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{#
# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements.  See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the "License"); you may not use this file except in compliance with
# the License.  You may obtain a copy of the License at
#
#    http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
-#}

  
    
      
        
          Submarine Usage
        
      
    
    
      
        You can execute the selected command by entering the parameters in the interface below.
        
          Submarine dashboard
        
      
    
  

  

  
    Launch Standalone Tensorflow Application:
    yarn jar path-to/hadoop-yarn-applications-submarine-3.2.0-SNAPSHOT.jar job run \
  --env DOCKER_JAVA_HOME=/usr/lib/jvm/java-8-openjdk-amd64/jre/ \
  --env DOCKER_HADOOP_HDFS_HOME=/hadoop-3.1.0 --name tf-job-001 \
  --docker_image  \
  --input_path hdfs://default/dataset/cifar-10-data  \
  --checkpoint_path hdfs://default/tmp/cifar-10-jobdir \
  --worker_resources memory=4G,vcores=2,gpu=2  \
  --worker_launch_cmd "python ... (Your training application cmd)" \
  --tensorboard # this will launch a companion tensorboard container for monitoring

  
  
    Launch Distributed Tensorflow Application:
    yarn jar hadoop-yarn-applications-submarine-${version}.jar job run \
 --name tf-job-001 --docker_image  \
 --input_path hdfs://default/dataset/cifar-10-data \
 --checkpoint_path hdfs://default/tmp/cifar-10-jobdir \
 --env DOCKER_JAVA_HOME=/usr/lib/jvm/java-8-openjdk-amd64/jre/ \
 --env DOCKER_HADOOP_HDFS_HOME=/hadoop-3.1.0 \
 --num_workers 2 \
 --worker_resources memory=8G,vcores=2,gpu=1 --worker_launch_cmd "cmd for worker ..." \
 --num_ps 2 \
 --ps_resources memory=4G,vcores=2,gpu=0 --ps_launch_cmd "cmd for ps"

  

  
    Commandline options
  
  
    
      
        
          
{% for item in COMMANDLINE_OPTIONS %}
              
{% endfor %}
            
            
              
                name
                value
              
            
            
                {{item.name}}
                
                  
                    {{item.description}}