* Copyright (c) 2025 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 "repeat_aclnn_runner.h"
#include "atb/utils/aclnn_util.h"
#include "atb/utils/log.h"
#include "atb/utils/operation_register.h"
namespace atb {
RepeatAclnnGetWorkspaceSizeFunc RepeatAclnnRunner::aclnnGetWorkspaceSizeFunc_ = nullptr;
RepeatAclnnExecuteFunc RepeatAclnnRunner::aclnnExecuteFunc_ = nullptr;
RepeatAclnnRunner::RepeatAclnnRunner(const infer::RepeatParam ¶m) : AclnnRunner("RepeatAclnnRunner"), param_(param)
{
ATB_LOG(INFO) << GetLogPrefix() << "RepeatAclnnRunner::RepeatAclnnRunner called";
}
RepeatAclnnRunner::~RepeatAclnnRunner() {}
Status RepeatAclnnRunner::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(1);
this->aclnnVariantPack_.aclInTensors.resize(1);
for (size_t i = 0; i < this->aclnnVariantPack_.aclInTensors.size(); ++i) {
std::shared_ptr<AclNNTensor> aclnnTensorPtr = std::make_shared<AclNNTensor>();
atb::Tensor atbTensor = runnerVariantPack.inTensors.at(i);
aclnnTensorPtr->atbTensor = atbTensor;
aclnnTensorPtr->strides = GetCopyTensorStride(atbTensor.desc.shape);
ret = CallAclCreateTensor(atbTensor.desc.shape, atbTensor.desc.shape, atbTensor, aclnnTensorPtr);
if (ret != NO_ERROR) {
ATB_LOG(ERROR) << GetLogPrefix() << "create aclTensor by aclCreateTensor failed!";
return ret;
}
aclnnTensorPtr->tensorIdx = static_cast<int>(i);
aclnnTensorPtr->needUpdateTensorDataPtr = true;
this->aclnnVariantPack_.aclInTensors[i] = aclnnTensorPtr;
}
this->aclnnVariantPack_.aclOutTensors.reserve(1);
this->aclnnVariantPack_.aclOutTensors.resize(1);
for (size_t i = 0; i < this->aclnnVariantPack_.aclOutTensors.size(); ++i) {
std::shared_ptr<AclNNTensor> aclnnTensorPtr = std::make_shared<AclNNTensor>();
atb::Tensor atbTensor = runnerVariantPack.outTensors.at(i);
aclnnTensorPtr->atbTensor = atbTensor;
aclnnTensorPtr->strides = GetCopyTensorStride(atbTensor.desc.shape);
ret = CallAclCreateTensor(atbTensor.desc.shape, atbTensor.desc.shape, atbTensor, aclnnTensorPtr);
if (ret != NO_ERROR) {
ATB_LOG(ERROR) << GetLogPrefix() << "create aclTensor by aclCreateTensor failed!";
return ret;
}
aclnnTensorPtr->tensorIdx = static_cast<int>(i);
aclnnTensorPtr->needUpdateTensorDataPtr = true;
this->aclnnVariantPack_.aclOutTensors[i] = aclnnTensorPtr;
}
return atb::NO_ERROR;
}
aclnnStatus RepeatAclnnRunner::SetAclNNWorkspaceExecutor()
{
ATB_LOG(INFO) << GetLogPrefix() << "aclnn setup start.";
ATB_LOG(INFO) << GetLogPrefix() << ", aclInTensors size: " << this->aclnnVariantPack_.aclInTensors.size()
<< ", aclOutTensors size: " << this->aclnnVariantPack_.aclOutTensors.size();
size_t inTensorStart = 0;
aclTensor *self = this->aclnnVariantPack_.aclInTensors.at(inTensorStart++)->tensor;
size_t outTensorStart = 0;
aclTensor *out = this->aclnnVariantPack_.aclOutTensors.at(outTensorStart++)->tensor;
size_ = aclCreateIntArray(this->param_.multiples.data(), this->param_.multiples.size());
aclOpExecutor *rawExecutorPtr = this->aclnnExecutor_.get();
aclnnStatus ret = RepeatAclnnRunner::aclnnGetWorkspaceSizeFunc_(
self, size_, out, &(this->atbVariantPack_.workspaceBufferSize), &rawExecutorPtr);
aclDestroyIntArray(size_);
this->aclnnExecutor_ = std::shared_ptr<aclOpExecutor>(rawExecutorPtr, [this](aclOpExecutor *ptr) {
if (ptr && this->executorRepeatable_) {
aclDestroyAclOpExecutor(ptr);
}
});
ATB_LOG(INFO) << GetLogPrefix() << "workspaceSize: " << this->atbVariantPack_.workspaceBufferSize;
return ret;
}
Status RepeatAclnnRunner::LaunchAclnnKernel()
{
ATB_LOG(INFO) << GetLogPrefix() << "LaunchAclnnKernel execute start.";
if (!RepeatAclnnRunner::aclnnExecuteFunc_) {
ATB_LOG(ERROR) << GetLogPrefix() << "Aclnn ExecuteFunc is null!";
return ERROR_INVALID_PARAM;
}
aclrtStream executeStream = GetExecuteStream(this->atbVariantPack_.context);
aclnnStatus ret = RepeatAclnnRunner::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 RepeatAclnnRunner::LoadMethod()
{
ATB_LOG(INFO) << "RepeatAclnnRunner LoadMethod";
if (RepeatAclnnRunner::aclnnGetWorkspaceSizeFunc_ != nullptr && RepeatAclnnRunner::aclnnExecuteFunc_ != nullptr) {
return NO_ERROR;
}
Status status =
LoadFromSharedObjectFile("aclnnRepeatGetWorkspaceSize", "aclnnRepeat",
RepeatAclnnRunner::aclnnGetWorkspaceSizeFunc_, RepeatAclnnRunner::aclnnExecuteFunc_);
return status;
}
REG_RUNNER_TYPE(RepeatAclnnRunner);
}