TF_CAPI_EXPORT unsigned char TF_GetXlaConstantFoldingDisabled();
TF_CAPI_EXPORT void TF_SetXlaConstantFoldingDisabled(
    unsigned char should_enable);

// Create a serialized tensorflow.ConfigProto proto, where:
//
// a) ConfigProto.optimizer_options.global_jit_level is set to ON_1 if
// `enable_xla_compilation` is non-zero, and OFF otherwise.
// b) ConfigProto.gpu_options.allow_growth is set to `gpu_memory_allow_growth`.

 * This class processes OpenSearch aggregations to provide structured facet information
 * for search result filtering and navigation.
 */
public class FacetResponse {
    /**
     * Map containing query facet counts, where keys are decoded query strings
     * and values are document counts for each query.
     */
    protected Map<String, Long> queryCountMap = new LinkedHashMap<>();

    /**

* MavenSession

  We may need to enable the context injection here, since this will be
  instantiated per-project. If we always inject the same context parameters,
  and are careful to inject nulls where things are missing, we should be

 of models you may specify:

 all of the models that you specify are collected to produce a lineage and then the super model is place at
 the top of that lineage to provide default values.

 The super model is where we place all the values which we believe to be standard, values that can be shared and
 utilized across all your Maven projects.

+-----+
 m0 <- m1 <- m2
+-----+

 which is transformed into

+-----+

		l.IDMap[id] = prev
		shouldLog = false
	}
	l.Unlock()

	if shouldLog {
		consoleLogIf(ctx, subsystem, err, errKind...)
	}
}

const unwrapErrsDepth = 3

// unwrapErrs upto the point where errors.Unwrap(err) returns nil
func unwrapErrs(err error) (leafErr error) {
	uerr := errors.Unwrap(err)
	depth := 1
	for uerr != nil {
		// Save the current `uerr`
		leafErr = uerr

    checkNotNull(r);
    for (char c : cs) {
      addEscape(c, r);
    }
    return this;
  }

  /**
   * Convert this builder into an array of char[]s where the maximum index is the value of the
   * highest character that has been seen. The array will be sparse in the sense that any unseen
   * index will default to null.
   *

     * This can be used to decide whether compression is worthwhile.
     *
     * @param data the data to analyze
     * @param algorithm the compression algorithm
     * @return estimated compression ratio (0.0 to 1.0, where 0.5 means 50% size reduction)
     */
    double estimateCompressionRatio(byte[] data, int algorithm);

    /**
     * Gets the minimum data size threshold for compression.

    }
  }

  /**
   * Returns a human-readable representation of HTTP/2 frame headers.
   *
   * The format is:
   *
   * ```
   * direction streamID length type flags
   * ```
   *
   * Where direction is `<<` for inbound and `>>` for outbound.
   *
   * For example, the following would indicate a HEAD request sent from the client.
   * ```
   * `<< 0x0000000f    12 HEADERS       END_HEADERS|END_STREAM

    public ModelBuildingException(ModelBuildingResult result) {
        super(toMessage(result));
        this.result = result;
    }

    /**
     * Gets the interim result of the model building up to the point where it failed.
     *
     * @return The interim model building result or {@code null} if not available.
     */
    public ModelBuildingResult getResult() {
        return result;
    }

    /**

	if !found {
		return nil, &ErrARNNotFound{}
	}
	return id, nil
}

// TargetIDResult returns result of Remove/Send operation, sets err if
// any for the associated TargetID
type TargetIDResult struct {
	// ID where the remove or send were initiated.
	ID TargetID
	// Stores any error while removing a target or while sending an event.
	Err error
}

// Remove - closes and removes targets by given target IDs.