#pragma once

template<typename T> 
__global__
void to_square_kernel(T* image_in,T* image_out,int heightImage,int widthImage)
{
	unsigned int x=blockIdx.x*blockDim.x+threadIdx.x;
 if(x<(heightImage*widthImage))
{
image_out[x]=image_in[x]*image_in[x];
}
}

template <typename T> 
void to_square_transform(T* image_in, T* image_out, int heightImage, int widthImage, int threadsX,cudaStream_t stream)
{	
int nblocks=(heightImage*widthImage)/threadsX;
if((heightImage*widthImage)%threadsX)nblocks++;

	to_square_kernel<<<nblocks,threadsX,0,stream>>>(image_in, image_out, widthImage, heightImage);

}

template<typename T> 
__global__
void multiply_kernel(T* image_in1,T* image_in2,T* image_out,int heightImage,int widthImage)
{
	unsigned int x=blockIdx.x*blockDim.x+threadIdx.x;
 if(x<(heightImage*widthImage))
{
image_out[x]=image_in1[x]*image_in2[x];
}
}

template <typename T> 
void multiply_transform(T* image_in1,T*image_in2, T* image_out, int heightImage, int widthImage, int threadsX,cudaStream_t stream)
{	
int nblocks=(heightImage*widthImage)/threadsX;
if((heightImage*widthImage)%threadsX)nblocks++;

	multiply_kernel<<<nblocks,threadsX,0,stream>>>(image_in1,image_in2, image_out, widthImage, heightImage);
}

template<typename T_in,typename T_out> 
__global__
void normalize_kernel(T_in* image_in,T_out* image_out,T_in * max_value,T_out bound_value,int heightImage,int widthImage)
{
	unsigned int x=blockIdx.x*blockDim.x+threadIdx.x;
T_in normalizing_constant=(*max_value)/bound_value;
 if(x<(heightImage*widthImage))
{
image_out[x]=(T_out)(image_in[x]/normalizing_constant);
}
}

template <typename T_in,typename T_out> 
void normalize_array(T_in* image_in,T_out* image_out,T_in * max_value,T_out bound_value,int heightImage,int widthImage,const int threadsX,cudaStream_t stream)
{	
int nblocks=(heightImage*widthImage)/threadsX;
if((heightImage*widthImage)%threadsX)nblocks++;

	normalize_kernel<<<nblocks,threadsX,0,stream>>>(image_in,image_out,max_value,bound_value, widthImage, heightImage);
}

template<typename T_in,typename T_out> 
__global__
void normalize_kernel2(T_in* image_in,T_out* image_out,T_in  max_value,T_out bound_value,int heightImage,int widthImage)
{
	unsigned int x=blockIdx.x*blockDim.x+threadIdx.x;
T_in normalizing_constant=max_value/bound_value;
 if(x<(heightImage*widthImage))
{
image_out[x]=(T_out)(image_in[x]/normalizing_constant);
}
}

template <typename T_in,typename T_out> 
void normalize_array2(T_in* image_in,T_out* image_out,T_in  max_value,T_out bound_value,int heightImage,int widthImage,const int threadsX,cudaStream_t stream)
{	
int nblocks=(heightImage*widthImage)/threadsX;
if((heightImage*widthImage)%threadsX)nblocks++;

	normalize_kernel2<<<nblocks,threadsX,0,stream>>>(image_in,image_out,max_value,bound_value, widthImage, heightImage);
}
	.file	"tmpxft_0032e5dd_00000000-6_transform_functors.cudafe1.cpp"
	.text
#APP

#NO_APP
	.type	_ZL26__cudaUnregisterBinaryUtilv, @function
_ZL26__cudaUnregisterBinaryUtilv:
.LFB2022:
	.cfi_startproc
	endbr64
	movq	_ZL20__cudaFatCubinHandle(%rip), %rdi
	jmp	__cudaUnregisterFatBinary@PLT
	.cfi_endproc
.LFE2022:
	.size	_ZL26__cudaUnregisterBinaryUtilv, .-_ZL26__cudaUnregisterBinaryUtilv
	.section	.text.startup,"ax",@progbits
	.type	_ZL24__sti____cudaRegisterAllv, @function
_ZL24__sti____cudaRegisterAllv:
.LFB2045:
	.cfi_startproc
	endbr64
	pushq	%rax
	.cfi_def_cfa_offset 16
	leaq	_ZL15__fatDeviceText(%rip), %rdi
	call	__cudaRegisterFatBinary@PLT
	movq	%rax, %rdi
	movq	%rax, _ZL20__cudaFatCubinHandle(%rip)
	call	__cudaRegisterFatBinaryEnd@PLT
	leaq	_ZL26__cudaUnregisterBinaryUtilv(%rip), %rdi
	popq	%rdx
	.cfi_def_cfa_offset 8
	jmp	atexit@PLT
	.cfi_endproc
.LFE2045:
	.size	_ZL24__sti____cudaRegisterAllv, .-_ZL24__sti____cudaRegisterAllv
	.section	.init_array,"aw"
	.align 8
	.quad	_ZL24__sti____cudaRegisterAllv
	.section	.nvFatBinSegment,"aw"
	.align 8
	.type	_ZL15__fatDeviceText, @object
	.size	_ZL15__fatDeviceText, 24
_ZL15__fatDeviceText:
	.long	1180844977
	.long	1
	.quad	fatbinData
	.quad	0
	.local	_ZL20__cudaFatCubinHandle
	.comm	_ZL20__cudaFatCubinHandle,8,8
	.ident	"GCC: (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0"
	.section	.note.GNU-stack,"",@progbits
	.section	.note.gnu.property,"a"
	.align 8
	.long	1f - 0f
	.long	4f - 1f
	.long	5
0:
	.string	"GNU"
1:
	.align 8
	.long	0xc0000002
	.long	3f - 2f
2:
	.long	0x3
3:
	.align 8
4:

