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[spark] Integrate HuggingFace tokenizer (#2311)
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96 changes: 96 additions & 0 deletions
96
extensions/spark/src/main/scala/ai/djl/spark/task/text/HuggingFaceTextDecoder.scala
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,96 @@ | ||
| /* | ||
| * Copyright 2023 Amazon.com, Inc. or its affiliates. All Rights Reserved. | ||
| * | ||
| * Licensed under the Apache License, Version 2.0 (the "License"). You may not use this file except in compliance | ||
| * with the License. A copy of the License is located at | ||
| * | ||
| * http://aws.amazon.com/apache2.0/ | ||
| * | ||
| * or in the "license" file accompanying this file. This file 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 ai.djl.spark.task.text | ||
|
|
||
| import ai.djl.huggingface.tokenizers.HuggingFaceTokenizer | ||
| import org.apache.spark.ml.param.Param | ||
| import org.apache.spark.ml.param.shared.{HasInputCol, HasOutputCol} | ||
| import org.apache.spark.ml.util.Identifiable | ||
| import org.apache.spark.sql.types.{ArrayType, LongType, StringType, StructField, StructType} | ||
| import org.apache.spark.sql.{DataFrame, Dataset, Row} | ||
|
|
||
| /** | ||
| * TextDecoder performs text decoding using HuggingFace tokenizers in Spark. | ||
| * | ||
| * @param uid An immutable unique ID for the object and its derivatives. | ||
| */ | ||
| class HuggingFaceTextDecoder(override val uid: String) extends TextPredictor[Array[Long], String] | ||
| with HasInputCol with HasOutputCol { | ||
|
|
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| def this() = this(Identifiable.randomUID("HuggingFaceTextDecoder")) | ||
|
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| final val name = new Param[String](this, "name", "The name of the tokenizer") | ||
|
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| private var inputColIndex : Int = _ | ||
|
|
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| /** | ||
| * Sets the inputCol parameter. | ||
| * | ||
| * @param value the value of the parameter | ||
| */ | ||
| def setInputCol(value: String): this.type = set(inputCol, value) | ||
|
|
||
| /** | ||
| * Sets the outputCol parameter. | ||
| * | ||
| * @param value the value of the parameter | ||
| */ | ||
| def setOutputCol(value: String): this.type = set(outputCol, value) | ||
|
|
||
| /** | ||
| * Sets the name parameter. | ||
| * | ||
| * @param value the value of the parameter | ||
| */ | ||
| def setName(value: String): this.type = set(name, value) | ||
|
|
||
| setDefault(inputClass, classOf[Array[Long]]) | ||
| setDefault(outputClass, classOf[String]) | ||
|
|
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| /** | ||
| * Decodes String from the input ids on the provided dataset. | ||
| * | ||
| * @param dataset input dataset | ||
| * @return output dataset | ||
| */ | ||
| def decode(dataset: Dataset[_]): DataFrame = { | ||
| transform(dataset) | ||
| } | ||
|
|
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| /** @inheritdoc */ | ||
| override def transform(dataset: Dataset[_]): DataFrame = { | ||
| inputColIndex = dataset.schema.fieldIndex($(inputCol)) | ||
| super.transform(dataset) | ||
| } | ||
|
|
||
| /** @inheritdoc */ | ||
| override def transformRows(iter: Iterator[Row]): Iterator[Row] = { | ||
| val tokenizer = HuggingFaceTokenizer.newInstance($(name)) | ||
| iter.map(row => { | ||
| Row.fromSeq(row.toSeq ++ Array[Any](tokenizer.decode(row.getAs[Seq[Long]]($(inputCol)).toArray))) | ||
| }) | ||
| } | ||
|
|
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| /** @inheritdoc */ | ||
| override def transformSchema(schema: StructType): StructType = { | ||
| validateInputType(schema($(inputCol))) | ||
| val outputSchema = StructType(schema.fields ++ | ||
| Array(StructField($(outputCol), StringType))) | ||
| outputSchema | ||
