ホーム › AI.MachineLearning.DirectML › DML_BATCH_NORMALIZATION_OPERATOR_DESC
DML_BATCH_NORMALIZATION_OPERATOR_DESC
構造体サイズ=各フィールドのバイト数(x64/x86 で異なる場合は x64/x86 と併記)。x64/x86 列=フィールドのバイトオフセット(HSPで dupptr / lpoke / wpoke 等に使用)。
フィールド
| フィールド | 型 | サイズ | x64 | x86 | 説明 |
|---|---|---|---|---|---|
| InputTensor | DML_TENSOR_DESC* | 8/4 | +0 | +0 | 演算子の入力テンソルを記述するDML_TENSOR_DESCへのポインタ。 |
| MeanTensor | DML_TENSOR_DESC* | 8/4 | +8 | +4 | 正規化に用いる平均値を保持するテンソルを記述するDML_TENSOR_DESCへのポインタ。 |
| VarianceTensor | DML_TENSOR_DESC* | 8/4 | +16 | +8 | 正規化に用いる分散を保持するテンソルを記述するDML_TENSOR_DESCへのポインタ。 |
| ScaleTensor | DML_TENSOR_DESC* | 8/4 | +24 | +12 | 量子化や正規化で用いるスケール係数を保持するテンソルを記述するDML_TENSOR_DESCへのポインタ。 |
| BiasTensor | DML_TENSOR_DESC* | 8/4 | +32 | +16 | 各要素に加算するバイアス値を保持するテンソルを記述するDML_TENSOR_DESCへのポインタ。省略可。 |
| OutputTensor | DML_TENSOR_DESC* | 8/4 | +40 | +20 | 演算結果を格納する出力テンソルを記述するDML_TENSOR_DESCへのポインタ。 |
| Spatial | BOOL | 4 | +48 | +24 | 空間次元をまたいで統計を共有するかを示すBOOL。 |
| Epsilon | FLOAT | 4 | +52 | +28 | ゼロ除算を避けるため分母に加える微小値。 |
| FusedActivation | DML_OPERATOR_DESC* | 8/4 | +56 | +32 | 演算の後段に融合させる活性化関数を指定するDML_OPERATOR_DESCへのポインタ。不要ならNULL可。 |
各言語での定義
#include <windows.h>
// DML_BATCH_NORMALIZATION_OPERATOR_DESC (x64 64 / x86 36 バイト)
typedef struct DML_BATCH_NORMALIZATION_OPERATOR_DESC {
DML_TENSOR_DESC* InputTensor;
DML_TENSOR_DESC* MeanTensor;
DML_TENSOR_DESC* VarianceTensor;
DML_TENSOR_DESC* ScaleTensor;
DML_TENSOR_DESC* BiasTensor;
DML_TENSOR_DESC* OutputTensor;
BOOL Spatial;
FLOAT Epsilon;
DML_OPERATOR_DESC* FusedActivation;
} DML_BATCH_NORMALIZATION_OPERATOR_DESC;using System;
using System.Runtime.InteropServices;
[StructLayout(LayoutKind.Sequential, CharSet = CharSet.Unicode)]
public struct DML_BATCH_NORMALIZATION_OPERATOR_DESC
{
public IntPtr InputTensor;
public IntPtr MeanTensor;
public IntPtr VarianceTensor;
public IntPtr ScaleTensor;
public IntPtr BiasTensor;
public IntPtr OutputTensor;
[MarshalAs(UnmanagedType.Bool)] public bool Spatial;
public float Epsilon;
public IntPtr FusedActivation;
}Imports System.Runtime.InteropServices
<StructLayout(LayoutKind.Sequential, CharSet:=CharSet.Unicode)>
Public Structure DML_BATCH_NORMALIZATION_OPERATOR_DESC
Public InputTensor As IntPtr
Public MeanTensor As IntPtr
Public VarianceTensor As IntPtr
Public ScaleTensor As IntPtr
Public BiasTensor As IntPtr
