| #!/bin/bash |
| |
| MXNET_ROOT=$(cd "$(dirname $0)/../../.."; pwd) |
| CLASS_PATH=$MXNET_ROOT/scala-package/assembly/linux-x86_64-gpu/target/*:$MXNET_ROOT/scala-package/examples/target/*:$MXNET_ROOT/scala-package/examples/target/classes/lib/* |
| |
| # which gpu card to use, -1 means cpu |
| GPU=$1 |
| # the mr dataset path, you should put the pos and neg file in the same folder |
| MR_DATASET_PATH=$2 |
| # the trained word2vec file path, binary or text format |
| W2V_FILE_PATH=$3 |
| # whether the format of the word2vec file is binary,1 means binary, 0 means text |
| W2V_FORMAT_BIN=$4 |
| BATCH_SIZE=$5 |
| SAVE_MODEL_PATH=$6 |
| |
| java -Xmx8G -cp $CLASS_PATH \ |
| ml.dmlc.mxnetexamples.cnntextclassification.CNNTextClassification \ |
| --gpu $GPU \ |
| --mr-dataset-path $MR_DATASET_PATH \ |
| --w2v-file-path $W2V_FILE_PATH \ |
| --w2v-format-bin $W2V_FORMAT_BIN \ |
| --batch-size $BATCH_SIZE \ |
| --save-model-path $SAVE_MODEL_PATH |
