- family-names: Mané
    given-names: Dan
  - family-names: Schuster
    given-names: Mike
  - family-names: Monga
    given-names: Rajat
  - family-names: Moore
    given-names: Sherry
  - family-names: Murray
    given-names: Derek
  - family-names: Olah
    given-names: Chris
  - family-names: Shlens
    given-names: Jonathon
  - family-names: Steiner
    given-names: Benoit
  - family-names: Sutskever

11:54:59 N 1 -73.860214233398438 40.729549407958984 -73.982475280761719 40.75054931640625 1 7.40 25 0 0.5 0 0 25.5 1 196 170 green 0.00 0.0 0.0 54 40 8.05 1287 717.01 4 Queens 071701 4071701 I QN18 Rego Park 4108 1885 82 1 Manhattan 008200 1008200 I MN20 Murray Hill-Kips Bay 3808 3389316 2 2014-03-24 12:55:16 2014-03-24 12:59:11 N 1 -73.860298156738281 40.729576110839844 -73.852508544921875 40.729724884033203 6 0.99 5 0 0.5 0 0 5.5 2 1 196 95 green 0.00 0.0 0.0 35 21 6.71 1287 717.01 4 Queens 071701 4071701...

limitations under the License.
==============================================================================*/

// This file is MACHINE GENERATED! Do not edit.

#ifndef TENSORFLOW_C_EXPERIMENTAL_OPS_ARRAY_OPS_H_
#define TENSORFLOW_C_EXPERIMENTAL_OPS_ARRAY_OPS_H_

#include "tensorflow/c/eager/abstract_context.h"
#include "tensorflow/c/eager/abstract_tensor_handle.h"

namespace tensorflow {
namespace ops {

#ifndef TENSORFLOW_C_EXPERIMENTAL_GRADIENTS_ARRAY_GRAD_H_
#define TENSORFLOW_C_EXPERIMENTAL_GRADIENTS_ARRAY_GRAD_H_

#include "tensorflow/c/eager/gradients.h"

namespace tensorflow {
namespace gradients {
GradientFunction* IdentityNRegisterer(const ForwardOperation& op);
}  // namespace gradients
}  // namespace tensorflow

See the License for the specific language governing permissions and
limitations under the License.
==============================================================================*/
#include "tensorflow/c/experimental/gradients/array_grad.h"

#include "tensorflow/c/eager/abstract_context.h"

namespace tensorflow {
namespace gradients {
namespace {
class IdentityNGradientFunction : public GradientFunction {
 public:

limitations under the License.
==============================================================================*/

// This file is MACHINE GENERATED! Do not edit.

#include "tensorflow/c/experimental/ops/array_ops.h"

#include "tensorflow/c/eager/abstract_context.h"
#include "tensorflow/c/eager/abstract_tensor_handle.h"
#include "tensorflow/c/eager/tracing_utils.h"
#include "tensorflow/core/framework/types.h"

#include "tensorflow/c/experimental/gradients/array_grad.h"

#include "tensorflow/c/eager/c_api_test_util.h"
#include "tensorflow/c/eager/c_api_unified_experimental_internal.h"
#include "tensorflow/c/eager/unified_api_testutil.h"
#include "tensorflow/c/experimental/gradients/grad_test_helper.h"
#include "tensorflow/c/experimental/gradients/tape/tape_context.h"
#include "tensorflow/c/experimental/ops/array_ops.h"
#include "tensorflow/c/tf_status_helper.h"

typedef jobject jclass;
typedef jobject jthrowable;
typedef jobject jstring;
typedef jobject jarray;
typedef jarray jbooleanArray;
typedef jarray jbyteArray;
typedef jarray jcharArray;
typedef jarray jshortArray;
typedef jarray jintArray;
typedef jarray jlongArray;
typedef jarray jfloatArray;
typedef jarray jdoubleArray;
typedef jarray jobjectArray;

typedef jobject jweak;

    checkArgument(array.length > 0);
    char min = array[0];
    for (int i = 1; i < array.length; i++) {
      if (array[i] < min) {
        min = array[i];
      }
    }
    return min;
  }

  /**
   * Returns the greatest value present in {@code array}.
   *
   * @param array a <i>nonempty</i> array of {@code char} values

    Arrays.sort(array, fromIndex, toIndex);
    reverse(array, fromIndex, toIndex);
  }

  /**
   * Reverses the elements of {@code array}. This is equivalent to {@code
   * Collections.reverse(Doubles.asList(array))}, but is likely to be more efficient.
   *
   * @since 23.1
   */
  public static void reverse(double[] array) {
    checkNotNull(array);
    reverse(array, 0, array.length);
  }