gistfile1.txt

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sitory/aopalliance/aopalliance/1.0/aopalliance-1.0.jar:/home/andreas/.m2/repository/org/springframework/spring-beans/3.1.2.RELEASE/spring-beans-3.1.2.RELEASE.jar:/home/andreas/.m2/repository/org/springframework/spring-expression/3.1.2.RELEASE/spring-expression-3.1.2.RELEASE.jar:/home/andreas/.m2/repository/org/cleartk/cleartk-type-system/2.0.0/cleartk-type-system-2.0.0.jar:/home/andreas/.m2/repository/org/cleartk/cleartk-opennlp-tools/2.0.0/cleartk-opennlp-tools-2.0.0.jar:/home/andreas/.m2/repository/org/apache/opennlp/opennlp-maxent/3.0.3/opennlp-maxent-3.0.3.jar:/home/andreas/.m2/repository/org/apache/opennlp/opennlp-tools/1.5.3/opennlp-tools-1.5.3.jar:/home/andreas/.m2/repository/net/sf/jwordnet/jwnl/1.3.3/jwnl-1.3.3.jar:/home/andreas/.m2/repository/org/apache/opennlp/opennlp-uima/1.5.3/opennlp-uima-1.5.3.jar:/home/andreas/.m2/repository/io/dropwizard/dropwizard-assets/0.8.0/dropwizard-assets-0.8.0.jar:/home/andreas/.m2/repository/io/dropwizard/dropwizard-views-mustache/0.8.0/dropwizard-views-mustache-0.8.0.jar:/home/andreas/.m2/repository/io/dropwizard/dropwizard-views/0.8.0/dropwizard-views-0.8.0.jar:/home/andreas/.m2/repository/com/github/spullara/mustache/java/compiler/0.8.17/compiler-0.8.17.jar:/home/andreas/.m2/repository/io/dropwizard/dropwizard-views-freemarker/0.8.0/dropwizard-views-freemarker-0.8.0.jar:/home/andreas/.m2/repository/org/freemarker/freemarker/2.3.21/freemarker-2.3.21.jar:/home/andreas/.m2/repository/org/nd4j/nd4j-jackson/0.4-rc3.9-SNAPSHOT/nd4j-jackson-0.4-rc3.9-SNAPSHOT.jar:/home/andreas/.m2/repository/org/nd4j/nd4j-api/0.4-rc3.9-SNAPSHOT/nd4j-api-0.4-rc3.9-SNAPSHOT.jar:/home/andreas/.m2/repository/io/netty/netty-buffer/4.0.28.Final/netty-buffer-4.0.28.Final.jar:/home/andreas/.m2/repository/io/netty/netty-common/4.0.28.Final/netty-common-4.0.28.Final.jar:/home/andreas/.m2/repository/org/nd4j/canova-api/0.0.0.15-SNAPSHOT/canova-api-0.0.0.15-20160419.015546-121.jar:/home/andreas/.m2/repository/org/apache/commons/commons-compress/1.8/commons-compress-1.8.jar:/home/andreas/.m2/repository/org/nd4j/canova-nd4j-image/0.0.0.14/canova-nd4j-image-0.0.0.14.jar:/home/andreas/.m2/repository/org/tukaani/xz/1.5/xz-1.5.jar:/home/andreas/.m2/repository/org/projectlombok/lombok/1.16.4/lombok-1.16.4.jar:/home/andreas/.m2/repository/org/nd4j/nd4j-buffer/0.4-rc3.9-SNAPSHOT/nd4j-buffer-0.4-rc3.9-SNAPSHOT.jar:/home/andreas/.m2/repository/org/nd4j/nd4j-common/0.4-rc3.9-SNAPSHOT/nd4j-common-0.4-rc3.9-SNAPSHOT.jar:/home/andreas/.m2/repository/org/reflections/reflections/0.9.10/reflections-0.9.10.jar:/home/andreas/.m2/repository/com/google/code/findbugs/annotations/2.0.1/annotations-2.0.1.jar:/home/andreas/.m2/repository/org/nd4j/nd4j-context/0.4-rc3.9-SNAPSHOT/nd4j-context-0.4-rc3.9-SNAPSHOT.jar:/home/andreas/.m2/repository/org/bytedeco/javacpp/1.2-SNAPSHOT/javacpp-1.2-20160417.144017-9.jar:/home/andreas/.m2/repository/org/yaml/snakeyaml/1.12/snakeyaml-1.12.jar:/home/andreas/.m2/repository/org/deeplearning4j/deeplearning4j-ui/0.4-rc3.9-SNAPSHOT/deeplearning4j-ui-0.4-rc3.9-20160417.234034-521.jar:/home/andreas/.m2/repository/io/dropwizard/dropwizard-client/