Public OutputTensor As IntPtr
<MarshalAs(UnmanagedType.Bool)> Public Spatial As Boolean
Public Epsilon As Single
Public FusedActivation As IntPtr
End Structureimport ctypes
from ctypes import wintypes
class DML_BATCH_NORMALIZATION_OPERATOR_DESC(ctypes.Structure):
_fields_ = [
("InputTensor", ctypes.c_void_p),
("MeanTensor", ctypes.c_void_p),
("VarianceTensor", ctypes.c_void_p),
("ScaleTensor", ctypes.c_void_p),
("BiasTensor", ctypes.c_void_p),
("OutputTensor", ctypes.c_void_p),
("Spatial", wintypes.BOOL),
("Epsilon", ctypes.c_float),
("FusedActivation", ctypes.c_void_p),
]#[repr(C)]
pub struct DML_BATCH_NORMALIZATION_OPERATOR_DESC {
pub InputTensor: *mut core::ffi::c_void,
pub MeanTensor: *mut core::ffi::c_void,
pub VarianceTensor: *mut core::ffi::c_void,
pub ScaleTensor: *mut core::ffi::c_void,
pub BiasTensor: *mut core::ffi::c_void,
pub OutputTensor: *mut core::ffi::c_void,
pub Spatial: i32,
pub Epsilon: f32,
pub FusedActivation: *mut core::ffi::c_void,
}import "golang.org/x/sys/windows"
type DML_BATCH_NORMALIZATION_OPERATOR_DESC struct {
InputTensor uintptr
MeanTensor uintptr
VarianceTensor uintptr
ScaleTensor uintptr
BiasTensor uintptr
OutputTensor uintptr
Spatial int32
Epsilon float32
FusedActivation uintptr
}type
DML_BATCH_NORMALIZATION_OPERATOR_DESC = record
InputTensor: Pointer;
MeanTensor: Pointer;
VarianceTensor: Pointer;
ScaleTensor: Pointer;
BiasTensor: Pointer;
OutputTensor: Pointer;
Spatial: BOOL;
Epsilon: Single;
FusedActivation: Pointer;
end;const DML_BATCH_NORMALIZATION_OPERATOR_DESC = extern struct {
InputTensor: ?*anyopaque,
MeanTensor: ?*anyopaque,
VarianceTensor: ?*anyopaque,
ScaleTensor: ?*anyopaque,
BiasTensor: ?*anyopaque,
OutputTensor: ?*anyopaque,
Spatial: i32,
Epsilon: f32,
FusedActivation: ?*anyopaque,
};type
DML_BATCH_NORMALIZATION_OPERATOR_DESC {.bycopy.} = object
InputTensor: pointer
MeanTensor: pointer
VarianceTensor: pointer
ScaleTensor: pointer
BiasTensor: pointer
OutputTensor: pointer
Spatial: int32
Epsilon: float32
FusedActivation: pointerstruct DML_BATCH_NORMALIZATION_OPERATOR_DESC
{
void* InputTensor;
void* MeanTensor;
void* VarianceTensor;
void* ScaleTensor;
void* BiasTensor;
void* OutputTensor;
int Spatial;
float Epsilon;
void* FusedActivation;
}HSP用 定義
HSP3.7/3.8 は構造体機能が無いため4byte整数配列(dim)+peek/poke で操作(32/64bitでサイズ・位置が異なる場合はタブで分割)。IronHSP は NSTRUCT(#defstruct/stdim/->)で32/64bit共通。
