/* NiuTrans.Tensor - an open-source tensor library
* Copyright (C) 2017, Natural Language Processing Lab, Northeastern University.
* All rights reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
*   http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/

/*
* $Created by: XIAO Tong (email: xiaotong@mail.neu.edu.cn) 2018-04-24
*/

#include "CopyValues.h"
#include "CopyValues.cuh"
#include "../../XUtility.h"
#include "../../XDevice.h"

namespace nts { // namespace nts(NiuTrans.Tensor)

#ifdef USE_CUDA

/*
copy a range of elements from a source vector to a target vector
>> s - source matrix
>> t - target matrix
<< return - succeed or not
*/
void _CudaCopyValues(const XTensor * s, XTensor * t)
{
    CheckNTErrors(s != NULL && t != NULL, "The input tensor and output tensor must be nonempty!");
    CheckNTErrors(s->dataType == t->dataType, "Unmatched data type!");
    CheckNTErrors(s->unitSize == t->unitSize, "Incompatible data types in value copy.");
    CheckNTErrors(s->unitNum == t->unitNum, "The data items are be the same.");
    CheckNTErrors(s->denseRatio <= t->denseRatio, "Incompatible vectors in value copy.");

    /* dense -> dense */
    if (!s->isSparse && !t->isSparse) {
        XMemCopy(t->data, t->devID, s->data, s->devID, s->unitSize * s->unitNum);
    }
    /* dense -> sparse */
    else if (!s->isSparse && t->isSparse &&
              s->dataType == DEFAULT_DTYPE &&
              t->dataType == DEFAULT_DTYPE)
    {
        ShowNTErrors("TODO!");
    }
    /* sparse -> dense */
    else if (s->isSparse && !t->isSparse &&
             s->dataType == DEFAULT_DTYPE &&
             t->dataType == DEFAULT_DTYPE)
    {
        ShowNTErrors("TODO!");
    }
    /* sparse -> sparse */
    else if (s->isSparse && t->isSparse &&
             s->dataType == DEFAULT_DTYPE &&
             t->dataType == DEFAULT_DTYPE)
    {
        int num = s->unitNumNonZero;
        int size = sizeof(int) + num * (s->unitSize + sizeof(int));

        XMemCopy(t->data, t->devID, s->data, s->devID, size);
        
        t->unitNumNonZero = num;
    }
    else {
        ShowNTErrors("TODO!");
    }
}


#endif // USE_CUDA

} // namespace nts(NiuTrans.Tensor)
	.file	"tmpxft_002a63e7_00000000-6_CopyValues.cudafe1.cpp"
	.text
#APP

#NO_APP
	.type	_ZL26__cudaUnregisterBinaryUtilv, @function
_ZL26__cudaUnregisterBinaryUtilv:
.LFB3060:
	.cfi_startproc
	endbr64
	movq	_ZL20__cudaFatCubinHandle(%rip), %rdi
	jmp	__cudaUnregisterFatBinary@PLT
	.cfi_endproc
.LFE3060:
	.size	_ZL26__cudaUnregisterBinaryUtilv, .-_ZL26__cudaUnregisterBinaryUtilv
	.section	.text.startup,"ax",@progbits
	.type	_ZL24__sti____cudaRegisterAllv, @function
_ZL24__sti____cudaRegisterAllv:
.LFB3083:
	.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
.LFE3083:
	.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:

/* NiuTrans.Tensor - an open-source tensor library
* Copyright (C) 2017, Natural Language Processing Lab, Northeastern University.
* All rights reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
*   http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/

/*
* $Created by: XIAO Tong (email: xiaotong@mail.neu.edu.cn) 2018-04-24
*/

#ifndef __COPYVALUES_CUH__
#define __COPYVALUES_CUH__

#include "../../XTensor.h"

namespace nts { // namespace nts(NiuTrans.Tensor)

#ifdef USE_CUDA

/* copy all elements from a source matrix to a target matrix */
void _CudaCopyValues(const XTensor * s, XTensor * t);

#endif // USE_CUDA

} // namespace nts(NiuTrans.Tensor)

#endif // __COPYVALUES_CUH__
	.text
	.file	"CopyValues.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
