DML_BATCH_NORMALIZATION_TRAINING_GRAD_OPERATOR_DESC

using System;
using System.Runtime.InteropServices;

[StructLayout(LayoutKind.Sequential, CharSet = CharSet.Unicode)]
public struct DML_BATCH_NORMALIZATION_TRAINING_GRAD_OPERATOR_DESC
{
    public IntPtr InputTensor;
    public IntPtr InputGradientTensor;
    public IntPtr MeanTensor;
    public IntPtr VarianceTensor;
    public IntPtr ScaleTensor;
    public IntPtr OutputGradientTensor;
    public IntPtr OutputScaleGradientTensor;
    public IntPtr OutputBiasGradientTensor;
    public float Epsilon;
}

Imports System.Runtime.InteropServices

<StructLayout(LayoutKind.Sequential, CharSet:=CharSet.Unicode)>
Public Structure DML_BATCH_NORMALIZATION_TRAINING_GRAD_OPERATOR_DESC
    Public InputTensor As IntPtr
    Public InputGradientTensor As IntPtr
    Public MeanTensor As IntPtr
    Public VarianceTensor As IntPtr
    Public ScaleTensor As IntPtr
    Public OutputGradientTensor As IntPtr
    Public OutputScaleGradientTensor As IntPtr
    Public OutputBiasGradientTensor As IntPtr
    Public Epsilon As Single
End Structure

import ctypes
from ctypes import wintypes

class DML_BATCH_NORMALIZATION_TRAINING_GRAD_OPERATOR_DESC(ctypes.Structure):
    _fields_ = [
        ("InputTensor", ctypes.c_void_p),
        ("InputGradientTensor", ctypes.c_void_p),
        ("MeanTensor", ctypes.c_void_p),
        ("VarianceTensor", ctypes.c_void_p),
        ("ScaleTensor", ctypes.c_void_p),
        ("OutputGradientTensor", ctypes.c_void_p),
        ("OutputScaleGradientTensor", ctypes.c_void_p),
        ("OutputBiasGradientTensor", ctypes.c_void_p),
        ("Epsilon", ctypes.c_float),
    ]

#[repr(C)]
pub struct DML_BATCH_NORMALIZATION_TRAINING_GRAD_OPERATOR_DESC {
    pub InputTensor: *mut core::ffi::c_void,
    pub InputGradientTensor: *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 OutputGradientTensor: *mut core::ffi::c_void,
    pub OutputScaleGradientTensor: *mut core::ffi::c_void,
    pub OutputBiasGradientTensor: *mut core::ffi::c_void,
    pub Epsilon: f32,
}

import "golang.org/x/sys/windows"

type DML_BATCH_NORMALIZATION_TRAINING_GRAD_OPERATOR_DESC struct {
	InputTensor uintptr
	InputGradientTensor uintptr
	MeanTensor uintptr
	VarianceTensor uintptr
	ScaleTensor uintptr
	OutputGradientTensor uintptr
	OutputScaleGradientTensor uintptr
	OutputBiasGradientTensor uintptr
	Epsilon float32
}

type
  DML_BATCH_NORMALIZATION_TRAINING_GRAD_OPERATOR_DESC = record
    InputTensor: Pointer;
    InputGradientTensor: Pointer;
    MeanTensor: Pointer;
    VarianceTensor: Pointer;
    ScaleTensor: Pointer;
    OutputGradientTensor: Pointer;
    OutputScaleGradientTensor: Pointer;
    OutputBiasGradientTensor: Pointer;
    Epsilon: Single;
  end;

const DML_BATCH_NORMALIZATION_TRAINING_GRAD_OPERATOR_DESC = extern struct {
    InputTensor: ?*anyopaque,
    InputGradientTensor: ?*anyopaque,
    MeanTensor: ?*anyopaque,
    VarianceTensor: ?*anyopaque,
    ScaleTensor: ?*anyopaque,
    OutputGradientTensor: ?*anyopaque,
    OutputScaleGradientTensor: ?*anyopaque,
    OutputBiasGradientTensor: ?*anyopaque,
    Epsilon: f32,
};

type
  DML_BATCH_NORMALIZATION_TRAINING_GRAD_OPERATOR_DESC {.bycopy.} = object
    InputTensor: pointer
    InputGradientTensor: pointer
    MeanTensor: pointer
    VarianceTensor: pointer
    ScaleTensor: pointer
    OutputGradientTensor: pointer
    OutputScaleGradientTensor: pointer
    OutputBiasGradientTensor: pointer
    Epsilon: float32

struct DML_BATCH_NORMALIZATION_TRAINING_GRAD_OPERATOR_DESC
{
    void* InputTensor;
    void* InputGradientTensor;
    void* MeanTensor;
    void* VarianceTensor;
    void* ScaleTensor;
    void* OutputGradientTensor;
    void* OutputScaleGradientTensor;
    void* OutputBiasGradientTensor;
    float Epsilon;
}