- sanjoy
# filesystem path
filesystem_path:
   - tensorflow/c/experimental/filesystem
# security path
security_path:
   - tensorflow/security
# words checklist
segfault_memory:
   - segfault
   - memory leaks
# assignees
filesystem_security_assignee:
   - mihaimaruseac
   
# Cuda Comment
cuda_comment: >
   From the template it looks like you are installing **TensorFlow** (TF) prebuilt binaries:

	Items []madmin.HealResultItem `json:"Items"`
}

// structure to hold state of all heal sequences in server memory
type allHealState struct {
	sync.RWMutex

	// map of heal path to heal sequence
	healSeqMap map[string]*healSequence // Indexed by endpoint
	// keep track of the healing status of disks in the memory
	//   false: the disk needs to be healed but no healing routine is started
	//    true: the disk is currently healing

   *
   * {@snippet :
   * Stream.of("foo", "quux", "banana", "elephant").collect(least(2, comparingInt(String::length)))
   * // returns {"foo", "quux"}
   * }
   *
   * <p>This {@code Collector} uses O(k) memory and takes expected time O(n) (worst-case O(n log
   * k)), as opposed to e.g. {@code Stream.sorted(comparator).limit(k)}, which currently takes O(n
   * log n) time and O(n) space.
   *

 * java.util.LinkedHashMap}. Generally speaking, this class reduces object allocation and memory
 * consumption at the price of moderately increased constant factors of CPU. Only use this class
 * when there is a specific reason to prioritize memory over CPU.
 *
 * @author Louis Wasserman
 */
@J2ktIncompatible // no support for access-order mode in LinkedHashMap delegate

limitations under the License.
==============================================================================*/
#ifndef TENSORFLOW_C_EAGER_ABSTRACT_CONTEXT_H_
#define TENSORFLOW_C_EAGER_ABSTRACT_CONTEXT_H_

#include <memory>

#include "tensorflow/c/eager/abstract_function.h"
#include "tensorflow/c/eager/abstract_operation.h"

namespace tensorflow {

// Abstract interface to a context.
//

 * lock, but also maximizes memory footprint. On the other extreme, one could use a single lock for
 * all tasks, which minimizes memory footprint but also minimizes concurrency. Instead of choosing
 * either of these extremes, {@code Striped} allows the user to trade between required concurrency
 * and memory footprint. For example, if a set of tasks are CPU-bound, one could easily create a

        /** File system errors (not found, access denied, etc.) */
        FILE_SYSTEM,
        /** Protocol errors (invalid message, unsupported operation, etc.) */
        PROTOCOL,
        /** Resource errors (out of memory, disk space, etc.) */
        RESOURCE,
        /** Configuration errors */
        CONFIGURATION,
        /** Transient errors that may succeed on retry */
        TRANSIENT,
        /** Unknown or unclassified errors */

        connection.connect();
        return connection;
    }

    @Override
    public RdmaMemoryRegion registerMemory(ByteBuffer buffer, EnumSet<RdmaAccess> access) throws IOException {
        // TCP doesn't need real memory registration
        return new TcpMemoryRegion(buffer, access);
    }

    @Override
    public String getProviderName() {
        return "TCP Fallback";
    }

    @Override

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

#ifndef TENSORFLOW_C_CHECKPOINT_READER_H_
#define TENSORFLOW_C_CHECKPOINT_READER_H_

#include <memory>
#include <string>

#include "tensorflow/c/tf_status_helper.h"
#include "tensorflow/core/framework/tensor_shape.h"
#include "tensorflow/core/platform/status.h"
#include "tensorflow/core/platform/types.h"

limitations under the License.
==============================================================================*/
#ifndef TENSORFLOW_C_EAGER_ABSTRACT_TENSOR_HANDLE_H_
#define TENSORFLOW_C_EAGER_ABSTRACT_TENSOR_HANDLE_H_

#include <memory>

#include "tensorflow/core/framework/full_type.pb.h"
#include "tensorflow/core/framework/tensor_shape.h"
#include "tensorflow/core/framework/types.pb.h"
#include "tensorflow/core/platform/refcount.h"