example/framework/scenario/tensorflow/ps/gpu/tensorflowdistributedtrainingwithdefaultscheduledgpu.yaml [40:67]:
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          containers:
          - name: tensorflow
            # Using official image to demonstrate this example.
            # The image contains and only contains tensorflow official code.
            image: frameworkcontroller/tensorflow-examples:gpu
            # For the tf_cnn_benchmarks usage, see
            # https://github.com/tensorflow/benchmarks/tree/master/scripts/tf_cnn_benchmarks
            workingDir: /tensorflow/benchmarks/scripts/tf_cnn_benchmarks
            # Using /mnt/frameworkbarrier/injector.sh to inject environment variables
            # without the need for image invasion and k8s DNS:
            # FB_{UpperCase({TaskRoleName})}_ADDRESSES=
            #   {Task[0].PodIP}:${FB_{UpperCase({TaskRoleName})}_PORT},...,
            #   {Task[TaskRole.TaskNumber-1].PodIP}:${FB_{UpperCase({TaskRoleName})}_PORT}
            # See more in ./example/framework/extension/frameworkbarrier.yaml
            command: [
            "sh", "-c",
            "FB_PS_PORT=4001 FB_WORKER_PORT=5001 . /mnt/frameworkbarrier/injector.sh &&
            python tf_cnn_benchmarks.py --job_name=ps --task_index=${FC_TASK_INDEX}
            --ps_hosts=${FB_PS_ADDRESSES} --worker_hosts=${FB_WORKER_ADDRESSES}
            --variable_update=parameter_server --cross_replica_sync=false
            --model=alexnet --batch_size=8 --num_batches=10
            --device=gpu --local_parameter_device=gpu --num_gpus=1 --data_format=NCHW
            --data_name=cifar10 --data_dir=/mnt/data/cifar-10-batches-py
            --train_dir=/mnt/data/${FC_FRAMEWORK_NAME}/output"]
            ports:
            - containerPort: 4001
            resources:
              limits:
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example/framework/scenario/tensorflow/ps/gpu/tensorflowdistributedtrainingwithhivedscheduledgpu.yaml [53:80]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
          containers:
          - name: tensorflow
            # Using official image to demonstrate this example.
            # The image contains and only contains tensorflow official code.
            image: frameworkcontroller/tensorflow-examples:gpu
            # For the tf_cnn_benchmarks usage, see
            # https://github.com/tensorflow/benchmarks/tree/master/scripts/tf_cnn_benchmarks
            workingDir: /tensorflow/benchmarks/scripts/tf_cnn_benchmarks
            # Using /mnt/frameworkbarrier/injector.sh to inject environment variables
            # without the need for image invasion and k8s DNS:
            # FB_{UpperCase({TaskRoleName})}_ADDRESSES=
            #   {Task[0].PodIP}:${FB_{UpperCase({TaskRoleName})}_PORT},...,
            #   {Task[TaskRole.TaskNumber-1].PodIP}:${FB_{UpperCase({TaskRoleName})}_PORT}
            # See more in ./example/framework/extension/frameworkbarrier.yaml
            command: [
            "sh", "-c",
            "FB_PS_PORT=4001 FB_WORKER_PORT=5001 . /mnt/frameworkbarrier/injector.sh &&
            python tf_cnn_benchmarks.py --job_name=ps --task_index=${FC_TASK_INDEX}
            --ps_hosts=${FB_PS_ADDRESSES} --worker_hosts=${FB_WORKER_ADDRESSES}
            --variable_update=parameter_server --cross_replica_sync=false
            --model=alexnet --batch_size=8 --num_batches=10
            --device=gpu --local_parameter_device=gpu --num_gpus=1 --data_format=NCHW
            --data_name=cifar10 --data_dir=/mnt/data/cifar-10-batches-py
            --train_dir=/mnt/data/${FC_FRAMEWORK_NAME}/output"]
            ports:
            - containerPort: 4001
            resources:
              limits:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -



