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InfiniTensor
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xgqdut2016 2024-05-07 16:31:53 +08:00
parent 9384cec7de
commit 5747eb8f7d
1 changed files with 25 additions and 29 deletions
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20
src/kernels/ascend/pad2d.cc
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@ -1,7 +1,7 @@
#include "operators/pad.h"
#include "aclnnop/level2/aclnn_reflection_pad2d.h" #include "aclnnop/level2/aclnn_reflection_pad2d.h"
#include "ascend/ascend_kernel_without_config.h" #include "ascend/ascend_kernel_without_config.h"
#include "ascend/ascend_runtime.h" #include "ascend/ascend_runtime.h"
#include "operators/pad.h"
namespace infini { namespace infini {
@ -12,7 +12,6 @@ class PadAclnn : public ASCENDKernelWithoutConfig {
auto op = as<PadObj>(_op); auto op = as<PadObj>(_op);
auto context = dynamic_cast<const ASCENDRuntimeObj *>(_context); auto context = dynamic_cast<const ASCENDRuntimeObj *>(_context);
void *const aData = (op->getInputs(0)->getRawDataPtr<void *>()); void *const aData = (op->getInputs(0)->getRawDataPtr<void *>());
void *const cData = (op->getOutput()->getRawDataPtr<void *>()); void *const cData = (op->getOutput()->getRawDataPtr<void *>());
@ -45,16 +44,16 @@ class PadAclnn : public ASCENDKernelWithoutConfig {
std::size_t length = intPads.size(); std::size_t length = intPads.size();
std::vector<int64_t> pads(4); std::vector<int64_t> pads(4);
if(length == 8){ if (length == 8) {
std::size_t halfLen = intPads.size() / 2; std::size_t halfLen = intPads.size() / 2;
bool condition = true; bool condition = true;
//std::cout << "Length of intPads: " << length << std::endl; // std::cout << "Length of intPads: " << length << std::endl;
for (std::size_t i = 0; i < halfLen; ++i) { for (std::size_t i = 0; i < halfLen; ++i) {
condition = (intPads[i] == intPads[i + 4]); condition = (intPads[i] == intPads[i + 4]);
//std::cout << "intPads[" << i << "]: " << intPads[i] << std::endl; // std::cout << "intPads[" << i << "]: " << intPads[i] <<
// std::endl;
} }
assert(condition); assert(condition);
@ -62,19 +61,16 @@ class PadAclnn : public ASCENDKernelWithoutConfig {
pads[1] = intPads[3]; pads[1] = intPads[3];
pads[2] = intPads[6]; pads[2] = intPads[6];
pads[3] = intPads[7]; pads[3] = intPads[7];
} } else if (length == 4) {
else if (length == 4){
for (std::size_t i = 0; i < 4; ++i) { for (std::size_t i = 0; i < 4; ++i) {
pads[i] = intPads[i]; pads[i] = intPads[i];
} }
} }
aclIntArray *padding = aclCreateIntArray(pads.data(), 4); aclIntArray *padding = aclCreateIntArray(pads.data(), 4);
auto ret = aclnnReflectionPad2dGetWorkspaceSize( auto ret = aclnnReflectionPad2dGetWorkspaceSize(
inputTensor, padding , outputTensor, inputTensor, padding, outputTensor, &workspaceSize, &executor);
&workspaceSize, &executor);
void *workspaceAddr = nullptr; void *workspaceAddr = nullptr;
if (workspaceSize > 0) { if (workspaceSize > 0) {
workspaceAddr = context->getWorkspace(workspaceSize); workspaceAddr = context->getWorkspace(workspaceSize);
@ -85,7 +81,7 @@ class PadAclnn : public ASCENDKernelWithoutConfig {
} }
assert(ret == ACL_SUCCESS); assert(ret == ACL_SUCCESS);
ret = aclnnReflectionPad2d(workspaceAddr, workspaceSize, executor, ret = aclnnReflectionPad2d(workspaceAddr, workspaceSize, executor,
context->ASCENDHandle()); context->ASCENDHandle());
assert(ret == ACL_SUCCESS); assert(ret == ACL_SUCCESS);
ret = aclrtSynchronizeStream(context->ASCENDHandle()); ret = aclrtSynchronizeStream(context->ASCENDHandle());