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!11084 debug tts encoder model 

From: @wangzhe128
Reviewed-by: 
Signed-off-by:
This commit is contained in:
mindspore-ci-bot 2021-01-11 15:00:56 +08:00 committed by Gitee
parent ec556edde7 c1a40c20a1
commit eaf7809c0e
10 changed files with 92 additions and 29 deletions
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2
mindspore/lite/src/lite_model.cc
View File

@ -126,7 +126,7 @@ void LiteModel::Destroy() {
int LiteModel::ConvertSubGraph(const schema::SubGraph &sub_graph) {
if (sub_graph.name() == nullptr || sub_graph.inputIndices() == nullptr || sub_graph.outputIndices() == nullptr ||
sub_graph.nodeIndices() == nullptr || sub_graph.tensorIndices() == nullptr) {
MS_LOG(ERROR) << "sub_graph is invalid.";
MS_LOG(ERROR) << "sub_graph is invalid";
return RET_ERROR;
}

11
mindspore/lite/src/ops/squeeze.cc
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@ -111,11 +111,10 @@ int Squeeze::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor *> out
std::vector<int> out_shape;
auto axis = GetAxis();
std::vector<int> axes_;
for (auto iter = axis.begin(); iter != axis.end(); iter++) {
axes_.push_back(*iter);
}
if (axes_.size() == 0) {
std::vector<int> axes;
std::transform(axis.begin(), axis.end(), std::back_inserter(axes),
[in_shape](int a) { return a >= 0 ? a : a + in_shape.size(); });
if (axes.size() == 0) {
for (size_t i = 0; i < in_shape.size(); i++) {
if (in_shape.at(i) != 1) {
out_shape.push_back(in_shape.at(i));
@ -124,7 +123,7 @@ int Squeeze::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor *> out
} else {
size_t axisIdx = 0;
for (size_t i = 0; i < in_shape.size(); i++) {
if (axisIdx < axes_.size() && axes_.at(axisIdx) == static_cast<int>(i)) {
if (axisIdx < axes.size() && axes.at(axisIdx) == static_cast<int>(i)) {
MS_ASSERT(in_shape.at(i) == 1);
axisIdx++;
continue;

30
mindspore/lite/src/runtime/kernel/arm/base/merge.cc
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@ -27,12 +27,26 @@ using mindspore::schema::PrimitiveType_Merge;
namespace mindspore::kernel {
int MergeCPUKernel::FreeInWorkTensor() const {
for (auto &in_tensor : this->in_tensors_) {
MS_ASSERT(in_tensor != nullptr);
if (in_tensor->root_tensor() == in_tensor) {
continue;
size_t stride = in_tensors_.size() / 2;
if (this->ready_part_ == LEFT_INPUT_PART) {
for (size_t i = 0; i < stride; ++i) {
auto in_tensor = in_tensors_[i];
MS_ASSERT(in_tensor != nullptr);
if (in_tensor->root_tensor() == in_tensor) {
continue;
}
in_tensor->DecRefCount();
}
}
if (this->ready_part_ == RIGHT_INPUT_PART) {
for (size_t i = stride; i < in_tensors_.size(); ++i) {
auto in_tensor = in_tensors_[i];
MS_ASSERT(in_tensor != nullptr);
if (in_tensor->root_tensor() == in_tensor) {
continue;
}
in_tensor->DecRefCount();
}
in_tensor->DecRefCount();
}
return RET_OK;
}
@ -102,15 +116,15 @@ InputPart MergeCPUKernel::FindReadyPart(const std::vector<lite::Tensor *> &scope
int MergeCPUKernel::Run() {
MS_ASSERT(in_tensors_.size() == 2 * out_tensors_.size());
auto ready_part = FindReadyPart(this->in_tensors_);
if (ready_part == LEFT_INPUT_PART) {
ready_part_ = FindReadyPart(this->in_tensors_);
if (ready_part_ == LEFT_INPUT_PART) {
auto ret = MoveData(this->out_tensors_.begin(), this->out_tensors_.end(), this->in_tensors_.begin(),
this->in_tensors_.end());
if (ret != RET_OK) {
MS_LOG(ERROR) << "carry data error : " << ret;
return ret;
}
} else if (ready_part == RIGHT_INPUT_PART) {
} else if (ready_part_ == RIGHT_INPUT_PART) {
auto ret = MoveData(this->out_tensors_.begin(), this->out_tensors_.end(),
(this->in_tensors_.begin() + in_tensors_.size() / 2), this->in_tensors_.end());
if (ret != RET_OK) {

2
mindspore/lite/src/runtime/kernel/arm/base/merge.h
View File

@ -41,7 +41,7 @@ class MergeCPUKernel : public CarryDataKernel {
InputPart FindReadyPart(const std::vector<lite::Tensor *> &scope_tensors);
private:
bool PartialInputReady(int num_begin, int num_end);
InputPart ready_part_ = UNKNOWN_INPUT_PART;
};
} // namespace mindspore::kernel

