/* 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.random;

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.TFloat32;
import org.tensorflow.types.TInt64;
import org.tensorflow.types.family.TType;

/**
 * Outputs random values from a truncated normal distribution.
 * <p>
 * The generated values follow a normal distribution with mean 0 and standard
 * deviation 1, except that values whose magnitude is more than 2 standard
 * deviations from the mean are dropped and re-picked.
 * 
 * @param <U> data type for {@code output()} output
 */
public final class StatefulTruncatedNormal<U extends TType> extends RawOp implements Operand<U> {
  
  /**
   * Factory method to create a class wrapping a new StatefulTruncatedNormal operation.
   * 
   * @param scope current scope
   * @param resource The handle of the resource variable that stores the state of the RNG.
   * @param algorithm The RNG algorithm.
   * @param shape The shape of the output tensor.
   * @param dtype The type of the output.
   * @return a new instance of StatefulTruncatedNormal
   */
  @Endpoint(describeByClass = true)
  public static <U extends TType> StatefulTruncatedNormal<U> create(Scope scope, Operand<?> resource, Operand<TInt64> algorithm, Operand<? extends TType> shape, Class<U> dtype) {
    OperationBuilder opBuilder = scope.env().opBuilder("StatefulTruncatedNormal", scope.makeOpName("StatefulTruncatedNormal"));
    opBuilder.addInput(resource.asOutput());
    opBuilder.addInput(algorithm.asOutput());
    opBuilder.addInput(shape.asOutput());
    opBuilder = scope.apply(opBuilder);
    opBuilder.setAttr("dtype", Operands.toDataType(dtype));
    return new StatefulTruncatedNormal<U>(opBuilder.build());
  }
  
  /**
   * Factory method to create a class wrapping a new StatefulTruncatedNormal operation using default output types.
   * 
   * @param scope current scope
   * @param resource The handle of the resource variable that stores the state of the RNG.
   * @param algorithm The RNG algorithm.
   * @param shape The shape of the output tensor.
   * @return a new instance of StatefulTruncatedNormal
   */
  @Endpoint(describeByClass = true)
  public static StatefulTruncatedNormal<TFloat32> create(Scope scope, Operand<?> resource, Operand<TInt64> algorithm, Operand<? extends TType> shape) {
    return create(scope, resource, algorithm, shape, TFloat32.class);
  }
  
  /**
   * Random values with specified shape.
   */
  public Output<U> output() {
    return output;
  }
  
  @Override
  public Output<U> asOutput() {
    return output;
  }
  
  /** The name of this op, as known by TensorFlow core engine */
  public static final String OP_NAME = "StatefulTruncatedNormal";
  
  private Output<U> output;
  
  private StatefulTruncatedNormal(Operation operation) {
    super(operation);
    int outputIdx = 0;
    output = operation.output(outputIdx++);
  }
}