0.8.0/dropwizard-client-0.8.0.jar:/home/andreas/.m2/repository/org/glassfish/hk2/hk2-utils/2.4.0-b09/hk2-utils-2.4.0-b09.jar:/home/andreas/.m2/repository/org/glassfish/hk2/external/aopalliance-repackaged/2.4.0-b09/aopalliance-repackaged-2.4.0-b09.jar:/home/andreas/.m2/repository/io/dropwizard/metrics/metrics-httpclient/3.1.0/metrics-httpclient-3.1.0.jar:/home/andreas/.m2/repository/org/apache/httpcomponents/httpclient/4.3.5/httpclient-4.3.5.jar:/home/andreas/.m2/repository/org/apache/httpcomponents/httpcore/4.3.2/httpcore-4.3.2.jar:/home/andreas/.m2/repository/org/glassfish/jersey/connectors/jersey-apache-connector/2.16/jersey-apache-connector-2.16.jar:/home/andreas/.m2/repository/io/dropwizard/dropwizard-forms/0.8.0/dropwizard-forms-0.8.0.jar:/home/andreas/.m2/repository/org/glassfish/jersey/media/jersey-media-multipart/2.16/jersey-media-multipart-2.16.jar:/home/andreas/.m2/repository/org/glassfish/jersey/bundles/repackaged/jersey-guava/2.16/jersey-guava-2.16.jar:/home/andreas/.m2/repository/org/jvnet/mimepull/mimepull/1.9.3/mimepull-1.9.3.jar:/home/andreas/.m2/repository/org/nd4j/nd4j-cuda-7.5/0.4-rc3.9-SNAPSHOT/nd4j-cuda-7.5-0.4-rc3.9-SNAPSHOT.jar:/home/andreas/.m2/repository/org/apache/commons/commons-pool2/2.4.2/commons-pool2-2.4.2.jar:/home/andreas/.m2/repository/org/nd4j/nd4j-native-api/0.4-rc3.9-SNAPSHOT/nd4j-native-api-0.4-rc3.9-SNAPSHOT.jar:/home/andreas/.m2/repository/org/nd4j/canova-nd4j-common/0.0.0.14/canova-nd4j-common-0.0.0.14.jar:/home/andreas/.m2/repository/org/nd4j/canova-data-image/0.0.0.14/canova-data-image-0.0.0.14.jar:/home/andreas/.m2/repository/com/github/jai-imageio/jai-imageio-core/1.3.0/jai-imageio-core-1.3.0.jar:/home/andreas/.m2/repository/com/twelvemonkeys/imageio/imageio-jpeg/3.1.1/imageio-jpeg-3.1.1.jar:/home/andreas/.m2/repository/com/twelvemonkeys/imageio/imageio-core/3.1.1/imageio-core-3.1.1.jar:/home/andreas/.m2/repository/com/twelvemonkeys/common/common-lang/3.1.1/common-lang-3.1.1.jar:/home/andreas/.m2/repository/com/twelvemonkeys/common/common-io/3.1.1/common-io-3.1.1.jar:/home/andreas/.m2/repository/com/twelvemonkeys/common/common-image/3.1.1/common-image-3.1.1.jar:/home/andreas/.m2/repository/com/twelvemonkeys/imageio/imageio-metadata/3.1.1/imageio-metadata-3.1.1.jar:/home/andreas/.m2/repository/com/twelvemonkeys/imageio/imageio-tiff/3.1.1/imageio-tiff-3.1.1.jar:/home/andreas/.m2/repository/com/twelvemonkeys/imageio/imageio-psd/3.1.1/imageio-psd-3.1.1.jar:/home/andreas/.m2/repository/com/twelvemonkeys/imageio/imageio-bmp/3.1.1/imageio-bmp-3.1.1.jar:/home/andreas/.m2/repository/org/nd4j/canova-nd4j-codec/0.0.0.14/canova-nd4j-codec-0.0.0.14.jar:/home/andreas/.m2/repository/org/jcodec/jcodec/0.1.5/jcodec-0.1.5.jar:/home/andreas/.m2/repository/jfree/jfreechart/1.0.13/jfreechart-1.0.13.jar:/home/andreas/.m2/repository/jfree/jcommon/1.0.16/jcommon-1.0.16.jar:/home/andreas/.m2/repository/junit/junit/4.12/junit-4.12.jar:/home/andreas/.m2/repository/org/hamcrest/hamcrest-core/1.3/hamcrest-core-1.3.jar:/home/andreas/programs/IntelliJ/lib/idea_rt.jar com.intellij.rt.execution.application.AppMain org.deeplearning4j.examples.convolution.LenetMnistExample
o.d.e.c.LenetMnistExample - Load data....