9
mindspore/lite/src/runtime/kernel/arm/fp32/transpose_fp32.cc
View File

@ -42,6 +42,11 @@ int TransposeCPUKernel::ReSize() {
if (in_tensors_.at(kInputIndex)->shape().size() != static_cast<size_t>(param->num_axes_) && in_tensors_.size() != 2) {
return RET_OK;
}
if (in_tensors_.size() == 2) {
auto input_perm = in_tensors_.at(1);
MS_ASSERT(input_perm != nullptr);
param->num_axes_ = input_perm->ElementsNum();
}
auto &inTensor = in_tensors_.front();
auto &outTensor = out_tensors_.front();
auto in_shape = inTensor->shape();
@ -94,14 +99,12 @@ int TransposeCPUKernel::Run() {
MS_ASSERT(input_perm != nullptr);
MS_ASSERT(input_perm->data_c() != nullptr);
int *perm_data = reinterpret_cast<int *>(input_perm->data_c());
auto perm = std::vector<int>{perm_data, perm_data + input_perm->ElementsNum()};
for (int i = 0; i < input_perm->ElementsNum(); ++i) {
param->perm_[i] = perm[i];
param->perm_[i] = perm_data[i];
}
for (int i = input_perm->ElementsNum(); i <= 8; ++i) {
param->perm_[i] = 0;
}
param->num_axes_ = input_perm->ElementsNum();
}
if (in_tensor->shape().size() != static_cast<size_t>(param->num_axes_)) {
memcpy(out_data_, in_data_, in_tensor->ElementsNum() * sizeof(float));

1
mindspore/lite/test/models_tf.cfg
View File

@ -1,3 +1,4 @@
decoder_step_201217.pb 5
decoder_step_201217_modified.pb 5
unet_model_reconstruct.pb 1;1,256,256,3
encoder_201228.pb 3;1:1,22:1

12
mindspore/lite/test/run_benchmark_nets.sh
View File

@ -336,9 +336,9 @@ function Run_x86() {
else
run_result='x86: '${model_name}' failed'; echo ${run_result} >> ${run_benchmark_result_file}; return 1
fi
# run benchmark test without clib data
echo 'export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:./lib:./third_party/libjpeg-turbo/lib:./third_party/opencv/lib;./benchmark/benchmark --inputShapes='${input_shapes}' --modelFile='${ms_models_path}'/'${model_name}'.ms' >> "${run_x86_log_file}"
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:./lib:./third_party/libjpeg-turbo/lib:./third_party/opencv/lib;./benchmark/benchmark --inputShapes=${input_shapes} --modelFile=${ms_models_path}/${model_name}.ms >> "${run_x86_log_file}"
# run benchmark test with input data
echo 'export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:./lib:./third_party/libjpeg-turbo/lib:./third_party/opencv/lib;./benchmark/benchmark --modelFile='${ms_models_path}'/'${model_name}'.ms --inDataFile=/home/workspace/mindspore_dataset/mslite/models/hiai/input_output/input/'${input_files}' --inputShapes='${input_shapes} >> "${run_x86_log_file}"
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:./lib:./third_party/libjpeg-turbo/lib:./third_party/opencv/lib;./benchmark/benchmark --modelFile=${ms_models_path}/${model_name}.ms --inDataFile=${input_files} --inputShapes=${input_shapes} >> "${run_x86_log_file}"
if [ $? = 0 ]; then
run_result='x86: '${model_name}' pass'; echo ${run_result} >> ${run_benchmark_result_file}
else
@ -1229,10 +1229,10 @@ function Run_arm64() {
else
run_result='arm64: '${model_name}' failed'; echo ${run_result} >> ${run_benchmark_result_file}; return 1
fi
# run benchmark test without clib data
# run benchmark test with input data
echo 'cd /data/local/tmp/benchmark_test' > adb_run_cmd.txt
echo 'export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/data/local/tmp/benchmark_test;./benchmark --inputShapes='${input_shapes}' --modelFile='${model_name}'.ms --warmUpLoopCount=1 --loopCount=2' >> "${run_arm64_log_file}"
echo 'export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/data/local/tmp/benchmark_test;./benchmark --inputShapes='${input_shapes}' --modelFile='${model_name}'.ms --warmUpLoopCount=1 --loopCount=2' >> adb_run_cmd.txt
echo 'export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/data/local/tmp/benchmark_test;./benchmark --inputShapes='${input_shapes}' --modelFile='${model_name}'.ms --inDataFile='${input_files}' --warmUpLoopCount=1 --loopCount=2' >> "${run_arm64_log_file}"
echo 'export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/data/local/tmp/benchmark_test;./benchmark --inputShapes='${input_shapes}' --modelFile='${model_name}'.ms --inDataFile='${input_files}' --warmUpLoopCount=1 --loopCount=2' >> adb_run_cmd.txt
adb -s ${device_id} shell < adb_run_cmd.txt >> "${run_arm64_log_file}"
if [ $? = 0 ]; then
run_result='arm64: '${model_name}' pass'; echo ${run_result} >> ${run_benchmark_result_file}

