rawrange.Src_offset = value.Src_offset
	rawrange.Src_length = value.Src_length
	rawrange.Dest_count = uint16(len(value.Info))
	rawrange.Reserved1 = value.Reserved1
	rawrange.Reserved2 = value.Reserved2

	for i := range value.Info {
		rawinfo := (*RawFileDedupeRangeInfo)(unsafe.Pointer(
			uintptr(unsafe.Pointer(&buf[0])) + uintptr(SizeofRawFileDedupeRange) +

	Imcasts    uint32
	Omcasts    uint32
	Iqdrops    uint32
	Noproto    uint32
	Recvtiming uint32
	Xmittiming uint32
	Lastchange Timeval32
	Unused2    uint32
	Hwassist   uint32
	Reserved1  uint32
	Reserved2  uint32
}

type IfaMsghdr struct {
	Msglen    uint16
	Version   uint8
	Type      uint8
	Addrs     int32
	Flags     int32
	Index     uint16
	Pad_cgo_0 [2]byte
	Metric    int32

	Imcasts    uint32
	Omcasts    uint32
	Iqdrops    uint32
	Noproto    uint32
	Recvtiming uint32
	Xmittiming uint32
	Lastchange Timeval32
	Unused2    uint32
	Hwassist   uint32
	Reserved1  uint32
	Reserved2  uint32
}

type IfaMsghdr struct {
	Msglen    uint16
	Version   uint8
	Type      uint8
	Addrs     int32
	Flags     int32
	Index     uint16
	Pad_cgo_0 [2]byte
	Metric    int32

) -> tensor<1x28x28x64xf32> {

  // CHECK: "tf.FusedBatchNormV3"
  // CHECK-SAME: (%[[X_TRANSPOSE:[0-9]*]], %arg1, %arg1, %arg1, %arg1)
  // CHECK-SAME: data_format = "NCHW"
  %y, %batch_mean, %batch_var, %reserve_1, %reserve_2, %reserve_3
    = "tf.FusedBatchNormV3"(%arg0, %arg1, %arg1, %arg1, %arg1)
       {
         data_format = "NHWC",
         epsilon = 1.001 : f32,
         exponential_avg_factor = 1.0 : f32,
         is_training = true

) -> tensor<1x28x28x64xf32> {

  // CHECK: "tf.FusedBatchNormV3"
  // CHECK-SAME: (%[[X_TRANSPOSE:[0-9]*]], %arg1, %arg1, %arg1, %arg1)
  // CHECK-SAME: data_format = "NCHW"
  %y, %batch_mean, %batch_var, %reserve_1, %reserve_2, %reserve_3
    = "tf.FusedBatchNormV3"(%arg0, %arg1, %arg1, %arg1, %arg1)
       {
         data_format = "NHWC",
         epsilon = 1.001 : f32,
         exponential_avg_factor = 1.0 : f32,

  %1 = "tf.Transpose"(%arg0, %0) : (tensor<1x64x112x112xf32>, tensor<4xi32>) -> tensor<1x112x112x64xf32>

  // Compute FusedBatchNormV3 in NHWC format
  %2, %batch_mean, %batch_var, %reserve_1, %reserve_2, %reserve_3
    = "tf.FusedBatchNormV3"(%1, %arg1, %arg1, %arg1, %arg1)
       {
         data_format = "NHWC",
         epsilon = 1.001 : f32,
         exponential_avg_factor = 1.0 : f32,

  // CHECK-SAME: <{value = dense<[0, 2, 3, 1]> : tensor<4xi64>}>
  // CHECK: %[[RES_TRANSPOSE:[0-9]*]] = "tf.Transpose"(%y, %[[RES_PERM]])
  // CHECK: return %[[RES_TRANSPOSE]]

  %y, %batch_mean, %batch_var, %reserve_1, %reserve_2, %reserve_3
    = "tf.FusedBatchNormV3"(%arg0, %arg1, %arg1, %arg1, %arg1)
       {
         data_format = "NHWC",
         epsilon = 1.001 : f32,
         exponential_avg_factor = 1.0 : f32,

  // CHECK-SAME: <{value = dense<[0, 3, 1, 2]> : tensor<4xi64>}>
  // CHECK: %[[RES_TRANSPOSE:[0-9]*]] = "tf.Transpose"(%y, %[[RES_PERM]])
  // CHECK: return %[[RES_TRANSPOSE]]

  %y, %batch_mean, %batch_var, %reserve_1, %reserve_2, %reserve_3
    = "tf.FusedBatchNormV3"(%arg0, %arg1, %arg1, %arg1, %arg1)
       {
         data_format = "NCHW",
         epsilon = 1.001 : f32,
         exponential_avg_factor = 1.0 : f32,
         is_training = true

//
// Developed at SunPro, a Sun Microsystems, Inc. business.
// Permission to use, copy, modify, and distribute this
// software is freely granted, provided that this notice
// is preserved.
// ====================================================
//
// __ieee754_remainder(x,y)
// Return :
//      returns  x REM y  =  x - [x/y]*y  as if in infinite
//      precision arithmetic, where [x/y] is the (infinite bit)

//
// Developed at SunPro, a Sun Microsystems, Inc. business.
// Permission to use, copy, modify, and distribute this
// software is freely granted, provided that this notice
// is preserved.
// ====================================================
//
//
// asinh(x)
// Method :
//	Based on
//	        asinh(x) = sign(x) * log [ |x| + sqrt(x*x+1) ]
//	we have
//	asinh(x) := x  if  1+x*x=1,