AbstractTensorHandlePtr fMinus(f_outputs[0]);

    // Take Difference of both estimates: (f(theta + eps) - f(theta - eps)).
    TF_RETURN_IF_ERROR(
        ops::Sub(ctx, fPlus.get(), fMinus.get(), f_outputs, "sub_top"));
    AbstractTensorHandlePtr fDiff(f_outputs[0]);

    // Calculate using the difference quotient definition:
    // (f(theta + eps) - f(theta - eps)) / (2 * eps).
    TF_RETURN_IF_ERROR(

 * NetworkBuilder}.
 *
 * <p>This class maintains a map of nodes to {@link NetworkConnections}. This class also maintains a
 * map of edges to reference nodes. The reference node is defined to be the edge's source node on
 * directed graphs, and an arbitrary endpoint of the edge on undirected graphs.
 *

 * NetworkBuilder}.
 *
 * <p>This class maintains a map of nodes to {@link NetworkConnections}. This class also maintains a
 * map of edges to reference nodes. The reference node is defined to be the edge's source node on
 * directed graphs, and an arbitrary endpoint of the edge on undirected graphs.
 *

    #    ; UPDATE_USER       = $$AccessContext$$.getAccessUserOnThread()
    #}
}
# ----------------/
#

	// position to discover whether there is a blank before the parenthesis.
	// We only get here if defining a macro inside a macro.
	// This imperfect implementation means we cannot tell the difference between
	//	#define A #define B(x) x
	// and
	//	#define A #define B (x) x
	// The first definition of B has an argument, the second doesn't. Because we let

[Kubernetes version and version skew support policy]: https://kubernetes.io/docs/setup/release/version-skew-policy/#supported-versions

## Current Behavior
<!--- If describing a bug, tell us what happens instead of the expected behavior -->
<!--- If suggesting a change/improvement, explain the difference from current behavior -->

## Possible Solution
<!--- Not obligatory, but suggest a fix/reason for the bug, -->
<!--- or ideas how to implement the addition or change -->

## Steps to Reproduce (for bugs)

  }

  /**
   * Returns a new array of the given length with the same type as a reference array.
   *
   * @param reference any array of the desired type
   * @param length the length of the new array
   */
  public static <T extends @Nullable Object> T[] newArray(T[] reference, int length) {
    return Platform.newArray(reference, length);
  }

  /**

// original framework of destruction, and this context will be deleted also.
struct TfDlManagedTensorCtx {
  TensorReference reference;
  std::vector<int64_t> shape;
  std::vector<int64_t> strides;
  DLManagedTensor tensor;

  explicit TfDlManagedTensorCtx(const TensorReference& ref) : reference(ref) {}
};

// Gets tensor from eager tensor handle.
const Tensor* GetTensorFromHandle(TFE_TensorHandle* h, TF_Status* status) {

## Prerequisites

- Install MinIO - [MinIO Quickstart Guide](https://min.io/docs/minio/linux/index.html#procedure).
- [Use `mc` with MinIO Server](https://min.io/docs/minio/linux/reference/minio-mc.html#quickstart)

## Set bucket quota configuration

### Set a hard quota of 1GB for a bucket `mybucket` on MinIO object storage

```sh
mc admin bucket quota myminio/mybucket --hard 1gb
```