mindspore2022/mindspore/ccsrc/kernel/kernel.cc

177 lines
6.6 KiB
C++

/**
* Copyright 2021 Huawei Technologies Co., Ltd
*
* 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.
*/
#include "kernel/kernel.h"
#include <algorithm>
#include <stack>
#include "utils/ms_context.h"
#include "utils/anf_utils.h"
#include "runtime/device/ms_device_shape_transfer.h"
#include "backend/common/session/anf_runtime_algorithm.h"
#include "include/common/utils/anfalgo.h"
#include "backend/common/optimizer/helper.h"
namespace mindspore {
namespace kernel {
constexpr int64_t kInvalidShape = -2;
void KernelMod::SetAtomicCleanNodes(const std::vector<CNodePtr> &atomic_clean_node) {
atomic_clean_nodes_.resize(atomic_clean_node.size());
for (size_t i = 0; i < atomic_clean_node.size(); ++i) {
atomic_clean_nodes_[i] = atomic_clean_node[i];
}
}
void KernelMod::InferShape() {
auto node = anf_node_.lock();
MS_EXCEPTION_IF_NULL(node);
auto cnode = node->cast<CNodePtr>();
MS_EXCEPTION_IF_NULL(cnode);
MS_LOG(INFO) << "InferShape start, node:" << cnode->fullname_with_scope();
GetDepndLists(cnode);
auto ret = InferShapeForDefiniteOutputNode(cnode);
if (ret) {
return;
}
depend_tensor_map_.clear();
auto &inputs = cnode->inputs();
if (inputs.empty()) {
MS_LOG(EXCEPTION) << "Invalid inputs.";
}
auto context = MsContext::GetInstance();
MS_EXCEPTION_IF_NULL(context);
AbstractBasePtrList args_spec_list;
auto primitive = GetValueNode<PrimitivePtr>(inputs[0]);
auto input_size = common::AnfAlgo::GetInputTensorNum(cnode);
for (size_t i = 0; i < input_size; i++) {
auto input_node_with_index = common::AnfAlgo::GetPrevNodeOutput(cnode, i);
auto real_input = input_node_with_index.first;
MS_EXCEPTION_IF_NULL(real_input);
auto cnode_input = cnode->input(i + 1);
MS_EXCEPTION_IF_NULL(cnode_input);
InferShapeForNopNode(&real_input);
if (depend_list_.find(i) != depend_list_.end()) {
auto pre_node_with_index = common::AnfAlgo::GetPrevNodeOutput(cnode, i);
bool skip_nop_node = !context->get_param<bool>(MS_CTX_ENABLE_MINDRT);
auto output_addr = AnfAlgo::GetPrevNodeMutableOutputAddr(cnode, i, skip_nop_node);
std::vector<int64_t> shapes =
trans::GetRuntimePaddingShape(pre_node_with_index.first, pre_node_with_index.second);
auto host_type = common::AnfAlgo::GetOutputInferDataType(pre_node_with_index.first, pre_node_with_index.second);
auto out_tensor = std::make_shared<tensor::Tensor>(host_type, shapes);
MS_EXCEPTION_IF_NULL(out_tensor);
// The second parameter must be false, otherwise the device address cannot be released and allocated, and the
// address size will be wrong in the dynamic shape scenario.
out_tensor->set_device_address(output_addr, false);
auto ret2 = depend_tensor_map_.try_emplace(i, out_tensor);
if (!ret2.second) {
MS_LOG(EXCEPTION) << "Insert map failed.";
}
out_tensor->data_sync();
// cppcheck-suppress unreadVariable
auto lock = AnfUtils::GetAbstractLock(real_input.get());
auto real_abs = real_input->abstract();
if (real_abs->isa<abstract::AbstractTensor>()) {
real_abs->set_value(out_tensor);
} else if (real_abs->isa<abstract::AbstractTuple>()) {
auto tuple_get_item_index = common::AnfAlgo::GetTupleGetItemOutIndex(cnode_input->cast<CNodePtr>());
auto abstract_tuple = real_abs->cast<abstract::AbstractTuplePtr>();
MS_EXCEPTION_IF_NULL(abstract_tuple);
auto tuple_elements = abstract_tuple->elements()[tuple_get_item_index];
tuple_elements->set_value(out_tensor);
}
}
common::AnfAlgo::AddArgList(&args_spec_list, cnode_input, real_input, i);
}
auto eval_result = opt::CppInferShape(primitive, args_spec_list);
cnode->set_abstract(eval_result);
}
bool KernelMod::InferShapeForDefiniteOutputNode(const CNodePtr &cnode) {
MS_EXCEPTION_IF_NULL(cnode);
if (!common::AnfAlgo::CheckPrimitiveType(cnode, prim::kPrimShape)) {
return false;
}
auto input_size = common::AnfAlgo::GetInputTensorNum(cnode);
if (input_size != 1) {
MS_LOG(EXCEPTION) << "Node only has one input: " << cnode->fullname_with_scope();
}
auto cur_shape = dynamic_cast<mindspore::abstract::Shape *>(cnode->Shape().get())->shape();
if (std::any_of(cur_shape.begin(), cur_shape.end(), [](int64_t x) { return x == kInvalidShape; })) {
return false;
}
std::vector<int64_t> output_shape = {static_cast<int64_t>(cur_shape.size())};
mindspore::abstract::BaseShapePtr shape = std::make_shared<mindspore::abstract::Shape>(output_shape);
// cppcheck-suppress unreadVariable
auto lock = AnfUtils::GetAbstractLock(cnode.get());
auto abstract = cnode->abstract();
MS_EXCEPTION_IF_NULL(abstract);
abstract->set_shape(shape);
return true;
}
void KernelMod::InferShapeForNopNode(AnfNodePtr *input_node) {
MS_EXCEPTION_IF_NULL(*input_node);
if (!common::AnfAlgo::IsNopNode(*input_node) || !common::AnfAlgo::IsDynamicShape(*input_node)) {
MS_LOG(INFO) << "Input node is not a nop node, no need infer.";
return;
}
MS_LOG(INFO) << "Infer shape for nop node.";
std::stack<AnfNodePtr> nop_road;
nop_road.push(*input_node);
/*lint -e716*/
while (true) {
auto input_node_with_idx = common::AnfAlgo::GetPrevNodeOutput(*input_node, 0);
auto in_node = input_node_with_idx.first;
MS_EXCEPTION_IF_NULL(in_node);
if (common::AnfAlgo::IsNopNode(in_node)) {
nop_road.push(in_node);
*input_node = in_node;
} else {
break;
}
}
/*lint +e716*/
while (!nop_road.empty()) {
auto nop_node = nop_road.top();
MS_EXCEPTION_IF_NULL(nop_node);
AnfAlgo::InferShape(nop_node->cast<CNodePtr>());
nop_road.pop();
}
}
void KernelMod::GetDepndLists(const CNodePtr &cnode) {
MS_EXCEPTION_IF_NULL(cnode);
if (depend_list_.size() != 0) {
return;
}
auto ret = abstract::GetDependsFormMap(cnode);
if (ret.empty()) {
MS_LOG(DEBUG) << "No dynamic_shape_depends found.";
return;
}
MS_LOG(INFO) << "Have depends.";
(void)std::transform(ret.begin(), ret.end(), std::inserter(depend_list_, depend_list_.begin()),
[](const int64_t &value) { return static_cast<int>(value); });
MS_LOG(INFO) << "Init End.";
}
} // namespace kernel
} // namespace mindspore