PutByteBuffer(resp)
						n++
					}
					atomic.AddInt64(&ops, int64(n))
					atomic.AddInt64(&lat, latency)
				})
				spent := time.Since(t)
				if spent > 0 && n > 0 {
					// Since we are benchmarking n parallel servers we need to multiply by n.
					// This will give an estimate of the total ops/s.
					latency := float64(atomic.LoadInt64(&lat)) / float64(time.Millisecond)

		m[i] = byte(i)
	}
	return moveToFrontDecoder(m)
}

func (m moveToFrontDecoder) Decode(n int) (b byte) {
	// Implement move-to-front with a simple copy. This approach
	// beats more sophisticated approaches in benchmarking, probably
	// because it has high locality of reference inside of a
	// single cache line (most move-to-front operations have n < 64).
	b = m[n]
	copy(m[1:], m[:n])
	m[0] = b
	return
}

//	  bar()
//	}
//
// Note that a nil Metrics object won't cause any errors, so one could write
// code like:
//
//	func main() {
//	  enableBenchmarking := flag.Bool("enable", true, "enables benchmarking")
//	  flag.Parse()
//	  var bench *benchmark.Metrics
//	  if *enableBenchmarking {
//	    bench = benchmark.New(benchmark.GC)
//	  }
//	  bench.Start("foo")
//	  // etc.
//	}

  // tensorflow.
  void Prepare(llvm::StringRef mlir_input);

  // Execute() can be called several times after the call to Prepare() (e.g. for
  // benchmarking).
  llvm::SmallVector<Tensor> Execute(llvm::StringRef function_name,
                                    llvm::ArrayRef<Tensor> arguments);

 private:
  void RunTfrtInitializer();

import java.util.Collections;
import java.util.List;
import java.util.Set;
import org.checkerframework.checker.nullness.qual.Nullable;

/**
 * Package up sample data for common collections benchmarking.
 *
 * @author Nicholaus Shupe
 */
class CollectionBenchmarkSampleData {
  private final boolean isUserTypeFast;
  private final SpecialRandom random;
  private final double hitRate;
  private final int size;

	m map[K]V       // for many pairs
}

type entry[K comparable, V any] struct {
	key   K
	value V
}

// maxSlice is the maximum number of pairs for which a slice is used.
// It is a variable for benchmarking.
var maxSlice int = 8

// add adds a key-value pair to the mapping.
func (h *mapping[K, V]) add(k K, v V) {
	if h.m == nil && len(h.s) < maxSlice {
		h.s = append(h.s, entry[K, V]{k, v})
	} else {

        allowEmpty = false,
        description = "Command line option for the performance test task to enable profiling. For example `async-profiler`, `async-profiler-heap`, `async-profiler-all` or `jfr`. Use `none` for benchmarking only."
    )
}

object AdHocPerformanceScenarioLinux : AdHocPerformanceScenario(Os.LINUX)
object AdHocPerformanceScenarioWindows : AdHocPerformanceScenario(Os.WINDOWS)

)

mlir_to_bef(
    name = "custom_thread_pool.mlir",
    tfrt_translate = "//tensorflow/compiler/mlir/tfrt:tfrt_fallback_translate",
)

# copybara:uncomment_begin(internal benchmarking)
# # C++ benchmarks for batch function runtime fallback.
# tfrt_cc_test_and_strict_benchmark(
#     name = "batch_function_fallback_benchmark_test",
#     srcs = ["batch_function_fallback_benchmark_test.cc"],

// Copyright 2022 The Go Authors. All rights reserved.
// Use of this source code is governed by a BSD-style
// license that can be found in the LICENSE file.

package benchmarks

// Handlers for benchmarking.

import (
	"context"
	"fmt"
	"io"
	"log/slog"
	"log/slog/internal/buffer"
	"strconv"
	"time"
)

// A fastTextHandler writes a Record to an io.Writer in a format similar to

			b.Fatal(resp.Err)
		}
		if resp.Count == 0 {
			b.Fatal("worker did not make progress")
		}
		i += resp.Count
	}
}

// newWorkerForTest creates and starts a worker process for testing or
// benchmarking. The worker process calls RunFuzzWorker, which responds to
// RPC messages until it's stopped. The process is stopped and cleaned up
// automatically when the test is done.
func newWorkerForTest(tb testing.TB) *worker {