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Pre Merge pull request !1708 from 王强/master

pull/1708/MERGE
王强 Gitee 4 years ago
parent
6f10b37e21 62250916b2
commit
8167509b6a
7 changed files with 1137 additions and 42 deletions
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  1. +4
    -0
      ge/CMakeLists.txt
  2. +636
    -0
      ge/graph/passes/infer_base_pass.cc
  3. +51
    -0
      ge/graph/passes/infer_base_pass.h
  4. +408
    -28
      ge/graph/passes/infershape_pass.cc
  5. +28
    -11
      ge/graph/passes/infershape_pass.h
  6. +4
    -2
      ge/hybrid/executor/worker/shape_inference_engine.cc
  7. +6
    -1
      tests/ut/ge/CMakeLists.txt

+ 4
- 0
ge/CMakeLists.txt View File

@@ -298,7 +298,9 @@ set(TRAIN_SRC_LIST
"graph/passes/hccl_continuous_memcpy_pass.cc"
"graph/passes/identity_pass.cc"
"graph/passes/ref_identity_delete_op_pass.cc"
"graph/passes/infer_base_pass.cc"
"graph/passes/infershape_pass.cc"
#"graph/passes/infer_value_range_pass.cc"
"graph/passes/iterator_op_pass.cc"
"graph/passes/link_gen_mask_nodes_pass.cc"
"graph/passes/merge_pass.cc"
@@ -552,7 +554,9 @@ set(INFER_SRC_LIST
"graph/passes/shape_operate_op_remove_pass.cc"
"graph/passes/assert_pass.cc"
"graph/passes/dropout_pass.cc"
"graph/passes/infer_base_pass.cc"
"graph/passes/infershape_pass.cc"
#"graph/passes/infer_value_range_pass.cc"
"graph/passes/unused_const_pass.cc"
"graph/passes/permute_pass.cc"
"graph/passes/ctrl_edge_transfer_pass.cc"


+ 636
- 0
ge/graph/passes/infer_base_pass.cc View File

@@ -0,0 +1,636 @@
/**
* 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 "infer_base_pass.h"
#include "common/ge/ge_util.h"
#include "common/util/error_manager/error_manager.h"
#include "framework/common/debug/ge_log.h"
#include "framework/common/util.h"
#include "graph/debug/ge_attr_define.h"
#include "graph/debug/ge_util.h"
#include "graph/utils/graph_utils.h"
#include "graph/utils/node_utils.h"
#include "graph/utils/tensor_utils.h"
#include "graph/utils/type_utils.h"

namespace ge {
namespace {
string Serial(const vector<int64_t> &dims) {
string serial_string;
serial_string += "[";
for (int64_t dim : dims) {
serial_string += std::to_string(dim) + " ";
}
serial_string += "]";
return serial_string;
}
void SerialShapeRange(const GeTensorDescPtr &desc, std::string &desc_str) {
desc_str += "[";
std::vector<std::pair<int64_t, int64_t>> shape_range;
(void)desc->GetShapeRange(shape_range);
for (const auto &pair : shape_range) {
desc_str += "{";
desc_str += std::to_string(pair.first) + "," + std::to_string(pair.second);
desc_str += "},";
}
desc_str += "]";
shape_range.clear();
(void)desc->GetOriginShapeRange(shape_range);
for (const auto &pair : shape_range) {
desc_str += ",{";
desc_str += std::to_string(pair.first) + "," + std::to_string(pair.second);
desc_str += "},";
}
}
graphStatus FindSubgraphDataAndNetoutput(std::shared_ptr<ComputeGraph> &sub_graph, NodePtr &netoutput,
const ConstNodePtr &node,
std::vector<std::vector<GeTensorDesc>> &ref_data_tensors) {
auto sub_nodes = sub_graph->GetDirectNode();
for (size_t i = sub_nodes.size(); i > 0; --i) {
auto sub_node = sub_nodes.at(i - 1);
if (sub_node->GetType() == NETOUTPUT) {
netoutput = sub_node;
}
if (sub_node->GetType() == DATA) {
if (sub_node->GetOpDesc() == nullptr) {
return GRAPH_FAILED;
}

int ref_i;
if (!AttrUtils::GetInt(sub_node->GetOpDesc(), ATTR_NAME_PARENT_NODE_INDEX, ref_i)) {
REPORT_INNER_ERROR("E19999", "subgraph data node[%s] has no parent node!", sub_node->GetName().c_str());
GELOGE(GRAPH_FAILED, "[Get][Int] subgraph data node[%s] has no parent node!", sub_node->GetName().c_str());
return GRAPH_FAILED;
}
if (ref_i < 0 || static_cast<uint32_t>(ref_i) >= node->GetAllInDataAnchorsSize()) {
REPORT_INNER_ERROR("E19999", "data node[%s]'s ref index[%d] is not in range [0, %u)!",
sub_node->GetName().c_str(), ref_i, node->GetAllInDataAnchorsSize());
GELOGE(GRAPH_FAILED, "[Check][Param] data node[%s]'s ref index[%d] is not in range [0, %u)!",
sub_node->GetName().c_str(), ref_i, node->GetAllInDataAnchorsSize());
return GRAPH_FAILED;
}
ref_data_tensors[ref_i].emplace_back(sub_node->GetOpDesc()->GetOutputDesc(0));
}
}
return GRAPH_SUCCESS;
}
} // namespace

Status InferBasePass::Run(NodePtr &node) {
GE_CHECK_NOTNULL(node);
GE_CHECK_NOTNULL(node->GetOpDesc());

bool need_infer = NeedInfer(node);
if (!need_infer) {
GELOGD("Node %s does not need to infer.", node->GetName().c_str());
return SUCCESS;
}

std::set<NodePtr> changed_nodes;
auto ret = InferAndUpdate(node, !OptionExists(kOptimizeAfterSubGraph), changed_nodes);
if (ret != GRAPH_SUCCESS) {
(void)AnalyzeFailedInfo(node);
return GE_GRAPH_INFERSHAPE_FAILED;
}

// AddChangedNodesImmediateRepass(changed_nodes);
auto status = DoRepassForLoopNode(node);
if (status != SUCCESS) {
GELOGE(GE_GRAPH_INFERSHAPE_FAILED, "repass failed. node: %s", node->GetName().c_str());
return GE_GRAPH_INFERSHAPE_FAILED;
}
return SUCCESS;
}

bool InferBasePass::NeedInfer(const NodePtr &node) { return true; }
void InferBasePass::AnalyzeFailedInfo(const NodePtr &node) { /* Analyze and select failed info*/ }
Status InferBasePass::DoRepassForLoopNode(NodePtr &node) { return SUCCESS; }
void InferBasePass::AddChangedNodesImmediateRepass(std::set<NodePtr> &changed_nodes) {
for (const auto &node_ele : changed_nodes) {
AddImmediateRePassNode(node_ele);
}
}

graphStatus InferBasePass::InferAndUpdate(NodePtr &node, bool before_subgraph, std::set<NodePtr> &changed_nodes) {
bool contain_subgraph = ContainsSubgraph(node);
if (contain_subgraph && before_subgraph) {
auto ret = UpdateTensorDescToSubgraphData(node, changed_nodes);
if (ret != GRAPH_SUCCESS) {
return ret;
}
}
auto ret = Infer(node);
if (ret != GRAPH_SUCCESS) {
return ret;
}
if (contain_subgraph && !before_subgraph) {
return UpdateTensorDescToParentNode(node, changed_nodes);
}

return UpdateTensorDescToPeerInputs(node, changed_nodes);
}

bool InferBasePass::ContainsSubgraph(const NodePtr &node) {
auto op_desc = node->GetOpDesc();
auto sub_graph_names = op_desc->GetSubgraphInstanceNames();
if (sub_graph_names.empty()) {
return false;
}

auto root_graph = GraphUtils::FindRootGraph(node->GetOwnerComputeGraph());
for (const auto &name : sub_graph_names) {
if (name.empty()) {
continue;
}
auto sub_graph = root_graph->GetSubgraph(name);
if (sub_graph != nullptr) {
return true;
}
}
return false;
}

graphStatus InferBasePass::UpdateTensorDescToSubgraphData(NodePtr &node, std::set<NodePtr> &changed_nodes) {
// if infer again, update output of while into subgraph data node
auto op_desc = node->GetOpDesc();
auto sub_graph_names = op_desc->GetSubgraphInstanceNames();
if (sub_graph_names.empty()) {
return GRAPH_SUCCESS;
}

