* 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

//
// Returns a TF_Buffer. The memory pointed to by the result is owned by
// lib_handle. The data in the buffer will be the serialized OpList proto for
// ops defined in the library.
TF_CAPI_EXPORT extern TF_Buffer TF_GetOpList(TF_Library* lib_handle);

// Frees the memory associated with the library handle.
// Does NOT unload the library.

 * 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

  # social:
  # Other plugins
  macros:
    include_yaml:
    - external_links: ../en/data/external_links.yml
    - github_sponsors: ../en/data/github_sponsors.yml
    - people: ../en/data/people.yml
    - members: ../en/data/members.yml
    - sponsors_badge: ../en/data/sponsors_badge.yml
    - sponsors: ../en/data/sponsors.yml
  redirects:
    redirect_maps:
      deployment/deta.md: deployment/cloud.md

                String.format(Locale.ROOT, "Caught an exception in %s.  Shutting down.", t),
                e);
      } catch (Throwable errorInLogging) { // sneaky checked exception
        // If logging fails, e.g. due to missing memory, at least try to log the
        // message and the cause for the failed logging.
        System.err.println(e.getMessage());
        System.err.println(errorInLogging.getMessage());
      } finally {
        runtime.exit(1);

# ADR-0002 - Avoid using Java serialization

## Date

2012-12-01

## Context

In Gradle we often need to serialize in-memory objects for caching, or to transmit them across process barriers, etc.
Java serialization is one way to implement this, however, despite its simplicity of implementation, it has several drawbacks:

- **Performance:**
Java's built-in serialization mechanism is often slower compared to other serialization solutions.

  public abstract HashCode hashBytes(byte[] input, int off, int len);

  @Override
  public HashCode hashBytes(ByteBuffer input) {
    return newHasher(input.remaining()).putBytes(input).hash();
  }

  /** In-memory stream-based implementation of Hasher. */
  private final class BufferingHasher extends AbstractHasher {
    final ExposedByteArrayOutputStream stream;

    BufferingHasher(int expectedInputSize) {

Each <code>DATA</code> directive initializes a section of the
corresponding memory.
The memory not explicitly initialized is zeroed.
The general form of the <code>DATA</code> directive is

<pre>
DATA	symbol+offset(SB)/width, value
</pre>

<p>
which initializes the symbol memory at the given offset and width with the given value.

import static org.apache.maven.api.services.BaseRequest.nonNull;

/**
 * Provides access to the contents of a source independently of the
 * backing store (e.g. file system, database, memory).
 * <p>
 * This is mainly used to parse files into objects such as
 * {@link org.apache.maven.api.Project},
 * {@link org.apache.maven.api.model.Model},
 * {@link org.apache.maven.api.settings.Settings}, or

//     in `input_shapes`.
//
// The results are returned in `output_shapes` and
// `output_resource_shapes_and_types`. The caller is responsible for freeing the
// memory in these buffers by calling `TF_DeleteShapeAndTypeList`.
TF_CAPI_EXPORT extern void TFE_InferShapes(
    TFE_Op* op, TF_ShapeAndTypeList* input_shapes, TF_Tensor** input_tensors,
    TF_ShapeAndTypeList* input_tensor_as_shapes,