lindong28 commented on a change in pull request #4:
URL: https://github.com/apache/flink-ml/pull/4#discussion_r715591990
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File path: flink-ml-api/src/main/java/org/apache/flink/ml/api/core/Pipeline.java
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@@ -19,241 +19,101 @@
package org.apache.flink.ml.api.core;
import org.apache.flink.annotation.PublicEvolving;
+import org.apache.flink.annotation.VisibleForTesting;
import org.apache.flink.ml.api.misc.param.Params;
+import org.apache.flink.ml.api.pipeline.PipelineModel;
import org.apache.flink.table.api.Table;
-import org.apache.flink.table.api.TableEnvironment;
-import org.apache.flink.util.InstantiationUtil;
-
-import
org.apache.flink.shaded.jackson2.com.fasterxml.jackson.core.JsonProcessingException;
-import
org.apache.flink.shaded.jackson2.com.fasterxml.jackson.databind.ObjectMapper;
import java.io.IOException;
import java.util.ArrayList;
import java.util.Collections;
-import java.util.HashMap;
import java.util.List;
-import java.util.Map;
/**
- * A pipeline is a linear workflow which chains {@link Estimator}s and {@link
Transformer}s to
- * execute an algorithm.
- *
- * <p>A pipeline itself can either act as an Estimator or a Transformer,
depending on the stages it
- * includes. More specifically:
- *
- * <ul>
- * <li>If a Pipeline has an {@link Estimator}, one needs to call {@link
- * Pipeline#fit(TableEnvironment, Table)} before use the pipeline as a
{@link Transformer} .
- * In this case the Pipeline is an {@link Estimator} and can produce a
Pipeline as a {@link
- * Model}.
- * <li>If a Pipeline has no {@link Estimator}, it is a {@link Transformer}
and can be applied to a
- * Table directly. In this case, {@link Pipeline#fit(TableEnvironment,
Table)} will simply
- * return the pipeline itself.
- * </ul>
- *
- * <p>In addition, a pipeline can also be used as a {@link PipelineStage} in
another pipeline, just
- * like an ordinary {@link Estimator} or {@link Transformer} as describe above.
+ * A Pipeline acts as an Estimator. It consists of an ordered list of stages,
each of which could be
+ * an Estimator, Model, Transformer or AlgoOperator.
*/
@PublicEvolving
-public final class Pipeline
- implements Estimator<Pipeline, Pipeline>, Transformer<Pipeline>,
Model<Pipeline> {
- private static final long serialVersionUID = 1L;
- private final List<PipelineStage> stages = new ArrayList<>();
+public final class Pipeline implements Estimator<Pipeline, PipelineModel> {
+ private static final long serialVersionUID = 6384850154817512318L;
+ private final List<Stage<?>> stages;
private final Params params = new Params();
- private int lastEstimatorIndex = -1;
-
- public Pipeline() {}
-
- public Pipeline(String pipelineJson) {
- this.loadJson(pipelineJson);
- }
-
- public Pipeline(List<PipelineStage> stages) {
- for (PipelineStage s : stages) {
- appendStage(s);
- }
- }
-
- // is the stage a simple Estimator or pipeline with Estimator
- private static boolean isStageNeedFit(PipelineStage stage) {
- return (stage instanceof Pipeline && ((Pipeline) stage).needFit())
- || (!(stage instanceof Pipeline) && stage instanceof
Estimator);
+ public Pipeline(List<Stage<?>> stages) {
+ this.stages = stages;
}
/**
- * Appends a PipelineStage to the tail of this pipeline. Pipeline is
editable only via this
- * method. The PipelineStage must be Estimator, Transformer, Model or
Pipeline.
+ * Trains the pipeline to fit on the given tables.
*
- * @param stage the stage to be appended
- */
- public Pipeline appendStage(PipelineStage stage) {
- if (isStageNeedFit(stage)) {
- lastEstimatorIndex = stages.size();
- } else if (!(stage instanceof Transformer)) {
- throw new RuntimeException(
- "All PipelineStages should be Estimator or Transformer,
got:"
- + stage.getClass().getSimpleName());
- }
- stages.add(stage);
- return this;
- }
-
- /**
- * Returns a list of all stages in this pipeline in order, the list is
immutable.
- *
- * @return an immutable list of all stages in this pipeline in order.
