* Copyright (c) 2024 Huawei Technologies Co., Ltd.
* This program is free software, you can redistribute it and/or modify it under the terms and conditions of
* CANN Open Software License Agreement Version 2.0 (the "License").
* Please refer to the License for details. You may not use this file except in compliance with the License.
* THIS SOFTWARE IS PROVIDED ON AN "AS IS" BASIS, WITHOUT WARRANTIES OF ANY KIND, EITHER EXPRESS OR IMPLIED,
* INCLUDING BUT NOT LIMITED TO NON-INFRINGEMENT, MERCHANTABILITY, OR FITNESS FOR A PARTICULAR PURPOSE.
* See LICENSE in the root of the software repository for the full text of the License.
*/
#include "transdata_aclnn_runner.h"
#include <aclnn/opdev/op_errno.h>
#include "atb/utils/aclnn_util.h"
#include "atb/utils/log.h"
#include "atb/utils/operation_register.h"
namespace {
static const uint32_t IN_TENSOR_NUM = 1;
static const uint32_t OUT_TENSOR_NUM = 1;
static const uint32_t INDEX_0 = 0;
}
namespace atb {
aclnnStatus (*TransdataAclnnRunner::aclnnGetWorkspaceSizeFunc_)(const aclTensor *, aclTensor *, uint64_t *,
aclOpExecutor **) = nullptr;
aclnnStatus (*TransdataAclnnRunner::aclnnExecuteFunc_)(void *, uint64_t, aclOpExecutor *, aclrtStream) = nullptr;
TransdataAclnnRunner::TransdataAclnnRunner(const infer::TransdataParam ¶m)
: AclnnRunner("TransdataAclnnRunner"), param_(param)
{
ATB_LOG(INFO) << GetLogPrefix() << "TransdataAclnnRunner::TransdataAclnnRunner created";
}
TransdataAclnnRunner::~TransdataAclnnRunner() {}
Status TransdataAclnnRunner::BuildAclnnVariantPack(const RunnerVariantPack &runnerVariantPack)
{
ATB_LOG(INFO) << GetLogPrefix() << "BuildAclnnVariantPack";
ATB_LOG(INFO) << GetLogPrefix() << "variantPack: " << runnerVariantPack.ToString();
this->atbVariantPack_ = runnerVariantPack;
Status ret = NO_ERROR;
this->aclnnVariantPack_.aclInTensors.reserve(IN_TENSOR_NUM);
this->aclnnVariantPack_.aclInTensors.resize(IN_TENSOR_NUM);
std::shared_ptr<AclNNTensor> aclnnTensorPtr = std::make_shared<AclNNTensor>();
atb::Tensor atbTensor = runnerVariantPack.inTensors.at(INDEX_0);
aclnnTensorPtr->atbTensor = atbTensor;
aclnnTensorPtr->strides = GetCopyTensorStride(atbTensor.desc.shape);
ret = CallAclCreateTensor(atbTensor.desc.shape, atbTensor.desc.shape, atbTensor, aclnnTensorPtr,
atbTensor.desc.dtype);
if (ret != NO_ERROR) {
ATB_LOG(ERROR) << GetLogPrefix() << "create aclTensor by aclCreateTensor failed!";
return ret;
}
aclnnTensorPtr->tensorIdx = static_cast<int>(INDEX_0);
aclnnTensorPtr->needUpdateTensorDataPtr = true;
this->aclnnVariantPack_.aclInTensors[INDEX_0] = aclnnTensorPtr;
this->aclnnVariantPack_.aclOutTensors.reserve(OUT_TENSOR_NUM);
this->aclnnVariantPack_.aclOutTensors.resize(OUT_TENSOR_NUM);
aclnnTensorPtr = std::make_shared<AclNNTensor>();
atbTensor = runnerVariantPack.outTensors.at(INDEX_0);
aclnnTensorPtr->atbTensor = atbTensor;
