Mode      uint32
	Uid       uint32
	Gid       uint32
	X__pad0   int32
	Rdev      uint64
	Size      int64
	Blksize   int64
	Blocks    int64
	Atim      Timespec
	Mtim      Timespec
	Ctim      Timespec
	X__unused [3]int64
}

type Statfs_t struct {
	Type    int64
	Bsize   int64
	Blocks  uint64
	Bfree   uint64
	Bavail  uint64
	Files   uint64
	Ffree   uint64
	Fsid    Fsid

  // CHECK: %[[R1:.*]] = "tf.MaxPool"(%[[R0]]) <{data_format = "NHWC", explicit_paddings = [], ksize = [1, 3, 3, 1], padding = "SAME", strides = [1, 2, 2, 1]}>
  // CHECK: %[[CST_0:.*]] = "tf.Const"() <{value = dense<[0, 3, 1, 2]> : tensor<4xi64>}>
  // CHECK: "tf.Transpose"(%[[R1]], %[[CST_0]])
  %0 = "tf.MaxPool"(%arg0)
       {
         data_format = "NCHW",
         ksize = [1, 1, 3, 3],
         padding = "SAME",
         strides = [1, 1, 2, 2]

  %1 = "quantfork.dcast"(%0) : (tensor<*x!quant.uniform<i8:f32, 5.000000e-02:-10>>) -> tensor<*xf32>
  %2 = "tf.MaxPool"(%1) {data_format = "NHWC", device = "", explicit_paddings = [], ksize = [1, 2, 2, 1], padding = "VALID", strides = [1, 2, 2, 1]} : (tensor<*xf32>) -> tensor<*xf32>
  %3 = "quantfork.qcast"(%2) {volatile} : (tensor<*xf32>) -> tensor<*x!quant.uniform<i8:f32, 5.000000e-02:-10>>

func (a byPVCSize) Swap(i, j int) {
	a[i], a[j] = a[j], a[i]
}

func (a byPVCSize) Less(i, j int) bool {
	iSize := a[i].Spec.Resources.Requests[v1.ResourceStorage]
	jSize := a[j].Spec.Resources.Requests[v1.ResourceStorage]
	// return true if iSize is less than jSize
	return iSize.Cmp(jSize) == -1
}

// isCSIMigrationOnForPlugin checks if CSI migration is enabled for a given plugin.

  %3 = "tf.TensorSliceDataset"(%2) {device = "", output_shapes = [#tf_type.shape<>], metadata = ""} : (tensor<3xi32>) -> tensor<*x!tf_type.variant>
  // CHECK: "tf.MapAndBatchDataset"(%[[TSLICE]], %[[BSIZE:.*]], %[[NPC]]
  // CHECK-SAME: f = @"__inference_Dataset_map_<lambda>_80",
  %4 = "tf.MapDataset"(%3) {device = "",
           f = @"__inference_Dataset_map_<lambda>_80",

    %0:2 = tf_executor.graph {
      %outputs:2, %control = tf_executor.island wraps "tf.MaxPoolWithArgmax"(%arg0) {T = f32, Targmax = i32, include_batch_in_index = false, ksize = [1, 2, 2, 1], padding = "SAME", strides = [1, 2, 2, 1]} : (tensor<2x4x2x2xf32>) -> (tensor<2x2x1x2xf32>, tensor<2x2x1x2xi32>)
      tf_executor.fetch %outputs#1, %outputs#0 : tensor<2x2x1x2xi32>, tensor<2x2x1x2xf32>
    }

	// not just the ones documented.
	// EaSize contains the reparse tag if the file is a reparse point.
	return &fileStat{
		FileAttributes: d.FileAttributes,
		CreationTime:   d.CreationTime,
		LastAccessTime: d.LastAccessTime,
		LastWriteTime:  d.LastWriteTime,
		FileSizeHigh:   uint32(d.EndOfFile >> 32),
		FileSizeLow:    uint32(d.EndOfFile),
		ReparseTag:     d.EaSize,
		idxhi:          uint32(d.FileID >> 32),

  %8 = "tf.MaxPool"(%7)
       {
         data_format = "NCHW",
         ksize = [1, 1, 3, 3],
         padding = "SAME",
         strides = [1, 1, 2, 2]
       } : (tensor<?x64x112x112xf32>) -> tensor<?x64x56x56xf32>

  // CHECK: %[[MAX_POOL:[0-9]*]] = "tf.MaxPool"
  // CHECK-SAME: data_format = "NHWC"
  // CHECK-SAME: ksize = [1, 3, 3, 1]
  // CHECK-SAME: strides = [1, 2, 2, 1]

Zichuan Wei <******@****.***> 1677736843 -0800

	case asmComplex:
		fsize := size / 2
		cc = append(cc, newComponent(suffix+"_real", asmKind(fsize), fmt.Sprintf("real(complex%d)", size*8), off, fsize, suffix))
		cc = append(cc, newComponent(suffix+"_imag", asmKind(fsize), fmt.Sprintf("imag(complex%d)", size*8), off+fsize, fsize, suffix))

	case asmStruct:
		tu := t.Underlying().(*types.Struct)