/* 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.ragged;

import org.tensorflow.Operand;
import org.tensorflow.Operation;
import org.tensorflow.OperationBuilder;
import org.tensorflow.Output;
import org.tensorflow.op.Operands;
import org.tensorflow.op.RawOp;
import org.tensorflow.op.Scope;
import org.tensorflow.op.annotation.Endpoint;
import org.tensorflow.op.annotation.Operator;
import org.tensorflow.types.family.TNumber;
import org.tensorflow.types.family.TType;

/**
 * Encodes a `RaggedTensor` into a `variant` Tensor.
 * <p>
 * 
 * Encodes the given `RaggedTensor` and returns a `variant` Tensor. If
 * `batched_input` is True, then input `RaggedTensor` is unbatched along the
 * zero-th dimension, each component `RaggedTensor` is encoded into a scalar
 * `variant` Tensor, and these are stacked to return a 1-D `variant` Tensor.
 * If `batched_input` is False, then the input `RaggedTensor` is encoded as is and
 * a scalar `variant` Tensor is returned. A `RaggedTensor` is encoded by first
 * creating a 1-D `variant` Tensor with `ragged_rank + 1` elements, containing the
 * splits and values Tensors of the `RaggedTensor`. Then the 1-D `variant` Tensor
 * is wrapped in a scalar `variant` Tensor. See `RaggedTensorFromVariant` for the
 * corresponding decoding logic.
 * 
 */
public final class RaggedTensorToVariant extends RawOp implements Operand<TType> {
  
  /**
   * Factory method to create a class wrapping a new RaggedTensorToVariant operation.
   * 
   * @param scope current scope
   * @param rtNestedSplits A list of one or more Tensors representing the splits of the input
   * `RaggedTensor`.
   * @param rtDenseValues A Tensor representing the values of the input `RaggedTensor`.
   * @param batchedInput A `bool` denoting whether the input is a batched `RaggedTensor`.
   * @return a new instance of RaggedTensorToVariant
   */
  @Endpoint(describeByClass = true)
  public static <T extends TNumber> RaggedTensorToVariant create(Scope scope, Iterable<Operand<T>> rtNestedSplits, Operand<? extends TType> rtDenseValues, Boolean batchedInput) {
    OperationBuilder opBuilder = scope.env().opBuilder("RaggedTensorToVariant", scope.makeOpName("RaggedTensorToVariant"));
    opBuilder.addInputList(Operands.asOutputs(rtNestedSplits));
    opBuilder.addInput(rtDenseValues.asOutput());
    opBuilder = scope.apply(opBuilder);
    opBuilder.setAttr("batched_input", batchedInput);
    return new RaggedTensorToVariant(opBuilder.build());
  }
  
  /**
   * A `variant` Tensor that containing encoded `RaggedTensor`.
   */
  public Output<?> encodedRagged() {
    return encodedRagged;
  }
  
  @Override
  @SuppressWarnings("unchecked")
  public Output<TType> asOutput() {
    return (Output<TType>) encodedRagged;
  }
  
  /** The name of this op, as known by TensorFlow core engine */
  public static final String OP_NAME = "RaggedTensorToVariant";
  
  private Output<?> encodedRagged;
  
  private RaggedTensorToVariant(Operation operation) {
    super(operation);
    int outputIdx = 0;
    encodedRagged = operation.output(outputIdx++);
  }
}