| } | ||
|
|
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| override def validateInputType(input: StructField): Unit = { | ||
| require(input.dataType == ArrayType(LongType), | ||
| s"Input column ${input.name} type must be ArrayType but got ${input.dataType}.") | ||
| } | ||
| } |
95 changes: 95 additions & 0 deletions
95
extensions/spark/src/main/scala/ai/djl/spark/task/text/HuggingFaceTextEncoder.scala
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,95 @@ | ||
| /* | ||
| * Copyright 2023 Amazon.com, Inc. or its affiliates. All Rights Reserved. | ||
| * | ||
| * Licensed under the Apache License, Version 2.0 (the "License"). You may not use this file except in compliance | ||
| * with the License. A copy of the License is located at | ||
| * | ||
| * http://aws.amazon.com/apache2.0/ | ||
| * | ||
| * or in the "license" file accompanying this file. This file 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 ai.djl.spark.task.text | ||
|
|
||
| import ai.djl.huggingface.tokenizers.{Encoding, HuggingFaceTokenizer} | ||
| import org.apache.spark.ml.param.Param | ||
| import org.apache.spark.ml.param.shared.{HasInputCol, HasOutputCol} | ||
| import org.apache.spark.ml.util.Identifiable | ||
| import org.apache.spark.sql.types.{ArrayType, LongType, StructField, StructType} | ||
| import org.apache.spark.sql.{DataFrame, Dataset, Row} | ||
|
|
||
| /** | ||
| * TextEncoder performs text encoding using HuggingFace tokenizers in Spark. | ||
| * | ||
| * @param uid An immutable unique ID for the object and its derivatives. | ||
| */ | ||
| class HuggingFaceTextEncoder(override val uid: String) extends TextPredictor[String, Encoding] | ||
| with HasInputCol with HasOutputCol { | ||
|
|
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| def this() = this(Identifiable.randomUID("HuggingFaceTextEncoder")) | ||
|
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| final val name = new Param[String](this, "name", "The name of the tokenizer") | ||
|
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| private var inputColIndex : Int = _ | ||
|
|
||
| /** | ||
| * Sets the inputCol parameter. | ||
| * | ||
| * @param value the value of the parameter | ||
| */ | ||
| def setInputCol(value: String): this.type = set(inputCol, value) | ||
|
|
||
| /** | ||
| * Sets the outputCol parameter. | ||
| * | ||
| * @param value the value of the parameter | ||
| */ | ||
| def setOutputCol(value: String): this.type = set(outputCol, value) | ||
|
|
||
| /** | ||
| * Sets the name parameter. | ||
| * | ||
| * @param value the value of the parameter | ||
| */ | ||
| def setName(value: String): this.type = set(name, value) | ||
|
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| setDefault(inputClass, classOf[String]) | ||
| setDefault(outputClass, classOf[Encoding]) | ||
|
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| /** | ||
| * Performs sentence encoding on the provided dataset. | ||
| * | ||
| * @param dataset input dataset | ||
| * @return output dataset | ||
| */ | ||
| def encode(dataset: Dataset[_]): DataFrame = { | ||
| transform(dataset) | ||
| } | ||
|
|
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| /** @inheritdoc */ | ||
| override def transform(dataset: Dataset[_]): DataFrame = { | ||
| inputColIndex = dataset.schema.fieldIndex($(inputCol)) | ||
| super.transform(dataset) | ||
| } | ||
|
|
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| /** @inheritdoc */ | ||
| override def transformRows(iter: Iterator[Row]): Iterator[Row] = { | ||
| val tokenizer = HuggingFaceTokenizer.newInstance($(name)) | ||
| iter.map(row => { | ||
| val encoding = tokenizer.encode(row.getString(inputColIndex)) | ||
| Row.fromSeq(row.toSeq | ||
| ++ Array[Any](Row(encoding.getIds, encoding.getTypeIds, encoding.getAttentionMask))) | ||
| }) | ||
| } | ||
|
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| /** @inheritdoc */ | ||