; HSP3.7/3.8 は構造体機能が無いため、4byte整数の配列変数で操作します。(x86 レイアウト)
; DML_BATCH_NORMALIZATION_OPERATOR_DESC サイズ: 36 バイト(x86)
dim st, 9 ; 4byte整数×9(構造体サイズ 36 / 4 切り上げ)
; InputTensor : DML_TENSOR_DESC* (+0, 4byte) varptr(st)+0 を基点に操作(4byte:入れ子/配列)
; MeanTensor : DML_TENSOR_DESC* (+4, 4byte) varptr(st)+4 を基点に操作(4byte:入れ子/配列)
; VarianceTensor : DML_TENSOR_DESC* (+8, 4byte) varptr(st)+8 を基点に操作(4byte:入れ子/配列)
; ScaleTensor : DML_TENSOR_DESC* (+12, 4byte) varptr(st)+12 を基点に操作(4byte:入れ子/配列)
; BiasTensor : DML_TENSOR_DESC* (+16, 4byte) varptr(st)+16 を基点に操作(4byte:入れ子/配列)
; OutputTensor : DML_TENSOR_DESC* (+20, 4byte) varptr(st)+20 を基点に操作(4byte:入れ子/配列)
; Spatial : BOOL (+24, 4byte) st.6 = 値 / 値 = st.6 (lpoke/lpeek も可)
; Epsilon : FLOAT (+28, 4byte) st.7 = 値 / 値 = st.7 (lpoke/lpeek も可)
; FusedActivation : DML_OPERATOR_DESC* (+32, 4byte) varptr(st)+32 を基点に操作(4byte:入れ子/配列)
; ※4byte境界の整数は添字 st.N(N=オフセット/4)で読み書き可。それ以外は peek/poke 系を使用。; HSP3.7/3.8 は構造体機能が無いため、4byte整数の配列変数で操作します。(x64 レイアウト)
; DML_BATCH_NORMALIZATION_OPERATOR_DESC サイズ: 64 バイト(x64)
dim st, 16 ; 4byte整数×16(構造体サイズ 64 / 4 切り上げ)
; InputTensor : DML_TENSOR_DESC* (+0, 8byte) varptr(st)+0 を基点に操作(8byte:入れ子/配列)
; MeanTensor : DML_TENSOR_DESC* (+8, 8byte) varptr(st)+8 を基点に操作(8byte:入れ子/配列)
; VarianceTensor : DML_TENSOR_DESC* (+16, 8byte) varptr(st)+16 を基点に操作(8byte:入れ子/配列)
; ScaleTensor : DML_TENSOR_DESC* (+24, 8byte) varptr(st)+24 を基点に操作(8byte:入れ子/配列)
; BiasTensor : DML_TENSOR_DESC* (+32, 8byte) varptr(st)+32 を基点に操作(8byte:入れ子/配列)
; OutputTensor : DML_TENSOR_DESC* (+40, 8byte) varptr(st)+40 を基点に操作(8byte:入れ子/配列)
; Spatial : BOOL (+48, 4byte) st.12 = 値 / 値 = st.12 (lpoke/lpeek も可)
; Epsilon : FLOAT (+52, 4byte) st.13 = 値 / 値 = st.13 (lpoke/lpeek も可)
; FusedActivation : DML_OPERATOR_DESC* (+56, 8byte) varptr(st)+56 を基点に操作(8byte:入れ子/配列)
; ※4byte境界の整数は添字 st.N(N=オフセット/4)で読み書き可。それ以外は peek/poke 系を使用。; IronHSP は NSTRUCT(構造体)をサポート。32bit/64bit どちらでも同じコードで動作します。
#defstruct global DML_BATCH_NORMALIZATION_OPERATOR_DESC
#field intptr InputTensor
#field intptr MeanTensor
#field intptr VarianceTensor
#field intptr ScaleTensor
#field intptr BiasTensor
#field intptr OutputTensor
#field bool Spatial
#field float Epsilon
#field intptr FusedActivation
#endstruct
stdim st, DML_BATCH_NORMALIZATION_OPERATOR_DESC ; NSTRUCT 変数を確保
st->Spatial = 100
mes "Spatial=" + st->Spatial