o.d.e.c.LenetMnistExample - Build model....
o.n.j.c.CudaEnvironment - Devices found: 1
o.n.j.a.i.AtomicAllocator - Starting device GC for device: 0
o.n.j.a.c.ContextPool - Creating new context...
o.n.j.a.c.ContextPool - Creating new stream for device [0]...
o.n.j.a.c.ContextPool - Creating new cuBLAS handle for device [0]...
o.n.j.a.c.ContextPool - Creating new stream for device [0]...
o.d.e.c.LenetMnistExample - Train model....
Setting max grid size to [8]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
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Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
Kernel h: [2], w: [2]; Col h: [4], w: [4]; Stride x: [2], y: [2]; Height: [8], Width: [8], Depth: [50], N: [204800], Samples: [64]
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CUDA error at /home/andreas/development/dl4j/libnd4j/blas/cuda/NativeOps.cu:1531 code=77(<unknown>) "cudaStreamSynchronize(*stream)" 
Exception in thread "main" java.lang.RuntimeException: Can't allocate [HOST] memory: 32
	at org.nd4j.jita.memory.impl.CudaDirectProvider.malloc(CudaDirectProvider.java:54)
	at org.nd4j.jita.handler.impl.CudaZeroHandler.alloc(CudaZeroHandler.java:153)
	at org.nd4j.jita.allocator.impl.AtomicAllocator.allocateMemory(AtomicAllocator.java:344)
	at org.nd4j.jita.allocator.impl.AtomicAllocator.allocateMemory(AtomicAllocator.java:320)
	at org.nd4j.linalg.jcublas.buffer.BaseCudaDataBuffer.<init>(BaseCudaDataBuffer.java:146)
	at org.nd4j.linalg.jcublas.buffer.CudaIntDataBuffer.<init>(CudaIntDataBuffer.java:41)
	at org.nd4j.linalg.jcublas.buffer.CudaIntDataBuffer.<init>(CudaIntDataBuffer.java:57)
	at org.nd4j.linalg.jcublas.buffer.factory.CudaDataBufferFactory.createInt(CudaDataBufferFactory.java:246)
	at org.nd4j.linalg.factory.Nd4j.createBuffer(Nd4j.java:1143)
	at org.nd4j.linalg.api.shape.Shape.createShapeInformation(Shape.java:1367)
	at org.nd4j.linalg.api.ndarray.BaseNDArray.<init>(BaseNDArray.java:335)
	at org.nd4j.linalg.api.ndarray.BaseNDArray.<init>(BaseNDArray.java:577)
	at org.nd4j.linalg.jcublas.JCublasNDArray.<init>(JCublasNDArray.java:283)
	at org.nd4j.linalg.jcublas.JCublasNDArrayFactory.create(JCublasNDArrayFactory.java:300)
	at org.nd4j.linalg.factory.BaseNDArrayFactory.create(BaseNDArrayFactory.java:1304)
	at org.nd4j.linalg.factory.Nd4j.create(Nd4j.java:2794)
	at org.nd4j.linalg.factory.BaseNDArrayFactory.valueArrayOf(BaseNDArrayFactory.java:880)
	at org.nd4j.linalg.factory.Nd4j.valueArrayOf(Nd4j.java:4148)
	at org.nd4j.linalg.jcublas.ops.executioner.JCudaExecutioner.exec(JCudaExecutioner.java:144)
	at org.nd4j.linalg.api.ndarray.BaseNDArray.sum(BaseNDArray.java:3372)
	at org.deeplearning4j.nn.layers.convolution.ConvolutionLayer.backpropGradient(ConvolutionLayer.java:99)
	at org.deeplearning4j.nn.multilayer.MultiLayerNetwork.calcBackpropGradients(MultiLayerNetwork.java:1093)
	at org.deeplearning4j.nn.multilayer.MultiLayerNetwork.backprop(MultiLayerNetwork.java:1028)
	at org.deeplearning4j.nn.multilayer.MultiLayerNetwork.computeGradientAndScore(MultiLayerNetwork.java:1689)
	at org.deeplearning4j.optimize.solvers.BaseOptimizer.gradientAndScore(BaseOptimizer.java:152)
	at org.deeplearning4j.optimize.solvers.StochasticGradientDescent.optimize(StochasticGradientDescent.java:56)
	at org.deeplearning4j.optimize.Solver.optimize(Solver.java:51)
	at org.deeplearning4j.nn.multilayer.MultiLayerNetwork.fit(MultiLayerNetwork.java:1018)
	at org.deeplearning4j.examples.convolution.LenetMnistExample.main(LenetMnistExample.java:91)
	at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
	at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
	at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
	at java.lang.reflect.Method.invoke(Method.java:498)
	at com.intellij.rt.execution.application.AppMain.main(AppMain.java:144)