aclnnTensorPtr->strides = GetCopyTensorStride(atbTensor.desc.shape);
ret = CallAclCreateTensor(atbTensor.desc.shape, atbTensor.desc.shape, atbTensor, aclnnTensorPtr,
atbTensor.desc.dtype);
if (ret != NO_ERROR) {
ATB_LOG(ERROR) << GetLogPrefix() << "create aclTensor by aclCreateTensor failed!";
return ret;
}
aclnnTensorPtr->tensorIdx = static_cast<int>(INDEX_0);
aclnnTensorPtr->needUpdateTensorDataPtr = true;
this->aclnnVariantPack_.aclOutTensors[INDEX_0] = aclnnTensorPtr;
return atb::NO_ERROR;
}
aclnnStatus TransdataAclnnRunner::SetAclNNWorkspaceExecutor()
{
ATB_LOG(INFO) << GetLogPrefix() << "aclnnNpuFormatCast setup start.";
if (TransdataAclnnRunner::aclnnGetWorkspaceSizeFunc_ == nullptr) {
ATB_LOG(ERROR) << GetLogPrefix() << "Aclnn GetWorkspaceSizeFunc is null!";
return ACLNN_ERR_INNER_FIND_KERNEL_ERROR;
}
aclTensor *x = this->aclnnVariantPack_.aclInTensors.at(INDEX_0)->tensor;
aclTensor *y = this->aclnnVariantPack_.aclOutTensors.at(INDEX_0)->tensor;
aclOpExecutor *raw_executor_ptr = this->aclnnExecutor_.get();
aclnnStatus ret = TransdataAclnnRunner::aclnnGetWorkspaceSizeFunc_(
x, y, &(this->atbVariantPack_.workspaceBufferSize), &raw_executor_ptr);
this->aclnnExecutor_ = std::shared_ptr<aclOpExecutor>(raw_executor_ptr, [this](aclOpExecutor *ptr) {
if (ptr && this->executorRepeatable_) {
aclDestroyAclOpExecutor(ptr);
}
});
if (ret != ACL_SUCCESS) {
ATB_LOG(DEBUG) << GetLogPrefix() << "aclnnGetWorkspaceSize failed!";
return ret;
}
ATB_LOG(INFO) << GetLogPrefix() << "workspaceSize: " << this->atbVariantPack_.workspaceBufferSize;
return ret;
}
Status TransdataAclnnRunner::LaunchAclnnKernel()
{
ATB_LOG(INFO) << GetLogPrefix() << "LaunchAclnnKernel execute start.";
if (TransdataAclnnRunner::aclnnExecuteFunc_ == nullptr) {
ATB_LOG(ERROR) << GetLogPrefix() << "Aclnn ExecuteFunc is null!";
return ACLNN_ERR_INNER_FIND_KERNEL_ERROR;
}
void *executeStream = GetExecuteStream(this->atbVariantPack_.context);
aclnnStatus ret = TransdataAclnnRunner::aclnnExecuteFunc_(this->atbVariantPack_.workspaceBuffer,
this->atbVariantPack_.workspaceBufferSize,
this->aclnnExecutor_.get(), executeStream);
if (ret != ACL_SUCCESS) {
ATB_LOG(ERROR) << GetLogPrefix() << "Atb aclnn op kernel launch failed with return value: " << ret;
return ERROR_CANN_ERROR;
}
ATB_LOG(INFO) << GetLogPrefix() << "LaunchAclnnKernel execute success.";
return NO_ERROR;
}
Status TransdataAclnnRunner::LoadMethod()
{
ATB_LOG(INFO) << "TransdataAclnnRunner LoadMethod";
if (TransdataAclnnRunner::aclnnGetWorkspaceSizeFunc_ != nullptr &&
TransdataAclnnRunner::aclnnExecuteFunc_ != nullptr) {
return NO_ERROR;
}
return LoadFromSharedObjectFile("aclnnNpuFormatCastGetWorkspaceSize", "aclnnNpuFormatCast",
TransdataAclnnRunner::aclnnGetWorkspaceSizeFunc_,
TransdataAclnnRunner::aclnnExecuteFunc_);
}
REG_RUNNER_TYPE(TransdataAclnnRunner);
}