#pragma once
#include <hip/hip_runtime.h>


template<typename T> 
__global__
void to_square_kernel(T* image_in,T* image_out,int heightImage,int widthImage)
{
	unsigned int x=blockIdx.x*blockDim.x+threadIdx.x;
 if(x<(heightImage*widthImage))
{
image_out[x]=image_in[x]*image_in[x];
}
}

template <typename T> 
void to_square_transform(T* image_in, T* image_out, int heightImage, int widthImage, int threadsX,hipStream_t stream)
{	
int nblocks=(heightImage*widthImage)/threadsX;
if((heightImage*widthImage)%threadsX)nblocks++;

	to_square_kernel<<<nblocks,threadsX,0,stream>>>(image_in, image_out, widthImage, heightImage);

}

template<typename T> 
__global__
void multiply_kernel(T* image_in1,T* image_in2,T* image_out,int heightImage,int widthImage)
{
	unsigned int x=blockIdx.x*blockDim.x+threadIdx.x;
 if(x<(heightImage*widthImage))
{
image_out[x]=image_in1[x]*image_in2[x];
}
}

template <typename T> 
void multiply_transform(T* image_in1,T*image_in2, T* image_out, int heightImage, int widthImage, int threadsX,hipStream_t stream)
{	
int nblocks=(heightImage*widthImage)/threadsX;
if((heightImage*widthImage)%threadsX)nblocks++;

	multiply_kernel<<<nblocks,threadsX,0,stream>>>(image_in1,image_in2, image_out, widthImage, heightImage);
}

template<typename T_in,typename T_out> 
__global__
void normalize_kernel(T_in* image_in,T_out* image_out,T_in * max_value,T_out bound_value,int heightImage,int widthImage)
{
	unsigned int x=blockIdx.x*blockDim.x+threadIdx.x;
T_in normalizing_constant=(*max_value)/bound_value;
 if(x<(heightImage*widthImage))
{
image_out[x]=(T_out)(image_in[x]/normalizing_constant);
}
}

template <typename T_in,typename T_out> 
void normalize_array(T_in* image_in,T_out* image_out,T_in * max_value,T_out bound_value,int heightImage,int widthImage,const int threadsX,hipStream_t stream)
{	
int nblocks=(heightImage*widthImage)/threadsX;
if((heightImage*widthImage)%threadsX)nblocks++;

	normalize_kernel<<<nblocks,threadsX,0,stream>>>(image_in,image_out,max_value,bound_value, widthImage, heightImage);
}

template<typename T_in,typename T_out> 
__global__
void normalize_kernel2(T_in* image_in,T_out* image_out,T_in  max_value,T_out bound_value,int heightImage,int widthImage)
{
	unsigned int x=blockIdx.x*blockDim.x+threadIdx.x;
T_in normalizing_constant=max_value/bound_value;
 if(x<(heightImage*widthImage))
{
image_out[x]=(T_out)(image_in[x]/normalizing_constant);
}
}

template <typename T_in,typename T_out> 
void normalize_array2(T_in* image_in,T_out* image_out,T_in  max_value,T_out bound_value,int heightImage,int widthImage,const int threadsX,hipStream_t stream)
{	
int nblocks=(heightImage*widthImage)/threadsX;
if((heightImage*widthImage)%threadsX)nblocks++;

	normalize_kernel2<<<nblocks,threadsX,0,stream>>>(image_in,image_out,max_value,bound_value, widthImage, heightImage);
}
	.text
	.file	"transform_functors.hip"
	.type	__hip_cuid_,@object             # @__hip_cuid_
	.bss
	.globl	__hip_cuid_
__hip_cuid_:
	.byte	0                               # 0x0
	.size	__hip_cuid_, 1

	.ident	"AMD clang version 18.0.0git (https://github.com/RadeonOpenCompute/llvm-project roc-6.3.2 25012 e5bf7e55c91490b07c49d8960fa7983d864936c4)"
	.section	".note.GNU-stack","",@progbits
	.addrsig
	.addrsig_sym __hip_cuid_

	.text
	.p2alignl 7, 3214868480
	.fill 96, 4, 3214868480
	.type	__hip_cuid_,@object             ; @__hip_cuid_
	.section	.bss,"aw",@nobits
	.globl	__hip_cuid_
__hip_cuid_:
	.byte	0                               ; 0x0
	.size	__hip_cuid_, 1

	.ident	"AMD clang version 18.0.0git (https://github.com/RadeonOpenCompute/llvm-project roc-6.3.2 25012 e5bf7e55c91490b07c49d8960fa7983d864936c4)"
	.section	".note.GNU-stack","",@progbits
	.addrsig
	.addrsig_sym __hip_cuid_
	.amdgcn_target "amdgcn-amd-amdhsa--gfx1100"
	.amdgpu_metadata
---
amdhsa.kernels:  []
amdhsa.target:   amdgcn-amd-amdhsa--gfx1100
amdhsa.version:
  - 1
  - 2
...

	.end_amdgpu_metadata
