com.johnsnowlabs.ml.tensorflow.SentenceGrouper.scala Maven / Gradle / Ivy
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/*
* Copyright 2017-2022 John Snow Labs
*
* 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.johnsnowlabs.ml.tensorflow
import scala.collection.mutable.ArrayBuffer
import scala.reflect.ClassTag
case class SentenceGrouper[T: ClassTag](
getLength: T => Int,
sizes: Array[Int] = Array(5, 10, 20, 50)) {
def getBucketId(len: Int): Int = {
for (i <- 0 until sizes.length) {
if (len <= sizes(i))
return i
}
sizes.length
}
def slice(source: TraversableOnce[T], batchSize: Int = 32): Iterator[Array[T]] = {
val buckets = Array.fill(sizes.length + 1)(ArrayBuffer.empty[T])
val batches = source.toIterator.flatMap { item =>
val length = getLength(item)
val bucketId = getBucketId(length)
buckets(bucketId).append(item)
if (buckets(bucketId).length >= batchSize) {
val result = buckets(bucketId).toArray
buckets(bucketId).clear()
Some(result)
} else {
None
}
}
val rest = buckets.toIterator.filter(b => b.nonEmpty).map(b => b.toArray)
batches ++ rest
}
}