER_HOSTS}" {DOCKER_IMAGE}

tools/aws_benchmarking/server/Dockerfile

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+# A image for building paddle binaries
+# Use cuda devel base image for both cpu and gpu environment
+FROM python:2.7.14-stretch
+
+ENV HOME /root
+# Add bash enhancements
+COPY ./ /root/
+WORKDIR /root
+RUN pip install -r /root/requirements.txt
+ENTRYPOINT ["python", "cluster_master.py"]

tools/aws_benchmarking/server/pserver.sh.template

@@ -0,0 +1,2 @@
+#!/bin/bash
+nvidia-docker run -p {PSERVER_PORT}:{PSERVER_PORT} -e "MASTER_ENDPOINT={MASTER_ENDPOINT}" -e "TASK_NAME={TASK_NAME}" -e "TRAINING_ROLE=PSERVER"  -e "PSERVER_HOSTS={PSERVER_HOSTS}" {DOCKER_IMAGE}

tools/aws_benchmarking/server/trainer.sh.template

@@ -0,0 +1,2 @@
+#!/bin/bash 
+nvidia-docker run  -e "MASTER_ENDPOINT={MASTER_ENDPOINT}" -e "TASK_NAME={TASK_NAME}" -e "TRAINER_INDEX={TRAINER_INDEX}" -e "TRAINING_ROLE=TRAINER"  -e "PSERVER_HOSTS={PSERVER_HOSTS}" {DOCKER_IMAGE}

tools/aws_benchmarking/trainer.sh.template

@@ -1,2 +0,0 @@
-#!/bin/bash 
-nvidia-docker run -e "TRAINER_INDEX={TRAINER_INDEX}" -e "TRAINING_ROLE=TRAINER"  -e "PSERVER_HOSTS={PSERVER_HOSTS}" {DOCKER_IMAGE}