5
mindspore/lite/tools/benchmark/benchmark.cc
View File

@ -327,8 +327,9 @@ int Benchmark::CompareDataGetTotalBiasAndSize(const std::string &name, tensor::M
MS_LOG(ERROR) << "mutableData is nullptr.";
return RET_ERROR;
}
switch (msCalibDataType) {
case TypeId::kNumberTypeFloat: {
switch (tensor->data_type()) {
case TypeId::kNumberTypeFloat:
case TypeId::kNumberTypeFloat32: {
bias = CompareData<float>(name, tensor->shape(), mutableData);
break;
}

37
mindspore/lite/tools/converter/legacy_optimizer/graph/switch_pass.cc
View File

@ -43,6 +43,35 @@ STATUS SwitchPass::Run(mindspore::schema::MetaGraphT *graph) {
return ret;
}
}
// remove empty subgraphs
std::vector<std::unique_ptr<SubGraphT>> new_sub_graphs;
std::map<uint32_t, uint32_t> sub_graph_index_map;
for (size_t i = 0; i < graph->subGraph.size(); ++i) {
auto &sub_graph = graph->subGraph.at(i);
if (!sub_graph->nodeIndices.empty()) {
new_sub_graphs.emplace_back(std::move(sub_graph));
sub_graph_index_map.emplace(std::make_pair(i, new_sub_graphs.size() - 1));
}
}
graph->subGraph.swap(new_sub_graphs);
for (size_t i = 0; i < graph->nodes.size(); ++i) {
auto &node = graph->nodes.at(i);
auto type = node->primitive->value.type;
if (type != schema::PrimitiveType_Partial) {
continue;
}
MS_ASSERT(node->primitive != nullptr);
MS_ASSERT(node->primitive->value.AsPartial() != nullptr);
auto partial_prim = node->primitive->value.AsPartial();
if (partial_prim->subGraphIndex == -1) {
continue;
}
if (sub_graph_index_map.find(partial_prim->subGraphIndex) == sub_graph_index_map.end()) {
MS_LOG(ERROR) << "subGraphIndex is illegal";
return RET_ERROR;
}
partial_prim->subGraphIndex = sub_graph_index_map[partial_prim->subGraphIndex];
}
return RET_OK;
}
@ -308,7 +337,7 @@ STATUS SingleSwitchPass::InsertPartialAndMergeAfterSwitch() {
auto origin_switch_outputs = switch_node_->outputIndex;
switch_node_->outputIndex.clear();
for (size_t i = 3; i < switch_node_->inputIndex.size(); i++) {
auto &switch_in_tensor = graph_->allTensors.at(i);
auto &switch_in_tensor = graph_->allTensors.at(switch_node_->inputIndex[i]);
auto tensor = NewTensor(switch_in_tensor);
graph_->allTensors.push_back(std::move(tensor));
switch_node_->outputIndex.push_back(graph_->allTensors.size() - 1);
@ -581,6 +610,9 @@ STATUS SingleSwitchPass::UpdateSubgraphOutput(const size_t &subgraph_index, sche
STATUS SingleSwitchPass::ConcatCondSubgraphInputAndOutput() {
if (first_subgraph_index_ == -1) {
MS_ASSERT(first_partial_node_->primitive != nullptr);
MS_ASSERT(first_partial_node_->primitive->value.AsPartial() != nullptr);
first_partial_node_->primitive->value.AsPartial()->subGraphIndex = -1;
return RET_OK;
}
int ret = UpdateSubgraphInput(first_subgraph_index_, first_partial_node_, first_graph_nodes_);
@ -599,6 +631,9 @@ STATUS SingleSwitchPass::ConcatCondSubgraphInputAndOutput() {
STATUS SingleSwitchPass::ConcatBodySubgraphInputAndOutput() {
if (second_subgraph_index_ == -1) {
MS_ASSERT(first_partial_node_->primitive != nullptr);
MS_ASSERT(first_partial_node_->primitive->value.AsPartial() != nullptr);
first_partial_node_->primitive->value.AsPartial()->subGraphIndex = -1;
return RET_OK;
}
int ret = UpdateSubgraphInput(second_subgraph_index_, second_partial_node_, second_graph_nodes_);

12
mindspore/lite/tools/converter/parser/tf/tf_model_parser.cc
View File

@ -592,7 +592,17 @@ STATUS TFModelParser::ControlFlowNodePostProcess(const std::map<CNodePtr, FuncGr
auto second_value_node = NewValueNode(second_sub_graph);
auto inputs = control_flow_node->inputs();
inputs.insert(inputs.begin() + 1, {first_value_node, second_value_node});
control_flow_node->set_inputs(inputs);
auto new_node = anf_root_graph_->NewCNode(inputs); // must create new node, otherwise node_users won't update
if (new_node == nullptr) {
MS_LOG(ERROR) << "new node failed";
return RET_ERROR;
}
new_node->set_abstract(control_flow_node->abstract()->Clone());
new_node->set_fullname_with_scope(control_flow_node->fullname_with_scope());
if (!root_func_manager->Replace(control_flow_node, new_node)) {
MS_LOG(ERROR) << "replace new node failed";
return RET_ERROR;
}
}
return RET_OK;
}