public interface DependencyCoordinates extends ArtifactCoordinates {
    /**
     * {@return the type of the dependency}
     * A dependency can be a <abbr>JAR</abbr> file,
     * a modular-<abbr>JAR</abbr> if it is intended to be placed on the module-path,
     * a <abbr>JAR</abbr> containing test classes, <i>etc.</i>
     */
    @Nonnull
    Type getType();

    /**
     * {@return the time at which the dependency will be used}

// library are platform-specific and are not documented here.
//
// On success, returns the newly created library handle and places OK in status.
// The caller owns the library handle.
//
// On failure, returns nullptr and places an error status in status.
TF_CAPI_EXPORT extern TF_Library* TF_LoadPluggableDeviceLibrary(
    const char* library_filename, TF_Status* status);

@Experimental
@Immutable
public interface Dependency extends Artifact {
    /**
     * {@return the type of the dependency}
     * A dependency can be a <abbr>JAR</abbr> file,
     * a modular-<abbr>JAR</abbr> if it is intended to be placed on the module-path,
     * a <abbr>JAR</abbr> containing test classes, <i>etc.</i>
     *
     * @see DependencyCoordinates#getType()
     */
    @Nonnull
    Type getType();

    /**

namespace tensorflow {
namespace parallel_device {

// Allocate a parallel device named `device_name` which forwards operations to
// `underlying_devices`, maintaining "parallel tensors" with components placed
// on each underlying device.
//
// For example if `device_name` is
//   "/job:localhost/replica:0/task:0/device:CUSTOM:0"
// and `underlying_devices` is
//   {"/job:localhost/replica:0/task:0/device:GPU:0",

     * we did list an exclusion on c, it was only from within the context of
     * project b.  We will pick up project c in this case because no
     * restrictions were placed on d.  This demonstrates that a, b, c, & d will
     * all be collected.
     *
     * @throws Exception
     */
    @Test

| xlVersion | [4]byte     | `'1', ' ', ' ', ' '`
| xlMetaV2  | msgp object | All versions as single messagepack object
| [EOF] | |

### v1.1+

Version 1.1 added inline data, which will be placed after the metadata.

Therefore, the metadata is wrapped as a binary array for easy skipping.

| Entry          | Encoding       | Content
| ---------------|----------------|----------------------------------------

# Header Parameter Models

If you have a group of related **header parameters**, you can create a **Pydantic model** to declare them.

This would allow you to **re-use the model** in **multiple places** and also to declare validations and metadata for all the parameters at once. 😎

/// note

This is supported since FastAPI version `0.115.0`. 🤓

///

## Header Parameters with a Pydantic Model

   * it is returned directly. Otherwise, a new array of size {@code minLength + padding} is
   * returned, containing the values of {@code array}, and zeroes in the remaining places.
   *
   * @param array the source array
   * @param minLength the minimum length the returned array must guarantee
   * @param padding an extra amount to "grow" the array by if growth is necessary

   * it is returned directly. Otherwise, a new array of size {@code minLength + padding} is
   * returned, containing the values of {@code array}, and zeroes in the remaining places.
   *
   * @param array the source array
   * @param minLength the minimum length the returned array must guarantee
   * @param padding an extra amount to "grow" the array by if growth is necessary

   * it is returned directly. Otherwise, a new array of size {@code minLength + padding} is
   * returned, containing the values of {@code array}, and zeroes in the remaining places.
   *
   * @param array the source array
   * @param minLength the minimum length the returned array must guarantee
   * @param padding an extra amount to "grow" the array by if growth is necessary