/* Copyright 2018 The TensorFlow Authors. 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.
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.
=======================================================================*/

// This class has been generated, DO NOT EDIT!

package org.tensorflow.op.data;

import java.util.Arrays;
import java.util.List;
import org.tensorflow.ConcreteFunction;
import org.tensorflow.GraphOperation;
import org.tensorflow.Operand;
import org.tensorflow.Operation;
import org.tensorflow.OperationBuilder;
import org.tensorflow.Output;
import org.tensorflow.ndarray.Shape;
import org.tensorflow.op.Operands;
import org.tensorflow.op.RawOp;
import org.tensorflow.op.RawOpInputs;
import org.tensorflow.op.Scope;
import org.tensorflow.op.annotation.Endpoint;
import org.tensorflow.op.annotation.OpInputsMetadata;
import org.tensorflow.op.annotation.OpMetadata;
import org.tensorflow.op.annotation.Operator;
import org.tensorflow.proto.framework.DataType;
import org.tensorflow.types.family.TType;

/**
 * Creates a dataset containing elements of {@code input_dataset} matching {@code predicate}.
 * The {@code predicate} function must return a scalar boolean and accept the
 * following arguments:
 * <ul>
 * <li>One tensor for each component of an element of {@code input_dataset}.</li>
 * <li>One tensor for each value in {@code other_arguments}.</li>
 * </ul>
 */
@OpMetadata(
    opType = FilterDataset.OP_NAME,
    inputsClass = FilterDataset.Inputs.class
)
@Operator(
    group = "data"
)
public final class FilterDataset extends RawOp implements Operand<TType> {
  /**
   * The name of this op, as known by TensorFlow core engine
   */
  public static final String OP_NAME = "FilterDataset";

  private Output<? extends TType> handle;

  @SuppressWarnings("unchecked")
  public FilterDataset(Operation operation) {
    super(operation, OP_NAME);
    int outputIdx = 0;
    handle = operation.output(outputIdx++);
  }

  /**
   * Factory method to create a class wrapping a new FilterDataset operation.
   *
   * @param scope current scope
   * @param inputDataset The inputDataset value
   * @param otherArguments A list of tensors, typically values that were captured when
   * building a closure for {@code predicate}.
   * @param predicate A function returning a scalar boolean.
   * @param outputTypes The value of the outputTypes attribute
   * @param outputShapes The value of the outputShapes attribute
   * @param options carries optional attribute values
   * @return a new instance of FilterDataset
   */
  @Endpoint(
      describeByClass = true
  )
  public static FilterDataset create(Scope scope, Operand<? extends TType> inputDataset,
      Iterable<Operand<?>> otherArguments, ConcreteFunction predicate,
      List<Class<? extends TType>> outputTypes, List<Shape> outputShapes, Options... options) {
    OperationBuilder opBuilder = scope.opBuilder(OP_NAME, "FilterDataset");
    opBuilder.addInput(inputDataset.asOutput());
    opBuilder.addInputList(Operands.asOutputs(otherArguments));
    opBuilder.setAttr("predicate", predicate);
    opBuilder.setAttr("output_types", Operands.toDataTypes(outputTypes));
    Shape[] outputShapesArray = new Shape[outputShapes.size()];
    for (int i = 0 ; i < outputShapesArray.length ; i++) {
      outputShapesArray[i] = outputShapes.get(i);
    }
    opBuilder.setAttr("output_shapes", outputShapesArray);
    if (options != null) {
      for (Options opts : options) {
        if (opts.metadata != null) {
          opBuilder.setAttr("metadata", opts.metadata);
        }
      }
    }
    return new FilterDataset(opBuilder.build());
  }

  /**
   * Sets the metadata option.
   *
   * @param metadata the metadata option
   * @return this Options instance.
   */
  public static Options metadata(String metadata) {
    return new Options().metadata(metadata);
  }

  /**
   * Gets handle.
   *
   * @return handle.
   */
  public Output<? extends TType> handle() {
    return handle;
  }

  @Override
  @SuppressWarnings("unchecked")
  public Output<TType> asOutput() {
    return (Output<TType>) handle;
  }

  /**
   * Optional attributes for {@link org.tensorflow.op.data.FilterDataset}
   */
  public static class Options {
    private String metadata;

    private Options() {
    }

    /**
     * Sets the metadata option.
     *
     * @param metadata the metadata option
     * @return this Options instance.
     */
    public Options metadata(String metadata) {
      this.metadata = metadata;
      return this;
    }
  }

  @OpInputsMetadata(
      outputsClass = FilterDataset.class
  )
  public static class Inputs extends RawOpInputs<FilterDataset> {
    /**
     * The inputDataset input
     */
    public final Operand<? extends TType> inputDataset;

    /**
     * A list of tensors, typically values that were captured when
     * building a closure for {@code predicate}.
     */
    public final Iterable<Operand<?>> otherArguments;

    /**
     * The Targuments attribute
     */
    public final DataType[] Targuments;

    /**
     * The outputTypes attribute
     */
    public final DataType[] outputTypes;

    /**
     * The outputShapes attribute
     */
    public final Shape[] outputShapes;

    /**
     * The metadata attribute
     */
    public final String metadata;

    public Inputs(GraphOperation op) {
      super(new FilterDataset(op), op, Arrays.asList("Targuments", "output_types", "output_shapes", "metadata"));
      int inputIndex = 0;
      inputDataset = (Operand<? extends TType>) op.input(inputIndex++);
      int otherArgumentsLength = op.inputListLength("other_arguments");
      otherArguments = Arrays.asList((Operand<?>[]) op.inputList(inputIndex, otherArgumentsLength));
      inputIndex += otherArgumentsLength;
      Targuments = op.attributes().getAttrTypeList("Targuments");
      outputTypes = op.attributes().getAttrTypeList("output_types");
      outputShapes = op.attributes().getAttrShapeList("output_shapes");
      metadata = op.attributes().getAttrString("metadata");
    }
  }
}
