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.
//

        "//tensorflow/c/eager:tfe_op_internal",
        "//tensorflow/c/eager:tfe_tensorhandle_internal",
        "//tensorflow/core:framework",
        "//tensorflow/core:lib",
        "@com_google_absl//absl/memory",
        "@com_google_absl//absl/status",
        "@com_google_absl//absl/strings",
        "@com_google_absl//absl/types:optional",
        "@com_google_absl//absl/types:span",

 *       <i>deeply</i> immutable.
 * </ul>
 *
 * <h4>Performance notes</h4>
 *
 * <ul>
 *   <li>Implementations can be generally assumed to prioritize memory efficiency, then speed of
 *       access, and lastly speed of creation.
 *   <li>The {@code copyOf} methods will sometimes recognize that the actual copy operation is

 * 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

See the License for the specific language governing permissions and
limitations under the License.
==============================================================================*/

#include <limits.h>
#include <memory.h>
#include <stdio.h>
#include <stdlib.h>
#include <time.h>
#include <unistd.h>

#ifdef _WIN32
#include <process.h>
#endif

#include "tensorflow/c/c_api.h"
#include "tensorflow/c/c_api_experimental.h"

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"

import com.google.errorprone.annotations.CanIgnoreReturnValue;
import java.io.DataInput;
import java.io.IOException;
import javax.annotation.CheckForNull;

/**
 * An extension of {@code DataInput} for reading from in-memory byte arrays; its methods offer
 * identical functionality but do not throw {@link IOException}.
 *
 * <p><b>Warning:</b> The caller is responsible for not attempting to read past the end of the

- A maximum of 100M inside a single zip is allowed. However, a reasonable limit of 100,000 files inside a single ZIP archive is recommended for best performance and memory usage trade-off.

## Content-Type

 * }
 * public void testFooLeak() {
 *   GcFinalization.awaitClear(fooWeakRef());
 * }
 * }</pre>
 *
 * <p>This class cannot currently be used to test soft references, since this class does not try to
 * create the memory pressure required to cause soft references to be cleared.
 *
 * <p>This class only provides testing utilities. It is not designed for direct use in production or
 * for benchmarking.
 *
 * @author mike nonemacher