auto root_graph = GraphUtils::FindRootGraph(node->GetOwnerComputeGraph());
for (const auto &name : sub_graph_names) {
if (name.empty()) {
GELOGW("The node %s contains empty subgraph instance name", node->GetName().c_str());
continue;
}
auto sub_graph = root_graph->GetSubgraph(name);
if (sub_graph == nullptr) {
REPORT_INNER_ERROR("E19999", "Can not find the subgrpah %s for node %s", name.c_str(), node->GetName().c_str());
GE_LOGE("[Get][Graph] can not find the subgrpah %s for node %s", name.c_str(), node->GetName().c_str());
return GRAPH_FAILED;
}
for (const auto &node_sub : sub_graph->GetDirectNode()) {
if (node_sub->GetType() != DATA) {
continue;
}
int ref_i;
auto data_opdesc = node_sub->GetOpDesc();
if (data_opdesc == nullptr) {
REPORT_INNER_ERROR("E19999", "Invalid data node on the sub graph %s parent node %s, no OpDesc", name.c_str(),
node->GetName().c_str());
GE_LOGE("[Get][OpDesc] Invalid data node on the sub graph %s parent node %s, no OpDesc", name.c_str(),
node->GetName().c_str());
return GRAPH_FAILED;
}
if (!AttrUtils::GetInt(data_opdesc, ATTR_NAME_PARENT_NODE_INDEX, ref_i)) {
REPORT_INNER_ERROR("E19999", "Invalid data node on the sub graph %s parent node %s, no ref-index attribute",
name.c_str(), node->GetName().c_str());
GE_LOGE("[Get][Int] Invalid data node on the sub graph %s parent node %s, no ref-index attribute", name.c_str(),
node->GetName().c_str());
return GRAPH_FAILED;
}
if (data_opdesc->HasAttr(ATTR_MBATCH_ORIGIN_INPUT_DIMS)) {
continue;
}
auto input_desc = op_desc->MutableInputDesc(ref_i);
if (input_desc == nullptr) {
REPORT_INNER_ERROR("E19999",
"The ref index(%d) on the data %s on the sub graph %s "
"parent node %s are incompatible, inputs num %u",
ref_i, node_sub->GetName().c_str(), name.c_str(), node->GetName().c_str(),
node->GetAllInDataAnchorsSize());
GE_LOGE(
"[Call][MutableInputDesc] The ref index(%d) on the data %s on the sub graph %s "
"parent node %s are incompatible, inputs num %u",
ref_i, node_sub->GetName().c_str(), name.c_str(), node->GetName().c_str(), node->GetAllInDataAnchorsSize());
return GRAPH_FAILED;
}
GELOGI("Ref index is %d, input_desc dtype is %d, node name is %s", ref_i, input_desc->GetDataType(),
node->GetName().c_str());

// if need infer again, refresh subgraph input with output
bool is_infer_again = false;
AttrUtils::GetBool(node->GetOpDesc(), ATTR_NAME_NEED_INFER_AGAIN, is_infer_again);
if (is_infer_again) {
input_desc = op_desc->MutableOutputDesc(ref_i);
if (input_desc == nullptr) {
REPORT_INNER_ERROR("E19999",
"The ref index(%d) on the data %s on the subgraph %s "
"parent node %s are incompatible, outputs num %u.",
ref_i, node_sub->GetName().c_str(), name.c_str(), node->GetName().c_str(),
node->GetAllOutDataAnchorsSize());
GELOGE(PARAM_INVALID,
"[Call][MutableOutputDesc] The ref index(%d) on the data %s on the subgraph %s "
"parent node %s are incompatible, outputs num %u.",
ref_i, node_sub->GetName().c_str(), name.c_str(), node->GetName().c_str(),
node->GetAllOutDataAnchorsSize());
}
GELOGD("Update input desc of data %s on the sub graph %s of node %s,output idx: %d from [%s] to [%s]",
node_sub->GetName().c_str(), name.c_str(), node->GetName().c_str(), ref_i,
data_opdesc->GetInputDescPtr(0)->GetShape().ToString().c_str(),
input_desc->GetShape().ToString().c_str());
}

// auto ret = data_opdesc->UpdateInputDesc(0, *input_desc);
bool input_changed = false;
auto data_input_desc = data_opdesc->MutableInputDesc(0);
auto ret = UpdateTensorDesc(input_desc, data_input_desc,input_changed);
if (ret != GRAPH_SUCCESS) {
REPORT_CALL_ERROR("E19999", "Failed to update input desc of data %s on the sub graph %s parent node %s",
node_sub->GetName().c_str(), name.c_str(), node->GetName().c_str());
GE_LOGE("[Update][InputDesc] of data %s on the sub graph %s parent node %s failed", node_sub->GetName().c_str(),
name.c_str(), node->GetName().c_str());
return ret;
}

// ret = data_opdesc->UpdateOutputDesc(0, *input_desc);
bool output_changed = false;
auto data_output_desc = data_opdesc->MutableOutputDesc(0);
ret = UpdateTensorDesc(input_desc, data_output_desc,output_changed);
if (ret != GRAPH_SUCCESS) {
REPORT_CALL_ERROR("E19999", "Failed to update output desc of data %s on the sub graph %s parent node %s",
node_sub->GetName().c_str(), name.c_str(), node->GetName().c_str());
GE_LOGE("[Update][OutputDesc] of data %s on the sub graph %s parent node %s failed",
node_sub->GetName().c_str(), name.c_str(), node->GetName().c_str());
return ret;
}

if (input_changed || output_changed) {
changed_nodes.insert(node_sub);
}
}
}
return GRAPH_SUCCESS;
}

graphStatus InferBasePass::UpdateTensorDescToParentNode(NodePtr &node, std::set<NodePtr> &changed_nodes) {
auto op_desc = node->GetOpDesc();
auto sub_graph_names = op_desc->GetSubgraphInstanceNames();
if (sub_graph_names.empty()) {
return GRAPH_SUCCESS;
}

std::vector<std::vector<GeTensorDesc>> ref_data_tensors(node->GetAllInDataAnchorsSize());
std::vector<std::vector<GeTensorDesc>> ref_out_tensors(node->GetAllOutDataAnchorsSize());
auto root_graph = GraphUtils::FindRootGraph(node->GetOwnerComputeGraph());

for (const auto &name : sub_graph_names) {
if (name.empty()) {
GELOGW("The node %s contains empty subgraph instance name", node->GetName().c_str());
continue;
}
auto sub_graph = root_graph->GetSubgraph(name);
if (sub_graph == nullptr) {
REPORT_INNER_ERROR("E19999", "Can not find the subgrpah %s for node %s", name.c_str(), node->GetName().c_str());
GE_LOGE("[Get][Subgraph] Can not find the subgrpah %s for node %s", name.c_str(), node->GetName().c_str());
return GRAPH_FAILED;
}
NodePtr netoutput = nullptr;
auto ret = FindSubgraphDataAndNetoutput(sub_graph, netoutput, node, ref_data_tensors);
if (ret != GRAPH_SUCCESS) {
return ret;
}
if (netoutput == nullptr) {
REPORT_INNER_ERROR("E19999", "No NetOutput node on sub graph %s, parent node %s", name.c_str(),
node->GetName().c_str());
GE_LOGE("[Check][Param] No NetOutput node on sub graph %s, parent node %s", name.c_str(),
node->GetName().c_str());
return GRAPH_FAILED;
}
auto netoutput_opdesc = netoutput->GetOpDesc();
if (netoutput_opdesc == nullptr) {
REPORT_INNER_ERROR("E19999", "Invalid NetOutput node on sub graph %s, parent node %s, no OpDesc on it",
name.c_str(), node->GetName().c_str());
GE_LOGE("[Get][OpDesc] Invalid NetOutput node on sub graph %s, parent node %s, no OpDesc on it", name.c_str(),
node->GetName().c_str());
return GRAPH_FAILED;
}
for (auto &edge_anchor : netoutput->GetAllInDataAnchors()) {
auto edge_desc = netoutput_opdesc->MutableInputDesc(edge_anchor->GetIdx());
if (edge_desc == nullptr) {
REPORT_INNER_ERROR("E19999",
"Invalid NetOutput node on sub graph %s, parent node %s, "
"can not find input tensor %d",
name.c_str(), node->GetName().c_str(), edge_anchor->GetIdx());
GE_LOGE("[Get][Tensor] Invalid NetOutput node on sub graph %s, parent node %s, can not find input tensor %d",
name.c_str(), node->GetName().c_str(), edge_anchor->GetIdx());
return GRAPH_FAILED;
}
GELOGI("Netoutput in anchor index is %d, input tensor dim is %zu", edge_anchor->GetIdx(),
edge_desc->GetShape().GetDimNum());
int ref_i;
if (!AttrUtils::GetInt(edge_desc, ATTR_NAME_PARENT_NODE_INDEX, ref_i)) {
// if there is no ref index on the TensorDesc, it means the output data will be ignored outer.
continue;
}
GELOGI("Parent node index of edge desc is %d", ref_i);
if (ref_i < 0 || static_cast<uint32_t>(ref_i) >= node->GetAllOutDataAnchorsSize()) {
return GRAPH_FAILED;
}
ref_out_tensors[ref_i].emplace_back(*edge_desc);
}
}

if (node->GetType() == WHILE) {
return UpdateParentNodeForWhile(node, ref_data_tensors, ref_out_tensors, changed_nodes);
}
return UpdateParentNodeForBranch(node, ref_out_tensors, changed_nodes);
}

graphStatus InferBasePass::UpdateParentNodeForWhile(NodePtr &node,
std::vector<std::vector<GeTensorDesc>> &ref_data_tensors,
std::vector<std::vector<GeTensorDesc>> &ref_out_tensors,
std::set<NodePtr> &changed_nodes) {
GELOGD("Enter update parent node shape for class while op process");
if (ref_data_tensors.size() != ref_out_tensors.size()) {
REPORT_INNER_ERROR("E19999", "op:%s(%s) input number[%zu] and output number[%zu] is not same!",
node->GetName().c_str(), node->GetType().c_str(), ref_data_tensors.size(),
ref_out_tensors.size());
GELOGE(GRAPH_FAILED, "[Check][Param] while op [%s] input number[%zu] and output number[%zu] is not same!",
node->GetName().c_str(), ref_data_tensors.size(), ref_out_tensors.size());
return GRAPH_FAILED;
}
for (size_t i = 0; i < ref_data_tensors.size(); i++) {
if (ref_out_tensors[i].size() != 1) {
REPORT_INNER_ERROR("E19999", "while op, every output should only find one output tensor in all graph!");
GELOGE(GRAPH_FAILED, "[Check][Param] while op, every output should only find one output tensor in all graph!");
return GRAPH_FAILED;
}
}
bool need_infer_again = false;
// check input and output
for (size_t i = 0; i < ref_out_tensors.size(); i++) {
if (ref_out_tensors[i].empty()) {
continue;
}
auto ref_out_tensor = ref_out_tensors[i].at(0);
auto out_shape = ref_out_tensor.MutableShape();
vector<std::pair<int64_t, int64_t>> data_shape_range;
// ref_i's data and output tensor shape should be same
for (auto &tensor : ref_data_tensors[i]) {
if (ref_out_tensor.GetDataType() != tensor.GetDataType()) {
REPORT_INNER_ERROR("E19999", "node[%s] does not support diff dtype or format among all ref output",
node->GetName().c_str());
GELOGE(GRAPH_FAILED, "[Check][Param] node[%s] does not support diff dtype or format output.",
node->GetName().c_str());
return GRAPH_FAILED;
}
auto data_shape = tensor.MutableShape();
// input is dynamic, here use dim_num
if (data_shape.GetDims() != out_shape.GetDims()) {
GELOGI("After infer, While %s %zu output shape [%s] is not match with input shape [%s].Need infer again.",
node->GetName().c_str(), i, out_shape.ToString().c_str(), data_shape.ToString().c_str());
if (data_shape.GetDimNum() != out_shape.GetDimNum()) {
ref_out_tensor.SetUnknownDimNumShape();
} else {
for (size_t j = 0; j < data_shape.GetDimNum(); ++j) {
if (data_shape.GetDim(j) != out_shape.GetDim(j)) {
if (data_shape.GetDim(j) != UNKNOWN_DIM) {
// if input data is fix shape, output is different, need_infer_again
need_infer_again = true;
}
data_shape.SetDim(j, UNKNOWN_DIM);
}
// set shape rang of while, if dim is unknown ,set shape range as {1,-1}
if (data_shape.GetDim(j) == UNKNOWN_DIM) {
data_shape_range.emplace_back(std::make_pair(1, UNKNOWN_DIM));
} else {
data_shape_range.emplace_back(std::make_pair(data_shape.GetDim(j), data_shape.GetDim(j)));
}
}
ref_out_tensor.SetShape(data_shape);
ref_out_tensor.SetShapeRange(data_shape_range);
}
}
}
//(void)node->GetOpDesc()->UpdateOutputDesc(i, ref_out_tensor);
bool output_changed = false;
auto output_desc = node->GetOpDesc()->MutableOutputDesc(i);
(void)UpdateTensorDesc(ComGraphMakeShared<GeTensorDesc>(ref_out_tensor), output_desc,output_changed);
if (output_changed) {
changed_nodes.insert(node);
}
}
AttrUtils::SetBool(node->GetOpDesc(), ATTR_NAME_NEED_INFER_AGAIN, need_infer_again);
return GRAPH_SUCCESS;
}

graphStatus InferBasePass::UpdateOutputForMultiBatch(NodePtr &node,
std::vector<std::vector<GeTensorDesc>> &ref_out_tensors,
std::set<NodePtr> &changed_nodes) {
// check sub_graph shape. Get max for update.
for (size_t i = 0; i < ref_out_tensors.size(); ++i) {
if (ref_out_tensors[i].empty()) {
continue;
}

int64_t max_size = 0;
size_t max_shape_index = 0;
auto &ref_out_tensor = ref_out_tensors[i].at(0);
for (size_t j = 0; j < ref_out_tensors[i].size(); ++j) {
auto &tensor = ref_out_tensors[i].at(j);
if (ref_out_tensor.GetDataType() != tensor.GetDataType()) {
REPORT_INNER_ERROR("E19999", "node[%s] does not support diff dtype among all ref output",
node->GetName().c_str());
GELOGE(GRAPH_FAILED, "[Check][Param] node[%s] does not support diff dtype among all ref output",
node->GetName().c_str());
return GRAPH_FAILED;
}

auto shape = tensor.MutableShape();
int64_t size = 1;
for (auto dim : shape.GetDims()) {
if (dim != 0 && INT64_MAX / dim < size) {
REPORT_INNER_ERROR("E19999", "The shape:%s size overflow, node:%s", shape.ToString().c_str(),
node->GetName().c_str());
GELOGE(PARAM_INVALID, "[Check][Overflow] The shape size overflow");
return PARAM_INVALID;
}
size *= dim;
}

if (size > max_size) {
max_size = size;
max_shape_index = j;
}
}

//(void)node->GetOpDesc()->UpdateOutputDesc(i, ref_out_tensors[i].at(max_shape_index));
bool output_changed = false;
auto output_desc = node->GetOpDesc()->MutableOutputDesc(i);
(void)UpdateTensorDesc(ComGraphMakeShared<GeTensorDesc>(ref_out_tensors[i].at(max_shape_index)), output_desc,
output_changed);
if (output_changed) {
changed_nodes.insert(node);
}
}

return GRAPH_SUCCESS;
}

graphStatus InferBasePass::UpdateParentNodeForBranch(NodePtr &node,
std::vector<std::vector<GeTensorDesc>> &ref_out_tensors,
std::set<NodePtr> &changed_nodes) {
GELOGD("Enter update parent node shape for class branch op process");
if (node->GetOpDesc()->HasAttr(ATTR_NAME_BATCH_NUM)) {
return UpdateOutputForMultiBatch(node, ref_out_tensors, changed_nodes);
}

// check sub_graph shape.If not same ,do unknown shape process
for (size_t i = 0; i < ref_out_tensors.size(); i++) {
if (ref_out_tensors[i].empty()) {
continue;
}
auto ref_out_tensor = ref_out_tensors[i].at(0);
ge::GeShape &ref_out_tensor_shape = ref_out_tensor.MutableShape();
for (auto &tensor : ref_out_tensors[i]) {
if (ref_out_tensor.GetDataType() != tensor.GetDataType()) {
REPORT_INNER_ERROR("E19999", "node[%s] does not support diff dtype among all ref output, shape:%s",
node->GetName().c_str(), ref_out_tensor_shape.ToString().c_str());
GELOGE(GRAPH_FAILED, "[Check][Param] node[%s] does not support diff dtype output", node->GetName().c_str());
return GRAPH_FAILED;
}
auto shape = tensor.MutableShape();
if (shape.GetDims().size() != ref_out_tensor_shape.GetDims().size()) {
GELOGD("node is %s, i : %zu, shape size: %lu, ref_out_tensor_shape size: %lu", node->GetName().c_str(), i,
shape.GetShapeSize(), ref_out_tensor_shape.GetShapeSize());
ref_out_tensor_shape = GeShape(UNKNOWN_RANK);
break;
}
for (size_t j = 0; j < ref_out_tensor_shape.GetDims().size(); j++) {
if (ref_out_tensor_shape.GetDim(j) == shape.GetDim(j)) {
continue;
}
GELOGD("node is %s, i : %zu, j: %zu ,shape size: %lu, ref_out_tensor_shape size: %lu", node->GetName().c_str(),
i, j, shape.GetShapeSize(), ref_out_tensor_shape.GetShapeSize());
(void)ref_out_tensor_shape.SetDim(j, UNKNOWN_DIM);
}
}
//(void)node->GetOpDesc()->UpdateOutputDesc(i, ref_out_tensor);
bool output_changed = false;
auto output_desc = node->GetOpDesc()->MutableOutputDesc(i);
(void)UpdateTensorDesc(ComGraphMakeShared<GeTensorDesc>(ref_out_tensor), output_desc, output_changed);
if (output_changed) {
changed_nodes.insert(node);
}
}
return GRAPH_SUCCESS;
}

graphStatus InferBasePass::UpdateTensorDescToPeerInputs(NodePtr &node, std::set<NodePtr> &changed_nodes) {
auto op_desc = node->GetOpDesc();
bool is_unknown_graph = node->GetOwnerComputeGraph()->GetGraphUnknownFlag();
if (is_unknown_graph) {
return GRAPH_SUCCESS;
}
for (const auto &out_anchor : node->GetAllOutDataAnchors()) {
auto output_tensor = op_desc->MutableOutputDesc(out_anchor->GetIdx());
for (const auto &peer_anchor : out_anchor->GetPeerInDataAnchors()) {
auto peer_anchor_opdesc = peer_anchor->GetOwnerNode()->GetOpDesc();
if (peer_anchor_opdesc == nullptr) {
continue;
}
if (op_desc->GetId() < peer_anchor_opdesc->GetId() || peer_anchor_opdesc->GetType() == CONSTANT ||
peer_anchor_opdesc->GetType() == CONSTANTOP) {
continue;
}
auto peer_input_desc = peer_anchor_opdesc->MutableInputDesc(peer_anchor->GetIdx());
if (peer_input_desc == nullptr) {
continue;
}

bool changed = false;
auto ret = UpdateDescAttrForPeerInput(output_tensor, peer_input_desc, changed);
if (ret != GRAPH_SUCCESS) {
REPORT_CALL_ERROR("E19999", "Failed to update peer tensor desc attr");
GE_LOGE("[Update][PeerInputDesc] Failed to update peer tensor desc attr");
return ret;
}
if (changed) {
changed_nodes.insert(peer_anchor->GetOwnerNode());
}
}
}
PrintInOutTensorShape(node, "after_infer");
return GRAPH_SUCCESS;
}

graphStatus InferBasePass::UpdateDescAttrForPeerInput(const GeTensorDescPtr &src, GeTensorDescPtr dst, bool &changed){
changed = false;
return GRAPH_SUCCESS;
}

void InferBasePass::PrintInOutTensorShape(const NodePtr &node, const std::string &phase) {
if (!IsLogEnable(GE, DLOG_DEBUG)) {
return;
}
if (node == nullptr) {
REPORT_INNER_ERROR("E19999", "param node is nullprt, check invalid");
GELOGE(GRAPH_FAILED, "[Check][Param] node is null");
return;
}
ge::OpDescPtr op_desc = node->GetOpDesc();
GE_IF_BOOL_EXEC(op_desc == nullptr, REPORT_INNER_ERROR("E19999", "node has no opdesc, check invalid");
GELOGE(GRAPH_FAILED, "[Get][OpDesc] op_desc is null."); return );
std::stringstream ss;
ss << "{";
int32_t in_idx = 0;
int32_t out_idx = 0;
for (const auto &input_desc : op_desc->GetAllInputsDescPtr()) {
if (input_desc == nullptr) {
in_idx++;
continue;
}
if (in_idx > 0) {
ss << " ";
}
ss << "input_" << in_idx << " "
<< "tensor: [";
ss << "(shape:[" << input_desc->MutableShape().ToString() << "]),";
ss << "(format:" << TypeUtils::FormatToSerialString(input_desc->GetFormat()) << "),";
ss << "(dtype:" << TypeUtils::DataTypeToSerialString(input_desc->GetDataType()) << "),";
ss << "(origin_shape:" << input_desc->GetOriginShape().ToString() << "),";
ss << "(origin_format:" << TypeUtils::FormatToSerialString(input_desc->GetOriginFormat()) << "),";
ss << "(origin_dtype:" << TypeUtils::DataTypeToSerialString(input_desc->GetOriginDataType()) << "),";
string range_str;
SerialShapeRange(input_desc, range_str);
ss << "(shape_range:" << range_str << ")]";
in_idx++;
}
for (const auto &output_desc : op_desc->GetAllOutputsDescPtr()) {
if (output_desc == nullptr) {
out_idx++;
continue;
}
ss << " ";
ss << "output_" << out_idx << " "
<< "tensor: [";
ss << "(shape:[" << output_desc->MutableShape().ToString() << "]),";
ss << "(format:" << TypeUtils::FormatToSerialString(output_desc->GetFormat()) << "),";
ss << "(dtype:" << TypeUtils::DataTypeToSerialString(output_desc->GetDataType()) << "),";
ss << "(origin_shape:" << output_desc->GetOriginShape().ToString() << "),";
ss << "(origin_format:" << TypeUtils::FormatToSerialString(output_desc->GetOriginFormat()) << "),";
ss << "(origin_dtype:" << TypeUtils::DataTypeToSerialString(output_desc->GetOriginDataType()) << "),";
string range_str;
SerialShapeRange(output_desc, range_str);
ss << "(shape_range:" << range_str << ")]";
out_idx++;
}
ss << "}";
GELOGD("Shape dump [%s], Node name: [%s]. %s", phase.c_str(), node->GetName().c_str(), ss.str().c_str());
}
} // namespace ge

+ 51
- 0
ge/graph/passes/infer_base_pass.h View File

@@ -0,0 +1,51 @@
/**
* 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.
*/
#ifndef GE_GRAPH_PASSES_INFER_BASE_PASS_H_
#define GE_GRAPH_PASSES_INFER_BASE_PASS_H_

#include "graph/passes/base_pass.h"

namespace ge {
class InferBasePass : public BaseNodePass {
public:
Status Run(NodePtr &node) override;
graphStatus InferAndUpdate(NodePtr &node, bool before_subgraph, std::set<NodePtr> &changed_nodes);
void PrintInOutTensorShape(const NodePtr &node, const std::string &phase);

protected:
virtual graphStatus Infer(NodePtr &node) = 0;
virtual graphStatus UpdateTensorDesc(const GeTensorDescPtr &src, GeTensorDescPtr dst, bool &changed) = 0;
virtual graphStatus UpdateDescAttrForPeerInput(const GeTensorDescPtr &src, GeTensorDescPtr dst, bool &changed);
virtual bool NeedInfer(const NodePtr &node);
virtual void AnalyzeFailedInfo(const NodePtr &node);
virtual Status DoRepassForLoopNode(NodePtr &node); // only for test inferXBase, will be deleted

private:
void AddChangedNodesImmediateRepass(std::set<NodePtr> &changed_nodes);
bool ContainsSubgraph(const NodePtr &node);
graphStatus UpdateTensorDescToSubgraphData(NodePtr &node, std::set<NodePtr> &changed_nodes);
graphStatus UpdateTensorDescToParentNode(NodePtr &node, std::set<NodePtr> &changed_nodes);
graphStatus UpdateParentNodeForWhile(NodePtr &node, std::vector<std::vector<GeTensorDesc>> &ref_data_tensors,
std::vector<std::vector<GeTensorDesc>> &ref_out_tensors,
std::set<NodePtr> &changed_nodes);
graphStatus UpdateParentNodeForBranch(NodePtr &node, std::vector<std::vector<GeTensorDesc>> &ref_out_tensors,
std::set<NodePtr> &changed_nodes);
graphStatus UpdateOutputForMultiBatch(NodePtr &node, std::vector<std::vector<GeTensorDesc>> &ref_out_tensors,
std::set<NodePtr> &changed_nodes);
graphStatus UpdateTensorDescToPeerInputs(NodePtr &node, std::set<NodePtr> &changed_nodes);
};
} // namespace ge
#endif // GE_GRAPH_PASSES_INFER_BASE_PASS_H_

+ 408
- 28
ge/graph/passes/infershape_pass.cc View File

@@ -19,15 +19,84 @@
#include "framework/common/debug/ge_log.h"
#include "analyzer/analyzer.h"
#include "framework/common/util.h"
#include "graph/shape_refiner.h"
#include "graph/utils/graph_utils.h"
#include "graph/utils/node_utils.h"
#include "graph/common/omg_util.h"
#include "graph/debug/ge_attr_define.h"
#include "utils/tensor_utils.h"
#include "utils/type_utils.h"
#include "graph/debug/ge_util.h"
#include "graph/operator_factory_impl.h"
#include "graph/utils/graph_utils.h"
#include "graph/utils/node_utils.h"
#include "graph/utils/tensor_utils.h"
#include "graph/utils/type_utils.h"

namespace ge {
namespace {
const char *const kPreOpInputShapeRange = "_pre_op_in_range";
thread_local std::unordered_map<NodePtr, InferenceContextPtr> context_map;
}

GE_FUNC_DEV_VISIBILITY GE_FUNC_HOST_VISIBILITY void InferShapePass::ClearContextMap() { context_map.clear(); }

InferenceContextPtr CreateInferenceContext(const std::unordered_map<NodePtr, InferenceContextPtr> &context_map,
const NodePtr &node) {
if (node == nullptr) {
GELOGE(GRAPH_FAILED, "node is null");
return nullptr;
}
InferenceContextPtr inference_context = std::shared_ptr<InferenceContext>(InferenceContext::Create());
if (inference_context == nullptr) {
REPORT_CALL_ERROR("E19999", "Failed to alloc InferenceContext, node:%s", node->GetName().c_str());
GELOGE(GRAPH_FAILED, "[Alloc][InferenceContext] failed.");
return nullptr;
}

auto all_in_data_anchors = node->GetAllInDataAnchors();
std::vector<std::vector<ShapeAndType>> input_shapes_and_types(all_in_data_anchors.size());
std::vector<std::string> marks;

bool has_input_shapes_and_types = false;
for (const auto &in_anchor : all_in_data_anchors) {
const auto &out_anchor = in_anchor->GetPeerOutAnchor();
if (out_anchor == nullptr) {
continue;
}

auto input_node = out_anchor->GetOwnerNode();
if (input_node == nullptr) {
continue;
}

auto iter = context_map.find(input_node);
if (iter != context_map.end()) {
const auto &src_context = iter->second;
GE_IF_BOOL_EXEC(src_context == nullptr, REPORT_INNER_ERROR("E19999", "src_context is null.");
GELOGE(GRAPH_FAILED, "[Check][Param] src_context is null."); return nullptr);
GELOGD("node:%s get %ld marks from node:%s", node->GetName().c_str(), src_context->GetMarks().size(),
input_node->GetName().c_str());
for (auto mark : src_context->GetMarks()) {
marks.push_back(mark);
}
auto output_idx = out_anchor->GetIdx();
auto input_idx = in_anchor->GetIdx();
auto output_shape_and_type = src_context->GetOutputHandleShapesAndTypes();
if (output_idx < static_cast<int>(output_shape_and_type.size())) {
GELOGI("Add shape and type from %s:%d to %s:%d", input_node->GetName().c_str(), output_idx,
node->GetName().c_str(), input_idx);
input_shapes_and_types[input_idx] = output_shape_and_type[output_idx];
has_input_shapes_and_types = true;
} else {
GELOGI("[%s] Output out of range. index = %d, size = %zu", node->GetName().c_str(), output_idx,
output_shape_and_type.size());
}
}
}

if (has_input_shapes_and_types) {
inference_context->SetInputHandleShapesAndTypes(std::move(input_shapes_and_types));
}
inference_context->SetMarks(marks);

return inference_context;
}

void SerialShapeRange(const GeTensorDescPtr &desc, std::string &desc_str) {
desc_str += "[";
@@ -61,7 +130,8 @@ std::string GetInTensorInfoWithString(const ge::NodePtr &node) {
if (in_idx > 0) {
ss << " ";
}
ss << "input_" << in_idx << " " << "tensor: [";
ss << "input_" << in_idx << " "
<< "tensor: [";
ss << "(shape:[" << input_desc->MutableShape().ToString() << "]),";
ss << "(format:" << TypeUtils::FormatToSerialString(input_desc->GetFormat()) << "),";
ss << "(dtype:" << TypeUtils::DataTypeToSerialString(input_desc->GetDataType()) << "),";
@@ -76,27 +146,238 @@ std::string GetInTensorInfoWithString(const ge::NodePtr &node) {
return ss.str();
}

Status InferShapePass::Run(NodePtr &node) {
// kOptimizeAfterSubGraph exist means after subgraph
auto ret = ShapeRefiner::InferShapeAndType(node, !OptionExists(kOptimizeAfterSubGraph));
if (ret != GRAPH_SUCCESS) {
// select INFERSHAPE failed info
auto graph = node->GetOwnerComputeGraph();
GE_CHECK_NOTNULL(graph);
auto root_graph = ge::GraphUtils::FindRootGraph(graph);
GE_CHECK_NOTNULL(root_graph);
analyzer::DataInfo analyze_info{root_graph->GetSessionID(), root_graph->GetGraphID(),
analyzer::INFER_SHAPE, node, "InferShapeFailed!"};
(void)Analyzer::GetInstance()->DoAnalyze(analyze_info);
(void)Analyzer::GetInstance()->SaveAnalyzerDataToFile(root_graph->GetSessionID(),
root_graph->GetGraphID());
void InferShapePass::AnalyzeFailedInfo(const NodePtr &node) {
auto graph = node->GetOwnerComputeGraph();
if (graph == nullptr) {
GELOGW("Owner compute graph of node %s is nullptr", node->GetName().c_str());
}
auto root_graph = ge::GraphUtils::FindRootGraph(graph);
if (root_graph == nullptr) {
GELOGW("Root compute graph of node %s is nullptr", node->GetName().c_str());
}
analyzer::DataInfo analyze_info{root_graph->GetSessionID(), root_graph->GetGraphID(), analyzer::INFER_SHAPE, node,
"InferShapeFailed!"};
(void)Analyzer::GetInstance()->DoAnalyze(analyze_info);
(void)Analyzer::GetInstance()->SaveAnalyzerDataToFile(root_graph->GetSessionID(), root_graph->GetGraphID());
REPORT_CALL_ERROR("E19999", "Call InferShapeAndType for node:%s(%s) failed, input_tensor:%s", node->GetName().c_str(),
node->GetType().c_str(), GetInTensorInfoWithString(node).c_str());
GELOGE(GE_GRAPH_INFERSHAPE_FAILED, "infershape failed. node: %s", node->GetName().c_str());
}

REPORT_CALL_ERROR("E19999", "Call InferShapeAndType for node:%s(%s) failed, input_tensor:%s",
node->GetName().c_str(), node->GetType().c_str(), GetInTensorInfoWithString(node).c_str());
GELOGE(GE_GRAPH_INFERSHAPE_FAILED, "infershape failed. node: %s", node->GetName().c_str());
return GE_GRAPH_INFERSHAPE_FAILED;
graphStatus InferShapePass::UpdateTensorDesc(const GeTensorDescPtr &src, GeTensorDescPtr dst, bool &changed) {
changed = false;
const auto &dst_dims = dst->GetShape().GetDims();
const auto &src_dims = src->GetShape().GetDims();
if (dst_dims == src_dims) {
changed = true;
}
dst = src;
return GRAPH_SUCCESS;
}

graphStatus InferShapePass::UpdateDescAttrForPeerInput(const GeTensorDescPtr &src, GeTensorDescPtr dst, bool &changed) {
changed = false;
if (dst->GetShape().GetDims() == src->GetShape().GetDims()) {
changed = true;
}
dst->SetOriginShape(src->GetOriginShape());
dst->SetShape(src->GetShape());
dst->SetDataType(src->GetDataType());
dst->SetOriginDataType(src->GetOriginDataType());
std::vector<std::pair<int64_t, int64_t>> shape_range;
(void)src->GetShapeRange(shape_range);
dst->SetShapeRange(shape_range);
ge::TensorUtils::SetRealDimCnt(*dst, static_cast<uint32_t>(src->GetShape().GetDims().size()));
return GRAPH_SUCCESS;
}

graphStatus InferShapePass::Infer(NodePtr &node) {
bool is_unknown_graph = node->GetOwnerComputeGraph()->GetGraphUnknownFlag();
auto opdesc = node->GetOpDesc();
// some op can not infershape twice such as aipp
bool need_update_input = !is_unknown_graph && !opdesc->HasAttr("has_infered_verified");
if (need_update_input) {
auto status = UpdateOpInputDesc(node);
if (status != GRAPH_SUCCESS) {
REPORT_CALL_ERROR("E19999", "update op input_desc failed! ret:%d, node:%s", status, node->GetName().c_str());
GELOGE(GRAPH_FAILED, "[Update][OpInputDesc] failed! ret:%d", status);
return status;
}
}

if (node->Verify() != GRAPH_SUCCESS) {
REPORT_CALL_ERROR("E19999", "Verifying %s failed.", node->GetName().c_str());
GELOGE(GRAPH_FAILED, "[Call][Verify] Verifying %s failed.", node->GetName().c_str());
return GRAPH_FAILED;
}
PrintInOutTensorShape(node, "before_infershape");
Operator op = OpDescUtils::CreateOperatorFromNode(node);

if (!is_unknown_graph) {
auto inference_context = CreateInferenceContext(context_map, node);
GE_CHECK_NOTNULL(inference_context);
GELOGD("create context for node:%s, marks %zu", node->GetName().c_str(), inference_context->GetMarks().size());
op.SetInferenceContext(inference_context);
}

graphStatus status = CallInferShapeFunc(node, op);
if (status == GRAPH_PARAM_INVALID || status == GRAPH_SUCCESS) {
if (is_unknown_graph) {
PrintInOutTensorShape(node, "after_infershape when running");
return GRAPH_SUCCESS;
}
UpdateInputOutputOriginAttr(node);
} else {
REPORT_CALL_ERROR("E19999", "%s call infer function failed.", node->GetName().c_str());
GELOGE(GRAPH_FAILED, "[Call][InferFunction] failed, node:%s.", node->GetName().c_str());
return GRAPH_FAILED;
}
if (!is_unknown_graph) {
auto ctx_after_infer = op.GetInferenceContext();
if (ctx_after_infer != nullptr) {
GELOGD("[%s] after infershape. mark:%zu", node->GetName().c_str(), ctx_after_infer->GetMarks().size());
if (!ctx_after_infer->GetOutputHandleShapesAndTypes().empty() || !ctx_after_infer->GetMarks().empty()) {
GELOGD("[%s] set inference context after. mark:%zu", node->GetName().c_str(),
ctx_after_infer->GetMarks().size());
(void)context_map.emplace(node, ctx_after_infer);
}
}
}

return GRAPH_SUCCESS;
}

graphStatus InferShapePass::CallInferShapeFunc(NodePtr &node, Operator &op) {
auto op_desc = node->GetOpDesc();
const auto &op_type = op_desc->GetType();
auto ret = op_desc->CallInferFunc(op);
if (ret == GRAPH_PARAM_INVALID) {
// Op ir no infer func, try to get infer func from operator factory
auto node_op = ge::OperatorFactory::CreateOperator("node_op", op_desc->GetType());
if (node_op.IsEmpty()) {
GELOGW("get op from OperatorFactory fail. opType: %s", op_type.c_str());
return ret;
}

GELOGD("get op from OperatorFactory success. opType: %s", op_type.c_str());
auto temp_op_desc = ge::OpDescUtils::GetOpDescFromOperator(node_op);
node_op.BreakConnect();
if (temp_op_desc == nullptr) {
REPORT_CALL_ERROR("E19999", "GetOpDescFromOperator failed, return nullptr.");
GELOGE(GRAPH_FAILED, "[Get][OpDesc] temp op desc is null");
return GRAPH_FAILED;
}
if (!op_desc->UpdateInputName(temp_op_desc->GetAllInputName())) {
GELOGW("InferShapeAndType UpdateInputName failed");
for (const auto &out_desc : op_desc->GetAllOutputsDescPtr()) {
if (out_desc != nullptr && out_desc->GetShape().GetDims().empty()) {
break;
}
return GRAPH_SUCCESS;
}
}
if (!op_desc->UpdateOutputName(temp_op_desc->GetAllOutputName())) {
GELOGW("InferShapeAndType UpdateOutputName failed");
}
op_desc->AddInferFunc(temp_op_desc->GetInferFunc());
ret = op_desc->CallInferFunc(op);
GELOGI("op CallInferFunc second. ret: %u", ret);
}
return ret;
}

void InferShapePass::UpdateInputOutputOriginAttr(NodePtr &node) {
auto op_desc = node->GetOpDesc();
for (const auto &out_anchor : node->GetAllOutDataAnchors()) {
auto output_tensor = op_desc->MutableOutputDesc(out_anchor->GetIdx());
if (output_tensor == nullptr) {
continue;
}
if (output_tensor->MutableShape().GetDims().empty()) {
output_tensor->SetOriginShape(output_tensor->GetShape());
}
ge::TensorUtils::SetRealDimCnt(*output_tensor,
static_cast<uint32_t>(output_tensor->GetOriginShape().GetDims().size()));
output_tensor->SetOriginDataType(output_tensor->GetDataType());
// set output origin shape range
std::vector<std::pair<int64_t, int64_t>> range;
(void)output_tensor->GetShapeRange(range);
output_tensor->SetOriginShapeRange(range);
GELOGD("node name is %s, origin shape is %ld, origin format is %s, origin data type is %s", node->GetName().c_str(),
output_tensor->GetOriginShape().GetShapeSize(),
TypeUtils::FormatToSerialString(output_tensor->GetOriginFormat()).c_str(),
TypeUtils::DataTypeToSerialString(output_tensor->GetOriginDataType()).c_str());
}
for (const auto &in_anchor : node->GetAllInDataAnchors()) {
auto input_tensor = op_desc->MutableInputDesc(in_anchor->GetIdx());
if (input_tensor == nullptr) {
continue;
}
// set input origin shape range
std::vector<std::pair<int64_t, int64_t>> range;
(void)input_tensor->GetShapeRange(range);
input_tensor->SetOriginShapeRange(range);
}
}

graphStatus InferShapePass::UpdateOpInputDesc(const ConstNodePtr &node_ptr) {
for (const auto &in_anchor : node_ptr->GetAllInDataAnchors()) {
auto in_idx = in_anchor->GetIdx();
auto peer_out_data_anchor = in_anchor->GetPeerOutAnchor();
if (peer_out_data_anchor == nullptr) {
continue;
}
auto peer_out_data_node = peer_out_data_anchor->GetOwnerNode();
if (peer_out_data_node == nullptr || peer_out_data_node->GetOpDesc() == nullptr) {
continue;
}
int peer_out_idx = peer_out_data_anchor->GetIdx();
auto peer_out_desc = peer_out_data_node->GetOpDesc()->MutableOutputDesc(static_cast<uint32_t>(peer_out_idx));

// check shape and dtype continuity. do not stop process
auto in_desc = node_ptr->GetOpDesc()->MutableInputDesc(static_cast<uint32_t>(in_idx));
if (in_desc == nullptr) {
continue;
}
auto in_shape = in_desc->MutableShape().GetDims();
auto in_dtype = in_desc->GetDataType();
auto peer_out_shape = peer_out_desc->MutableShape().GetDims();
auto peer_out_dtype = peer_out_desc->GetDataType();
if (peer_out_dtype != in_dtype) {
GELOGW(
"current node [%s] [%d]\'th in_dtype is [%s].peer output node [%s] [%d]\'th "
"output_dtype is [%s].The two dtype should be same! Please check graph and fix it",
node_ptr->GetName().c_str(), in_idx, TypeUtils::DataTypeToSerialString(in_dtype).c_str(),
peer_out_data_node->GetName().c_str(), peer_out_idx, TypeUtils::DataTypeToSerialString(peer_out_dtype).c_str());
} else if ((!in_shape.empty()) && (in_shape != peer_out_shape)) {
string in_shape_str = " "; //Serial(in_shape);
string peer_out_shape_str = " "; //Serial(peer_out_shape);
GELOGW(
"current node [%s] [%d]\'th in_shape is [%s].peer output node [%s] [%d]\'th "
"output_shape is [%s].The two shape should be same! Please check graph and fix it",
node_ptr->GetName().c_str(), in_idx, in_shape_str.c_str(), peer_out_data_node->GetName().c_str(), peer_out_idx,
peer_out_shape_str.c_str());
}
// refresh current node input desc
in_desc->SetOriginShape(peer_out_desc->GetOriginShape());
in_desc->SetShape(peer_out_desc->MutableShape());
in_desc->SetDataType(peer_out_desc->GetDataType());
in_desc->SetOriginDataType(peer_out_desc->GetOriginDataType());
if (peer_out_desc->MutableShape().GetDims() != UNKNOWN_RANK) {
std::vector<std::pair<int64_t, int64_t>> shape_range;
(void)peer_out_desc->GetShapeRange(shape_range);
in_desc->SetShapeRange(shape_range);
}
std::vector<int64_t> pre_op_in_range;
if (ge::AttrUtils::GetListInt(*peer_out_desc, kPreOpInputShapeRange, pre_op_in_range)) {
(void)ge::AttrUtils::SetListInt(*in_desc, kPreOpInputShapeRange, pre_op_in_range);
}
ge::TensorUtils::SetRealDimCnt(*in_desc, static_cast<uint32_t>(peer_out_desc->MutableShape().GetDims().size()));
}
return GRAPH_SUCCESS;
}

Status InferShapePass::DoRepassForLoopNode(NodePtr &node) {
GE_CHK_STATUS_RET_NOLOG(RePassLoopNode(node));
bool need_repass = false;
auto has_attr = AttrUtils::GetBool(node->GetOpDesc(), ATTR_NAME_NEED_INFER_AGAIN, need_repass);
@@ -148,13 +429,13 @@ Status InferShapePass::RePassLoopNode(const NodePtr &node) {
std::string node_type;
GE_CHK_STATUS_RET(GetOriginalType(node, node_type), "Get original node type failed.");
if (kNextIterationOpTypes.count(node_type) > 0) {
return RePassNode(kMergeOpTypes); // Re-Pass Merge
return RePassNode(kMergeOpTypes); // Re-Pass Merge
}

if (kMergeOpTypes.count(node_type) > 0) {
if (node->GetOpDesc()->HasAttr(ATTR_NAME_NEED_INFER_AGAIN)) {
node->GetOpDesc()->DelAttr(ATTR_NAME_NEED_INFER_AGAIN);
return RePassNode(kSwitchOpTypes); // Re-Pass Switch
return RePassNode(kSwitchOpTypes); // Re-Pass Switch
}
return SUCCESS;
}
@@ -162,12 +443,111 @@ Status InferShapePass::RePassLoopNode(const NodePtr &node) {
if (kSwitchOpTypes.count(node_type) > 0) {
if (node->GetOpDesc()->HasAttr(ATTR_NAME_NEED_INFER_AGAIN)) {
node->GetOpDesc()->DelAttr(ATTR_NAME_NEED_INFER_AGAIN);
return ExProcNode(kExitOpTypes, &InferShapePass::AddNodeResume, "need resume"); // Resume Exit
return ExProcNode(kExitOpTypes, &InferShapePass::AddNodeResume, "need resume"); // Resume Exit
} else {
return ExProcNode(kExitOpTypes, &InferShapePass::AddNodeSuspend, "need suspend"); // Suspend Exit
return ExProcNode(kExitOpTypes, &InferShapePass::AddNodeSuspend, "need suspend"); // Suspend Exit
}
}

return SUCCESS;
}

GE_FUNC_DEV_VISIBILITY GE_FUNC_HOST_VISIBILITY
graphStatus InferShapePass::InferShapeAndType(NodePtr &node) {
GE_CHECK_NOTNULL(node);
GE_CHECK_NOTNULL(node->GetOpDesc());
InferShapePass pass;
std::set<NodePtr> unused_changed_nodes;
return pass.InferAndUpdate(node, true, unused_changed_nodes);
}
GE_FUNC_DEV_VISIBILITY GE_FUNC_HOST_VISIBILITY
graphStatus InferShapePass::InferShapeAndType(NodePtr &node, bool before_subgraph) {
GE_CHECK_NOTNULL(node);
GE_CHECK_NOTNULL(node->GetOpDesc());
InferShapePass pass;
std::set<NodePtr> unused_changed_nodes;
return pass.InferAndUpdate(node, before_subgraph, unused_changed_nodes);
}


graphStatus InferShapeForRunning::Infer(NodePtr &node) {
auto opdesc = node->GetOpDesc();
vector<ge::DataType> temp_dtype;
for (auto &tensor_desc : opdesc->GetAllOutputsDescPtr()) {
temp_dtype.emplace_back(tensor_desc->GetDataType());
}
PrintInOutTensorShape(node, "before_infershape when running");

Operator op = OpDescUtils::CreateOperatorFromNode(node);
graphStatus status = CallInferShapeFuncForRunning(node, op);
if (status == GRAPH_PARAM_INVALID || status == GRAPH_SUCCESS) {
// ensure the dtype is not changed after infershape in running
auto after_opdesc = node->GetOpDesc();
GE_IF_BOOL_EXEC(after_opdesc == nullptr, REPORT_INNER_ERROR("E19999", "param node has no opdesc, check invalid.");
GELOGE(GRAPH_FAILED, "[Get][OpDesc] after_opdesc is null."); return GRAPH_FAILED);
auto all_output_tensor = after_opdesc->GetAllOutputsDescPtr();
for (size_t i = 0; i < all_output_tensor.size(); ++i) {
if (all_output_tensor.at(i)->GetDataType() != temp_dtype[i]) {
GELOGD("Op %s output %zu need reset dtype,original dtype is %s, new dtype is %s", node->GetName().c_str(), i,
TypeUtils::DataTypeToSerialString(all_output_tensor.at(i)->GetDataType()).c_str(),
TypeUtils::DataTypeToSerialString(temp_dtype[i]).c_str());
all_output_tensor.at(i)->SetDataType(temp_dtype[i]);
}
}
PrintInOutTensorShape(node, "after_infershape when running");
return GRAPH_SUCCESS;
} else {
REPORT_CALL_ERROR("E19999", "%s call infer function failed.", node->GetName().c_str());
GELOGE(GRAPH_FAILED, "[Call][InferFunction] failed, node:%s.", node->GetName().c_str());
return GRAPH_FAILED;
}
}

graphStatus InferShapeForRunning::CallInferShapeFuncForRunning(NodePtr &node, Operator &op) {
auto op_desc = node->GetOpDesc();
const auto &op_type = op_desc->GetType();

// Create InferenceContext to avoid null pointer access.
const static std::set<std::string> force_context_op_types{"Enter", "Switch", "RefSwitch"};
if (force_context_op_types.count(op_type) > 0) {
GELOGD("Set InferenceContext for node [%s]", op_desc->GetName().c_str());
op.SetInferenceContext(std::shared_ptr<InferenceContext>(InferenceContext::Create()));
}

// Get infer func and execute
auto ret = op_desc->CallInferFunc(op);
if (ret == GRAPH_PARAM_INVALID) {
GELOGD("NodeUtils::GetNodeType return value is: [%s]", NodeUtils::GetNodeType(*node).c_str());
auto origin_type = NodeUtils::GetNodeType(*node);
auto infer_func = ge::OperatorFactoryImpl::GetInferShapeFunc(origin_type);
if (infer_func == nullptr) {
REPORT_INNER_ERROR("E19999", "Failed to Get InferFunc. type is %s", origin_type.c_str());
GELOGE(GRAPH_FAILED, "[Get][InferFunc] failed. type is %s", origin_type.c_str());
return GRAPH_FAILED;
}
op_desc->AddInferFunc(infer_func);
ret = op_desc->CallInferFunc(op);
GELOGI("op CallInferFunc second. ret: %u", ret);
}
return ret;
}
graphStatus InferShapeForRunning::UpdateTensorDesc(const GeTensorDescPtr &src, GeTensorDescPtr dst, bool &changed) {
changed = false;
const auto &dst_dims = dst->GetShape().GetDims();
const auto &src_dims = src->GetShape().GetDims();
if (dst_dims == src_dims) {
changed = true;
}
dst = src;
return GRAPH_SUCCESS;
}

GE_FUNC_DEV_VISIBILITY GE_FUNC_HOST_VISIBILITY
graphStatus InferShapeForRunning::InferShapeAndTypeForRunning(NodePtr &node, bool before_subgraph) {
GE_CHECK_NOTNULL(node);
GE_CHECK_NOTNULL(node->GetOpDesc());
InferShapeForRunning pass;
std::set<NodePtr> unused_changed_nodes;
return pass.InferAndUpdate(node, before_subgraph, unused_changed_nodes);
}
} // namespace ge

+ 28
- 11
ge/graph/passes/infershape_pass.h View File

@@ -17,22 +17,39 @@
#ifndef GE_GRAPH_PASSES_INFERSHAPE_PASS_H_
#define GE_GRAPH_PASSES_INFERSHAPE_PASS_H_

#include "graph/passes/base_pass.h"
#include "graph/passes/infer_base_pass.h"

namespace ge {
class InferShapePass : public BaseNodePass {
class InferShapePass : public InferBasePass {
public:
///
/// Entry of the InferShapePass optimizer
/// @param [in] graph: Input ComputeGraph
/// @return SUCCESS: Execution succeed
/// @return OTHERS: Execution failed
/// @author
///
Status Run(ge::NodePtr &node) override;
static void ClearContextMap();
graphStatus Infer(NodePtr &node) override;
graphStatus UpdateTensorDesc(const GeTensorDescPtr &src, GeTensorDescPtr dst, bool &changed) override;
graphStatus UpdateDescAttrForPeerInput(const GeTensorDescPtr &src, GeTensorDescPtr dst, bool &changed) override;
void AnalyzeFailedInfo(const NodePtr &node) override;

static graphStatus InferShapeAndType(NodePtr &node); // temp: visible static func is in cur pass
static graphStatus InferShapeAndType(NodePtr &node, bool before_subgraph); // temp: visible static func is in cur pass

private:
graphStatus CallInferShapeFunc(NodePtr &node, Operator &op);
void UpdateInputOutputOriginAttr(NodePtr &node);
graphStatus UpdateOpInputDesc(const ConstNodePtr &node_ptr); // maybe useless, just test infer_shape

Status DoRepassForLoopNode(NodePtr &node) override; // only for test inferXBase, will be deleted
Status RePassLoopNode(const NodePtr &node); // old repass logic, will be deleted
};


class InferShapeForRunning : public InferBasePass {
public:
graphStatus Infer(NodePtr &node) override;
graphStatus UpdateTensorDesc(const GeTensorDescPtr &src, GeTensorDescPtr dst, bool &changed) override;

static graphStatus InferShapeAndTypeForRunning(NodePtr &node, bool before_subgraph); // temp: visible static func

private:
Status RePassLoopNode(const NodePtr &node);
graphStatus CallInferShapeFuncForRunning(NodePtr &node, Operator &op);
};
} // namespace ge
#endif // GE_GRAPH_PASSES_INFERSHAPE_PASS_H_

+ 4
- 2
ge/hybrid/executor/worker/shape_inference_engine.cc View File

@@ -22,6 +22,8 @@
#include "common/math/math_util.h"
#include "hybrid/node_executor/node_executor.h"

#include "graph/passes/infershape_pass.h" // test new infershape pass

namespace ge {
namespace {
const int kAlignment = 32;
@@ -71,7 +73,7 @@ Status ShapeInferenceEngine::InferShape(NodeState &node_state) {
GELOGD("[%s] Start to invoke InferShapeAndType", node_item.NodeName().c_str());
{
RECORD_SHAPE_INFERENCE_EVENT(execution_context_, node_item.NodeName().c_str(), "[InferShapeAndType] Start");
GE_CHK_STATUS_RET(ShapeRefiner::InferShapeAndTypeForRunning(node_item.node, true),
GE_CHK_STATUS_RET(InferShapeForRunning::InferShapeAndTypeForRunning(const_cast<NodePtr &>(node_item.node), true),
"[Invoke][InferShapeAndType] for %s failed.", node_item.NodeName().c_str());
RECORD_SHAPE_INFERENCE_EVENT(execution_context_, node_item.NodeName().c_str(), "[InferShapeAndType] End");
}
@@ -173,7 +175,7 @@ Status ShapeInferenceEngine::InferShapeForSubgraph(const NodeItem &node_item, co

for (auto &node : fused_subgraph.nodes) {
GELOGD("[%s] Start to invoke InferShapeAndType", node->GetName().c_str());
GE_CHK_STATUS_RET(ShapeRefiner::InferShapeAndType(node));
GE_CHK_STATUS_RET(InferShapePass::InferShapeAndType(const_cast<NodePtr &>(node)));
GELOGD("[%s] Done invoking InferShapeAndType", node->GetName().c_str());
GE_CHK_STATUS_RET(UpdatePeerNodeShape(*node),
"[Update][PeerNodeShape] failed for [%s].", node->GetName().c_str());


+ 6
- 1
tests/ut/ge/CMakeLists.txt View File

@@ -218,7 +218,9 @@ set(COMMON_SRC_FILES
"${GE_CODE_DIR}/ge/graph/passes/shape_operate_op_remove_pass.cc"
"${GE_CODE_DIR}/ge/graph/passes/assert_pass.cc"
"${GE_CODE_DIR}/ge/graph/passes/dropout_pass.cc"
"${GE_CODE_DIR}/ge/graph/passes/infer_base_pass.cc"
"${GE_CODE_DIR}/ge/graph/passes/infershape_pass.cc"
#"${GE_CODE_DIR}/ge/graph/passes/infer_value_range_pass.cc"
"${GE_CODE_DIR}/ge/graph/passes/unused_const_pass.cc"
"${GE_CODE_DIR}/ge/graph/passes/permute_pass.cc"
"${GE_CODE_DIR}/ge/graph/passes/ctrl_edge_transfer_pass.cc"
@@ -477,7 +479,7 @@ set(GRAPH_BUILD_COMMON_SRC_FILES
)

set(GRAPH_PASS_COMMON_SRC_FILES
"${GE_CODE_DIR}/ge/graph/passes/pass_manager.cc"
"${GE_CODE_DIR}/ge/graph/passes/pass_manager.cc"
"${GE_CODE_DIR}/ge/graph/passes/base_pass.cc"
"${GE_CODE_DIR}/ge/graph/passes/variable_prepare_op_pass.cc"
"${GE_CODE_DIR}/ge/graph/passes/variable_ref_delete_op_pass.cc"
@@ -531,7 +533,9 @@ set(GRAPH_PASS_COMMON_SRC_FILES
"${GE_CODE_DIR}/ge/graph/passes/transpose_transdata_pass.cc"
"${GE_CODE_DIR}/ge/graph/passes/hccl_memcpy_pass.cc"
"${GE_CODE_DIR}/ge/graph/passes/no_use_reshape_remove_pass.cc"
"${GE_CODE_DIR}/ge/graph/passes/infer_base_pass.cc"
"${GE_CODE_DIR}/ge/graph/passes/infershape_pass.cc"
#"${GE_CODE_DIR}/ge/graph/passes/infer_value_range_pass.cc"
"${GE_CODE_DIR}/ge/ge_local_engine/engine/host_cpu_engine.cc"
"${GE_CODE_DIR}/ge/analyzer/analyzer.cc"
"${GE_CODE_DIR}/ge/graph/passes/net_output_pass.cc"
@@ -706,6 +710,7 @@ set(PASS_TEST_FILES
"graph/passes/net_output_pass_unittest.cc"
"graph/passes/no_use_reshape_remove_pass_unittest.cc"
"graph/passes/infershape_pass_unittest.cc"
#"graph/passes/infer_value_range_pass_unittest.cc"
"graph/passes/mark_force_unknown_for_cond_pass_unittest.cc"
"graph/passes/multi_batch_clone_pass_unittest.cc"
"graph/passes/replace_with_empty_const_pass_unittest.cc"


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