// gradient registerer to instantiate a GradientFunction.
struct ForwardOperation {
 public:
  string op_name;
  std::vector<AbstractTensorHandle*> inputs;
  std::vector<AbstractTensorHandle*> outputs;
  std::vector<int64_t> skip_input_indices;
  AttrBuilder attrs;
};

using GradientFunctionFactory =
    std::function<GradientFunction*(const ForwardOperation& op)>;

  var previousMappedRanges: List<MappedRange>? = null

  for ((section, sectionMappedRanges) in sections) {
    // Skip sequential ranges when they are equal.
    if (sectionMappedRanges == previousMappedRanges) continue
    previousMappedRanges = sectionMappedRanges

    val sectionOffset = rangesBuffer.size.toInt() / 4

    // Section prefix.
    sectionIndexBuffer.writeByte(section and 0x1fc000 shr 14)

            return;
        }

        Document document = parent.getOwnerDocument();

        Element section = document.createElement("section");
        parent.appendChild(section);

        Element title = document.createElement("title");
        section.appendChild(title);
        title.appendChild(document.createTextNode("Methods added by the "));

                Map.of("_default", List.of("QUERY1")), //
                Set.of("QUERY1"), //

image: {{ .Values.image.repository }}:{{ .Values.image.tag }} imagePullPolicy: {{ .Values.image.pullPolicy }} command: [ "/bin/sh", "-ce", "/usr/bin/docker-entrypoint.sh minio server {{- range $i := until $poolCount }}{{ $factor := mul $i $nodeCount }}{{ $endIndex := add $factor $nodeCount }}{{ $beginIndex := mul $i $nodeCount }} {{ $scheme }}://{{ template `minio.fullname` $ }}-{{ `{` }}{{ $beginIndex }}...{{ sub $endIndex 1 }}{{ `}`}}.{{ template `minio.fullname` $ }}-svc.{{ $.Release.Namespace...

image: {{ .Values.image.repository }}:{{ .Values.image.tag }} imagePullPolicy: {{ .Values.image.pullPolicy }} command: [ "/bin/sh", "-ce", "/usr/bin/docker-entrypoint.sh minio server {{- range $i := until $poolCount }}{{ $factor := mul $i $nodeCount }}{{ $endIndex := add $factor $nodeCount }}{{ $beginIndex := mul $i $nodeCount }} {{ $scheme }}://{{ template `minio.fullname` $ }}-{{ `{` }}{{ $beginIndex }}...{{ sub $endIndex 1 }}{{ `}`}}.{{ template `minio.fullname` $ }}-svc.{{ $.Release.Namespace...

image: {{ .Values.image.repository }}:{{ .Values.image.tag }} imagePullPolicy: {{ .Values.image.pullPolicy }} command: [ "/bin/sh", "-ce", "/usr/bin/docker-entrypoint.sh minio server {{- range $i := until $poolCount }}{{ $factor := mul $i $nodeCount }}{{ $endIndex := add $factor $nodeCount }}{{ $beginIndex := mul $i $nodeCount }} {{ $scheme }}://{{ template `minio.fullname` $ }}-{{ `{` }}{{ $beginIndex }}...{{ sub $endIndex 1 }}{{ `}`}}.{{ template `minio.fullname` $ }}-svc.{{ $.Release.Namespace...

   *
   * <p><i>Notes:</i> This is an implementation of the algorithm for Lexicographical Permutations
   * Generation, described in Knuth's "The Art of Computer Programming", Volume 4, Chapter 7,
   * Section 7.2.1.2. The iteration order follows the lexicographical order. This means that the
   * first permutation will be in ascending order, and the last will be in descending order.
   *

==============================================================================*/

#ifndef TENSORFLOW_C_EAGER_C_API_UNIFIED_EXPERIMENTAL_INTERNAL_H_
#define TENSORFLOW_C_EAGER_C_API_UNIFIED_EXPERIMENTAL_INTERNAL_H_

#include <vector>

#include "tensorflow/c/c_api.h"
#include "tensorflow/c/conversion_macros.h"
#include "tensorflow/c/eager/abstract_context.h"
#include "tensorflow/c/eager/abstract_operation.h"

	MOVL (AX)(X0*1), AX             // ERROR "invalid instruction"
	MOVL (AX)(Y0*1), AX             // ERROR "invalid instruction"
	// VSIB/VM is invalid without vector index.
	// TODO(quasilyte): improve error message (#21860).
	// "invalid VSIB address (missing vector index)"
	VPGATHERQQ Y2, (BP), Y1         // ERROR "invalid instruction"
	// AVX2GATHER mask/index/dest #UD cases.