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!4144 fix anf transform bug 

Merge pull request !4144 from zhengjun10/master
This commit is contained in:
mindspore-ci-bot 2020-08-10 20:12:41 +08:00 committed by Gitee
parent 0a1fac9246 0a1d090b3e
commit 7f53253b56
4 changed files with 22 additions and 22 deletions
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2
mindspore/lite/tools/converter/converter.cc
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@ -90,7 +90,7 @@ MetaGraphT *Converter::Convert(const converter::Flags *flag) {
return nullptr; return nullptr;
} }
// graph = anfTransform->Transform(graph); graph = anfTransform->Transform(graph);
CreateQuantizer(graph, flag); CreateQuantizer(graph, flag);
if (mQuantizer != nullptr) { if (mQuantizer != nullptr) {

28
mindspore/lite/tools/converter/graphdef_transform.cc
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@ -100,20 +100,20 @@ int GraphDefTransform::Transform(const converter::Flags &ctx) {
// } // }
// fusion // fusion
{ // {
Optimizer fusionOptimizer; // Optimizer fusionOptimizer;
fusionOptimizer.AddPass(new (std::nothrow) ConvBiasAddFusionPass()); // fusionOptimizer.AddPass(new (std::nothrow) ConvBiasAddFusionPass());
fusionOptimizer.AddPass(new (std::nothrow) ConvBNFusionPass()); // fusionOptimizer.AddPass(new (std::nothrow) ConvBNFusionPass());
fusionOptimizer.AddPass(new (std::nothrow) ConvScaleFusionPass()); // fusionOptimizer.AddPass(new (std::nothrow) ConvScaleFusionPass());
fusionOptimizer.AddPass(new (std::nothrow) ConvReluFusionPass()); // fusionOptimizer.AddPass(new (std::nothrow) ConvReluFusionPass());
fusionOptimizer.AddPass(new (std::nothrow) ConvRelu6FusionPass()); // fusionOptimizer.AddPass(new (std::nothrow) ConvRelu6FusionPass());
fusionOptimizer.AddPass(new (std::nothrow) IsolatedNodeRemovePass()); // fusionOptimizer.AddPass(new (std::nothrow) IsolatedNodeRemovePass());
status = fusionOptimizer.Run(graphDefT); // status = fusionOptimizer.Run(graphDefT);
if (status != RET_OK && status != RET_NO_CHANGE) { // if (status != RET_OK && status != RET_NO_CHANGE) {
MS_LOG(ERROR) << "Run fusionOptimizer graphPasses Failed"; // MS_LOG(ERROR) << "Run fusionOptimizer graphPasses Failed";
return status; // return status;
} // }
} // }
// weight format trans // weight format trans
if (ctx.formatTrans) { if (ctx.formatTrans) {

8
mindspore/lite/tools/optimizer/fusion/conv_biasadd_fusion.cc
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@ -89,10 +89,10 @@ void GenConvNewBias(const FuncGraphPtr &func_graph, const CNodePtr &conv_node, c
auto add_weight_param = bias_add_weight->cast<ParameterPtr>()->default_param(); auto add_weight_param = bias_add_weight->cast<ParameterPtr>()->default_param();
auto add_weight_tensor = std::dynamic_pointer_cast<ParamValueLite>(add_weight_param); auto add_weight_tensor = std::dynamic_pointer_cast<ParamValueLite>(add_weight_param);
auto add_weight_data = reinterpret_cast<float *>(add_weight_tensor->tensor_addr()); auto add_weight_data = reinterpret_cast<float *>(add_weight_tensor->tensor_addr());
auto add_weight_shape = add_weight_tensor->tensor_shape();
if (add_weight_tensor->tensor_shape().empty()) { if (add_weight_shape.empty() || (add_weight_shape.size() == 1 && add_weight_shape[0] ==1)) {
if (EOK != memset_s(add_bias_data, kernel_nums * sizeof(float), *add_weight_data, kernel_nums * sizeof(float))) { for (size_t i = 0; i < kernel_nums; i++) {
MS_LOG(EXCEPTION) << "memset_s conv_bias_data failed"; add_bias_data[i] = *add_weight_data;
} }
} else { } else {
if (EOK != memcpy_s(add_bias_data, kernel_nums * sizeof(float), add_weight_data, kernel_nums * sizeof(float))) { if (EOK != memcpy_s(add_bias_data, kernel_nums * sizeof(float), add_weight_data, kernel_nums * sizeof(float))) {

6
mindspore/lite/tools/optimizer/fusion/conv_transform_fusion.cc
View File

@ -145,8 +145,8 @@ const {
// conv has bias,bias_flag true // conv has bias,bias_flag true
bool bias_flag = false; bool bias_flag = false;
if (conv_bias_node != nullptr) { if (conv_bias_node != nullptr) {
auto bias_weight_param = conv_weight_node->cast<ParameterPtr>()->default_param(); auto conv_bias_param = conv_bias_node->cast<ParameterPtr>()->default_param();
auto bias_tensor = std::dynamic_pointer_cast<ParamValueLite>(bias_weight_param); auto bias_tensor = std::dynamic_pointer_cast<ParamValueLite>(conv_bias_param);
bias_data = reinterpret_cast<float *>(bias_tensor->tensor_addr()); bias_data = reinterpret_cast<float *>(bias_tensor->tensor_addr());
bias_flag = true; bias_flag = true;
} else { } else {
@ -187,7 +187,7 @@ const void ConvTransformFusion::CalNewBiasTensor(float *bias_data, int kernel_nu
MS_ASSERT(bias_data != nullptr); MS_ASSERT(bias_data != nullptr);
if (bias_flag) { if (bias_flag) {
auto tmp_bias_data = new(std::nothrow) float[kernel_num]; auto tmp_bias_data = new(std::nothrow) float[kernel_num];
if (EOK != memset_s(bias_data, kernel_num * sizeof(float), 0, kernel_num * sizeof(float))) { if (EOK != memset_s(tmp_bias_data, kernel_num * sizeof(float), 0, kernel_num * sizeof(float))) {
MS_LOG(EXCEPTION) << "memset bias data failed"; MS_LOG(EXCEPTION) << "memset bias data failed";
} }
for (size_t i = 0; i < kernel_num; i++) { for (size_t i = 0; i < kernel_num; i++) {