com.intel.analytics.bigdl.example.textclassification.TextClassifier.scala Maven / Gradle / Ivy

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/*
 * Copyright 2016 The BigDL Authors.
 *
 * Licensed 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.
 */

package com.intel.analytics.bigdl.example.textclassification

import com.intel.analytics.bigdl.example.utils._
import com.intel.analytics.bigdl.nn.{ClassNLLCriterion, _}
import com.intel.analytics.bigdl.utils.{Engine, LoggerFilter, T}
import org.apache.log4j.{Level => Levle4j, Logger => Logger4j}
import org.slf4j.{Logger, LoggerFactory}
import scopt.OptionParser

import scala.collection.mutable.{ArrayBuffer, Map => MMap}
import scala.language.existentials

object TextClassifier {
  val log: Logger = LoggerFactory.getLogger(this.getClass)
  LoggerFilter.redirectSparkInfoLogs()
  Logger4j.getLogger("com.intel.analytics.bigdl.optim").setLevel(Levle4j.INFO)

  def main(args: Array[String]): Unit = {
    val localParser = new OptionParser[TextClassificationParams]("BigDL Example") {
      opt[String]('b', "baseDir")
        .required()
        .text("Base dir containing the training and word2Vec data")
        .action((x, c) => c.copy(baseDir = x))
      opt[String]('p', "partitionNum")
        .text("you may want to tune the partitionNum if run into spark mode")
        .action((x, c) => c.copy(partitionNum = x.toInt))
      opt[String]('s', "maxSequenceLength")
        .text("maxSequenceLength")
        .action((x, c) => c.copy(maxSequenceLength = x.toInt))
      opt[String]('w', "maxWordsNum")
        .text("maxWordsNum")
        .action((x, c) => c.copy(maxWordsNum = x.toInt))
      opt[String]('l', "trainingSplit")
        .text("trainingSplit")
        .action((x, c) => c.copy(trainingSplit = x.toDouble))
      opt[String]('z', "batchSize")
        .text("batchSize")
        .action((x, c) => c.copy(batchSize = x.toInt))
      opt[Int]('l', "learningRate")
        .text("learningRate")
        .action((x, c) => c.copy(learningRate = x))
    }

    localParser.parse(args, TextClassificationParams()).map { param =>
      log.info(s"Current parameters: $param")
      val textClassification = new TextClassifier(param)
      textClassification.train()
    }
  }
}