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This repository has been archived by the owner on Nov 16, 2019. It is now read-only.
--driver-library-path "${CAFFE_ON_SPARK}/caffe-grid/target/caffe-grid-0.1-SNAPSHOT-jar-with-dependencies.jar"
--driver-class-path "${CAFFE_ON_SPARK}/caffe-grid/target/caffe-grid-0.1-SNAPSHOT-jar-with-dependencies.jar"
--conf spark.driver.extraLibraryPath="${LD_LIBRARY_PATH}"
--py-files ${CAFFE_ON_SPARK}/caffe-grid/target/caffeonsparkpythonapi.zip
--files ${CAFFE_ON_SPARK}/data/caffe/caffe.so
--jars "${CAFFE_ON_SPARK}/caffe-grid/target/caffe-grid-0.1-SNAPSHOT-jar-with-dependencies.jar"
Python 2.7.5 (default, Nov 6 2016, 00:28:07)
[GCC 4.8.5 20150623 (Red Hat 4.8.5-11)] on linux2
Type "help", "copyright", "credits" or "license" for more information.
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/usr/hdp/2.6.4.0-91/CaffeOnSpark/caffe-grid/target/caffe-grid-0.1-SNAPSHOT-jar-with-dependencies.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/usr/hdp/2.6.4.0-91/spark2/jars/slf4j-log4j12-1.7.16.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation.
SLF4J: Actual binding is of type [org.slf4j.impl.Log4jLoggerFactory]
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).
19/03/01 11:12:53 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
19/03/01 11:12:55 WARN DomainSocketFactory: The short-circuit local reads feature cannot be used because libhadoop cannot be loaded.
Welcome to
____ __
/ / ___ / / \ / _ / _ `/ __/ '/
/ / ._/_,// //_\ version 2.2.0.2.6.4.0-91
/_/
Using Python version 2.7.5 (default, Nov 6 2016 00:28:07)
SparkSession available as 'spark'.
from pyspark import SparkConf,SparkContext
from com.yahoo.ml.caffe.RegisterContext import registerContext,registerSQLContext
from com.yahoo.ml.caffe.CaffeOnSpark import CaffeOnSpark
from com.yahoo.ml.caffe.Config import Config
from com.yahoo.ml.caffe.DataSource import DataSource
from pyspark.mllib.linalg import Vectors
from pyspark.mllib.regression import LabeledPoint
from pyspark.mllib.linalg import Vectors
from pyspark.mllib.classification import LogisticRegressionWithLBFGS
registerContext(sc)
registerSQLContext(sqlContext)
cos=CaffeOnSpark(sc)
cfg=Config(sc)
cfg.protoFile='/usr/hdp/2.6.4.0-91/CaffeOnSpark/data/lenet_memory_solver.prototxt'
Attribute protoFile not valid
cfg.protoFile='/user/root/lenet_memory_solver.prototxt'
Attribute protoFile not valid
I dont know why the protofile is not valid
The text was updated successfully, but these errors were encountered:
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[root@node93 ~]# pyspark --master yarn \
Using Python version 2.7.5 (default, Nov 6 2016 00:28:07)
SparkSession available as 'spark'.
I dont know why the protofile is not valid
The text was updated successfully, but these errors were encountered: