Using the command $XLEARNING_HOME/bin/xl-submit
to submit the application to Cluster at the XLearning client. Please see the example in the part of README Quick Start. The following is more details of the parameter.
Property Name | Meaning |
---|---|
app-name | application name |
app-type | application type, default as the "XLearning", can set as "TensorFlow", "Caffe" according to the deeplearning framework |
input | input file path in the format of "the HDFS path"#"local path" |
output | output file path in the format of "the HDFS path"#"local path" |
files | the required local files of the application |
cacheArchive | the required compressed files in the HDFS path |
cacheFile | the required files in the HDFS path |
launch-cmd | execute command |
user-path | the append for the environment variable $PATH |
jars | the required jar files |
user-classpath-first | whether user job jar should be the first one on class path or not, default as the configure of xlearning.user.classpath.first |
conf | set the configuration |
am-cores | number of cores to use for the AM process, default as the configure of xlearning.am.cores |
am-memory | amount of memory to use for the AM process (in MB),default as the configure of xlearning.am.memory |
ps-num | number of ps containers to use for the application, default as the configure of xlearning.ps.num |
ps-cores | number of cores to use for the ps process, default as the configure of xlearning.ps.cores |
ps-memory | amount of memory to use for the ps process (in MB), default as the configure of xlearning.ps.memory |
worker-num | number of worker containers to use for the application, default as the configure of xlearning.worker.num |
worker-cores | number of cores to use for the worker process, default as the configure of xlearning.worker.cores |
worker-memory | amount of memory to use for the worker process(in MB), default as the configure of xlearning.worker.memory |
chiefworker-memory | amount of memory for the chief worker, especially for the index 0 worker of the TensorFlow application, default as the worker-memory |
evaluatorworker-memory | amount of memory for the estimator worker, especially for the TensorFlow Estimator application, default as the worker-memory |
queue | the queue of application submitted to, default as the configure of xlearning.app.queue |
priority | the priority of application, default as the configure of xlearning.app.priority |
board-enable | whether to start the service of Board, default as the configure of xlearning.tf.board.enable |
board-index | specify the index of worker which start the Board, default as the configure of xlearning.tf.board.worker.index |
board-logdir | the directory save Board event log, default as the configure of xlearning.tf.board.log.dir |
board-reloadinterval | how often the backend should load more data of event log for tensorboard, default as the configure of xlearning.tf.board.reload.interval |
board-historydir | specify the HDFS path which the Board event log upload to, default as the configure of xlearning.tf.board.history.dir |
board-modelpb | model proto in ONNX format for VisualDL, default as the configure of xlearning.board.modelpb |
board-cacheTimeout | memory cache timeout duration in seconds for VisualDL,default as the configure of xlearning.board.cache.timeout |
input-strategy | the strategy of the input file, default as the configure of xlearning.input.strategy |
inRenameInputFile | whether to rename the download file when input-strategy is "DOWNLOAD", default as the configure of xlearning.inputfile.rename |
stream-epoch | specify the epoch num of the input file read when input-strategy is "STREAM", default as the configure of xlearning.stream.epoch |
inputformat | specify the class of the inputformat when input-strategy is "STREAM", default as the configure of xlearning.inputformat.class |
inputformat-shuffle | whether to shuffle the input splits when input-strategy is "STREAM", default as the configure of xlearning.input.stream.shuffle |
output-strategy | the strategy of the output file, default as the configure of xlearning.output.strategy |
outputformat | specify the class of outputformat when output-strategy is "STREAM", default as the configure of xlearning.outputformat.class |
tf-evaluator | whether to set the last worker as evaluator of distributed TensorFlow job type, default as the configure of xlearning.tf.evaluator |
output-index | specify the index of the worker which to upload the output, default upload the output of all the workers. |