| override def transformSchema(schema: StructType): StructType = { | ||
| validateInputType(schema($(inputCol))) | ||
| val outputSchema = StructType(schema.fields ++ | ||
| Array(StructField($(outputCol), StructType(Seq(StructField("ids", ArrayType(LongType)), | ||
| StructField("type_ids", ArrayType(LongType)), | ||
| StructField("attention_mask", ArrayType(LongType))))))) | ||
| outputSchema | ||
| } | ||
| } |
91 changes: 91 additions & 0 deletions
91
extensions/spark/src/main/scala/ai/djl/spark/task/text/HuggingFaceTextTokenizer.scala
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,91 @@ | ||
| /* | ||
| * Copyright 2023 Amazon.com, Inc. or its affiliates. All Rights Reserved. | ||
| * | ||
| * Licensed under the Apache License, Version 2.0 (the "License"). You may not use this file except in compliance | ||
| * with the License. A copy of the License is located at | ||
| * | ||
| * http://aws.amazon.com/apache2.0/ | ||
| * | ||
| * or in the "license" file accompanying this file. This file 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 ai.djl.spark.task.text | ||
|
|
||
| import ai.djl.huggingface.tokenizers.HuggingFaceTokenizer | ||
| import org.apache.spark.ml.param.Param | ||
| import org.apache.spark.ml.param.shared.{HasInputCol, HasOutputCol} | ||
| import org.apache.spark.ml.util.Identifiable | ||
| import org.apache.spark.sql.types.{ArrayType, StringType, StructField, StructType} | ||
| import org.apache.spark.sql.{DataFrame, Dataset, Row} | ||
|
|
||
| /** | ||
| * TextTokenizer performs text tokenization using HuggingFace tokenizers in Spark. | ||
| * | ||
| * @param uid An immutable unique ID for the object and its derivatives. | ||
| */ | ||
| class HuggingFaceTextTokenizer(override val uid: String) extends TextPredictor[String, Array[String]] | ||
| with HasInputCol with HasOutputCol { | ||
|
|
||
| def this() = this(Identifiable.randomUID("HuggingFaceTextTokenizer")) | ||
|
|
||
| final val name = new Param[String](this, "name", "The name of the tokenizer") | ||
|
|
||
| private var inputColIndex : Int = _ | ||
|
|
||
| /** | ||
| * Sets the inputCol parameter. | ||
| * | ||
| * @param value the value of the parameter | ||
| */ | ||
| def setInputCol(value: String): this.type = set(inputCol, value) | ||
|
|
||
| /** | ||
| * Sets the outputCol parameter. | ||
| * | ||
| * @param value the value of the parameter | ||
| */ | ||
| def setOutputCol(value: String): this.type = set(outputCol, value) | ||
|
|
||
| /** | ||
| * Sets the name parameter. | ||
| * | ||
| * @param value the value of the parameter | ||
| */ | ||
| def setName(value: String): this.type = set(name, value) | ||
|
|
||
| setDefault(inputClass, classOf[String]) | ||
| setDefault(outputClass, classOf[Array[String]]) | ||
|
|
||
| /** | ||
| * Performs sentence tokenization on the provided dataset. | ||
| * | ||
| * @param dataset input dataset | ||
| * @return output dataset | ||
| */ | ||
| def tokenize(dataset: Dataset[_]): DataFrame = { | ||
| transform(dataset) | ||
| } | ||
|
|
||
| /** @inheritdoc */ | ||
| override def transform(dataset: Dataset[_]): DataFrame = { | ||
| inputColIndex = dataset.schema.fieldIndex($(inputCol)) | ||
| super.transform(dataset) | ||
| } | ||
|
|
||
| /** @inheritdoc */ | ||
| override def transformRows(iter: Iterator[Row]): Iterator[Row] = { | ||
| val tokenizer = HuggingFaceTokenizer.newInstance($(name)) | ||
| iter.map(row => { | ||
| Row.fromSeq(row.toSeq ++ Array[Any](tokenizer.tokenize(row.getString(inputColIndex)).toArray)) | ||
| }) | ||
| } | ||
|
|
||
| /** @inheritdoc */ | ||
| override def transformSchema(schema: StructType): StructType = { | ||
| validateInputType(schema($(inputCol))) | ||
| val outputSchema = StructType(schema.fields ++ | ||
| Array(StructField($(outputCol), ArrayType(StringType)))) | ||
| outputSchema | ||
| } | ||
| } |
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