- */
- public List<PipelineStage> getStages() {
- return Collections.unmodifiableList(stages);
- }
-
- /**
- * Check whether the pipeline acts as an {@link Estimator} or not. When
the return value is
- * true, that means this pipeline contains an {@link Estimator} and thus
users must invoke
- * {@link #fit(TableEnvironment, Table)} before they can use this pipeline
as a {@link
- * Transformer}. Otherwise, the pipeline can be used as a {@link
Transformer} directly.
- *
- * @return {@code true} if this pipeline has an Estimator, {@code false}
otherwise
- */
- public boolean needFit() {
- return this.getIndexOfLastEstimator() >= 0;
- }
-
- public Params getParams() {
- return params;
- }
-
- // find the last Estimator or Pipeline that needs fit in stages, -1 stand
for no Estimator in
- // Pipeline
- private int getIndexOfLastEstimator() {
- return lastEstimatorIndex;
- }
-
- /**
- * Train the pipeline to fit on the records in the given {@link Table}.
- *
- * <p>This method go through all the {@link PipelineStage}s in order and
does the following on
- * each stage until the last {@link Estimator}(inclusive).
+ * <p>This method goes through all stages of this pipeline in order and
does the following on
+ * each stage until the last Estimator (inclusive).
*
* <ul>
- * <li>If a stage is an {@link Estimator}, invoke {@link
Estimator#fit(TableEnvironment,
- * Table)} with the input table to generate a {@link Model},
transform the the input table
- * with the generated {@link Model} to get a result table, then pass
the result table to
- * the next stage as input.
- * <li>If a stage is a {@link Transformer}, invoke {@link
- * Transformer#transform(TableEnvironment, Table)} on the input
table to get a result
- * table, and pass the result table to the next stage as input.
+ * <li>If a stage is an Estimator, invoke {@link
Estimator#fit(Table...)} with the input
+ * tables to generate a Model, transform the the input tables with
the generated Model to
+ * get result tables, then pass the result tables to the next stage
as inputs.
+ * <li>If a stage is an AlgoOperator, invoke {@link
AlgoOperator#transform(Table...)} on the
+ * input tables to get result tables, and pass the result tables to
the next stage as
+ * inputs.
* </ul>
*
- * <p>After all the {@link Estimator}s are trained to fit their input
tables, a new pipeline
- * will be created with the same stages in this pipeline, except that all
the Estimators in the
- * new pipeline are replaced with their corresponding Models generated in
the above process.
- *
- * <p>If there is no {@link Estimator} in the pipeline, the method returns
a copy of this
- * pipeline.
+ * <p>After all the Estimators are trained to fit their input tables, a
new PipelineModel will
+ * be created with the same stages in this pipeline, except that all the
Estimators in the
+ * PipelineModel are replaced with the models generated in the above
process.
*
- * @param tEnv the table environment to which the input table is bound.
- * @param input the table with records to train the Pipeline.
- * @return a pipeline with same stages as this Pipeline except all
Estimators replaced with
- * their corresponding Models.
+ * @param inputs a list of tables
+ * @return a PipelineModel
*/
@Override
- public Pipeline fit(TableEnvironment tEnv, Table input) {
- List<PipelineStage> transformStages = new ArrayList<>(stages.size());
- int lastEstimatorIdx = getIndexOfLastEstimator();
+ public PipelineModel fit(Table... inputs) {
+ List<Stage<?>> modelStages = new ArrayList<>(stages.size());
+ int lastEstimatorIdx = -1;
+ for (int i = 0; i < stages.size(); i++) {
+ if (stages.get(i) instanceof Estimator) {
+ lastEstimatorIdx = i;
+ }
+ }
+
for (int i = 0; i < stages.size(); i++) {
- PipelineStage s = stages.get(i);
+ Stage<?> s = stages.get(i);
if (i <= lastEstimatorIdx) {
- Transformer t;
- boolean needFit = isStageNeedFit(s);
- if (needFit) {
- t = ((Estimator) s).fit(tEnv, input);
+ AlgoOperator<?> t;
+ if (s instanceof Estimator<?, ?>) {
+ t = ((Estimator<?, ?>) s).fit(inputs);
} else {
- // stage is Transformer, guaranteed in appendStage() method
- t = (Transformer) s;
+ t = (AlgoOperator<?>) s;
}
- transformStages.add(t);
- input = t.transform(tEnv, input);
+ modelStages.add(t);
+ inputs = t.transform(inputs);
Review comment:
Thanks for catching this. Both the code and the Java doc has been
updated accordingly.
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