<gradient
                android:endX="78.5885"
                android:endY="90.9159"
                android:startX="48.7653"
                android:startY="61.0927"
                android:type="linear">
                <item
                    android:color="#44000000"
                    android:offset="0.0" />
                <item
                    android:color="#00000000"

            <gradient
                android:endX="78.5885"
                android:endY="90.9159"
                android:startX="48.7653"
                android:startY="61.0927"
                android:type="linear">
                <item
                    android:color="#44000000"
                    android:offset="0.0" />
                <item
                    android:color="#00000000"

            <gradient
                android:endX="78.5885"
                android:endY="90.9159"
                android:startX="48.7653"
                android:startY="61.0927"
                android:type="linear">
                <item
                    android:color="#44000000"
                    android:offset="0.0" />
                <item
                    android:color="#00000000"

            <gradient
                android:endX="78.5885"
                android:endY="90.9159"
                android:startX="48.7653"
                android:startY="61.0927"
                android:type="linear">
                <item
                    android:color="#44000000"
                    android:offset="0.0" />
                <item
                    android:color="#00000000"

import java.util.ArrayList;
import java.util.Collection;
import java.util.Comparator;
import java.util.List;

public class ChildMapFactory {
    /**
     * If a node has fewer children, we use a linear search for the child.
     * We use this limit since {@link VfsRelativePath#compareToFirstSegment(String, CaseSensitivity)}
     * is about twice as slow as {@link VfsRelativePath#hasPrefix(String, CaseSensitivity)},

        }

        // Note, that the potential side effect of the transformed provider
        // is going to be executed before this fixed side effect.
        // It is not possible to preserve linear execution order in the general case,
        // as the transformed provider can have side effects hidden under other wrapping providers.
        return Providers.internal(transformedProvider).withSideEffect(SideEffect.fixedFrom(value));

#include "xla/service/hlo.pb.h"
#include "tensorflow/core/platform/path.h"
#include "tensorflow/core/public/session.h"

namespace tensorflow {
namespace {

// Creates a float tensor of linearly increasing values, starting from offset.
Tensor CreateInputTensor(const TensorShape& shape, float offset) {
  Tensor tensor(DT_FLOAT, shape);
  for (int64 i = 0; i < tensor.flat<float>().size(); ++i) {

  mutex_lock lock(mu_);
  if (!definition_event_) {
    return;
  }

  // The set of defined streams is expected to be very small indeed (usually
  // 1-2), so a simple linear scan should be fast enough.
  if (std::find(streams_defined_on_.begin(), streams_defined_on_.end(),
                stream) != streams_defined_on_.end()) {
    // stream is in streams_defined_on_; it doesn't need to be waited on.

		"articles",
	}
	if len(children) != 32 {
		panic("bad len")
	}
	for _, n := range []int{2, 4, 8, 16, 32} {
		list := children[:n]
		b.Run(fmt.Sprintf("n=%d", n), func(b *testing.B) {

			b.Run("rep=linear", func(b *testing.B) {
				var entries []entry[string, any]
				for _, c := range list {
					entries = append(entries, entry[string, any]{c, nil})
				}
				b.ResetTimer()
				for i := 0; i < b.N; i++ {

// a bit vector with (length of input) * (length of prog) bits,
// to make sure it never explores the same (character position, instruction)
// state multiple times. This limits the search to run in time linear in
// the length of the test.
//
// backtrack is a fast replacement for the NFA code on small
// regexps when onepass cannot be used.

package regexp

import (
	"regexp/syntax"
	"sync"
)