bells17 <******@****.***> 1713555590 +0900

// size might have a 26.6% (1.266x) overhead.
// In practice, only one of the wastes comes into play for a
// given size (sizes < 512 waste mainly on the round-up,
// sizes > 512 waste mainly on the page chopping).
// For really small sizes, alignment constraints force the
// overhead higher.

package main

import (
	"bytes"
	"flag"
	"fmt"
	"go/format"
	"io"
	"log"
	"math"

  MLIR input.
* `--input-arg-shapes`: A string representation of input argument shapes for
  'main' entry-point, separating tensors with ':', dimension with ',', and
  using '?' for unknown sizes. For example, `input-arg-shapes=1,2::1,?`
  expresses argument shapes `[1,2]`, `[]` and `[1,?]`.
* `--e`: Elide large elements attrs while dumping the output StableHLO.

//    SavedModel.
//   input_arg_shapes_str: A string representation of input argument
//    shapes for 'main' entry-point, separating tensors with ':', dimension
//    with ',', and using '?' for unknown sizes. For example,
//    'input-arg-shapes=1,2::1,?' expresses argument shapes [1,2], [] and [1,?].
//
// Returns:
//   An absl::StatusOr containing the serialized bytecode of the StableHLO

)

func TestSendFile(t *testing.T) {
	sizes := []int{
		1,
		42,
		1025,
		syscall.Getpagesize() + 1,
		32769,
	}
	t.Run("sendfile-to-unix", func(t *testing.T) {
		for _, size := range sizes {
			t.Run(strconv.Itoa(size), func(t *testing.T) {
				testSendFile(t, "unix", int64(size))
			})
		}
	})
	t.Run("sendfile-to-tcp", func(t *testing.T) {
		for _, size := range sizes {

	buildSlicing8TablesOnce()
	crc = ^crc
	// Table comparison is somewhat expensive, so avoid it for small sizes
	for len(p) >= 64 {
		var helperTable *[8]Table
		if *tab == slicing8TableECMA[0] {
			helperTable = slicing8TableECMA
		} else if *tab == slicing8TableISO[0] {
			helperTable = slicing8TableISO
			// For smaller sizes creating extended table takes too much time
		} else if len(p) >= 2048 {

        * input-arg-shapes: A string representation of input argument shapes for
          'main' entry-point, separating tensors with ':', dimension with ',', and
          using '?' for unknown sizes. For example, 'input-arg-shapes=1,2::1,?'
          expresses argument shapes [1,2], [] and [1,?].
        )pbdoc",
      py::arg("input_path"),
      py::arg("exported_model_signatures") =

  }

  // These ops are cheap regardless of their input sizes.
  //
  // TODO(chky): Find a more scalable way to figure out cheap ops.
  if (llvm::isa<mlir::TF::ShapeOp, mlir::TF::StridedSliceOp,
                mlir::TF::ReshapeOp, mlir::TF::ExpandDimsOp>(op)) {
    cost_map_[op] = kDefaultCheapCost;
    return;
  }

  // For other ops, use the sum of input sizes as its cost.
  int64_t cost = kDefaultCheapCost;

//     backup space is needed for incremental backups. Larger block sizes also mean less performance for random read restore
//     methods like Instant Restore, File Level Recovery, and Database/Application restores. Veeam recommends that vendors
//     optimize the storage system for the default value of 1MB minus compression object sizes. The setting simultaneously

	configSizeBytes = monitoring.NewDistribution(
		"pilot_xds_config_size_bytes",
		"Distribution of configuration sizes pushed to clients",
		// Important boundaries: 10K, 1M, 4M, 10M, 40M
		// 4M default limit for gRPC, 10M config will start to strain system,
		// 40M is likely upper-bound on config sizes supported.
		[]float64{1, 10000, 1000000, 4000000, 10000000, 40000000},
		monitoring.WithUnit(monitoring.Bytes),
	)
)