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!7780 fix the bug introduced by ohter pr 

Merge pull request !7780 from xutianchun/fix_cjh
This commit is contained in:
mindspore-ci-bot 2020-10-26 20:52:07 +08:00 committed by Gitee
parent 9a6be0f48a 022c530de0
commit 8c79cf2c20
3 changed files with 21 additions and 10 deletions
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23
mindspore/lite/tools/converter/quantizer/post_training_quantizer.cc
View File

@ -565,7 +565,7 @@ PostTrainingQuantizer::PostTrainingQuantizer(FuncGraphPtr graph, string path, in
}
STATUS PostTrainingQuantizer::DoQuantInput(double scale, int32_t zeropoint, struct MaxMin *max_min,
std::shared_ptr<PrimitiveC> lite_primitive, const size_t &index) {
std::shared_ptr<PrimitiveC> lite_primitive) {
schema::QuantParamT quant_param;
quant_param.scale = scale;
quant_param.zeroPoint = zeropoint;
@ -573,8 +573,9 @@ STATUS PostTrainingQuantizer::DoQuantInput(double scale, int32_t zeropoint, stru
quant_param.min = max_min->min;
quant_param.numBits = bit_num;
quant_param.narrowRange = false;
quant_param.inited = true;
std::vector<schema::QuantParamT> quant_params = {quant_param};
lite_primitive->SetInputQuantParam(index, quant_params);
lite_primitive->AddInputQuantParam(quant_params);
return RET_OK;
}
@ -589,7 +590,7 @@ STATUS PostTrainingQuantizer::DoQuantOutput(double scale, int zeropoint, struct
quant_param.narrowRange = false;
quant_param.inited = true;
std::vector<schema::QuantParamT> quant_params = {quant_param};
lite_primitive->SetOutputQuantParam(0, quant_params);
lite_primitive->AddOutputQuantParam(quant_params);
return RET_OK;
}
@ -642,7 +643,7 @@ STATUS PostTrainingQuantizer::DoBiasQuant(AnfNodePtr bias, std::shared_ptr<Primi
auto bias_param = std::dynamic_pointer_cast<ParamValueLite>(bias_default_param);
auto active_weight_quant_params = primitive_c->GetInputQuantParams();
if (active_weight_quant_params.size() != 3) {
if (active_weight_quant_params.size() != 2) {
MS_LOG(ERROR) << "unexpected active_weight_quant_params size: " << active_weight_quant_params.size();
return RET_ERROR;
}
@ -721,7 +722,7 @@ STATUS PostTrainingQuantizer::DoBiasQuant(AnfNodePtr bias, std::shared_ptr<Primi
auto quant_data = (int32_t)std::round(raw_datas[i] / bias_scale_tmp);
quant_datas[i] = quant_data;
}
primitive_c->SetInputQuantParam(2, quant_params);
primitive_c->AddInputQuantParam(quant_params);
auto ret = memcpy_s(bias_param->tensor_addr(), bias_param->tensor_size(), quant_datas, shape_size * sizeof(int32_t));
if (ret != EOK) {
MS_LOG(ERROR) << "memcpy_s failed.";
@ -832,19 +833,19 @@ STATUS PostTrainingQuantizer::QuantNode() {
}
if (input_cnode_primitive_c->IsOutputQuantParamsInited()) {
auto quant_param = input_cnode_primitive_c->GetOutputQuantParams().front();
primitive_c->SetInputQuantParam(i - 1, quant_param);
primitive_c->AddInputQuantParam(quant_param);
} else {
// do input quant
double scale = input_scale[cnode];
int32_t zp = input_zero_point[cnode];
DoQuantInput(scale, zp, &input_min_max[cnode], primitive_c, i - 1);
DoQuantInput(scale, zp, &input_min_max[cnode], primitive_c);
}
}
} else {
// do input quant
double scale = input_scale[cnode];
int32_t convInputzeropoint = input_zero_point[cnode];
DoQuantInput(scale, convInputzeropoint, &input_min_max[cnode], primitive_c, 0);
DoQuantInput(scale, convInputzeropoint, &input_min_max[cnode], primitive_c);
// do weight quant
auto weight = cnode->input(2);
bool perchannel = per_channel_;
@ -916,6 +917,12 @@ STATUS PostTrainingQuantizer::PreProcess() {
if (strategy.CanOpPostQuantized(anf)) {
calibrator_->AddQuantizedOp(cnode);
}
auto primitive_c = GetValueNode<std::shared_ptr<PrimitiveC>>(cnode->input(0));
if (primitive_c == nullptr) {
MS_LOG(ERROR) << cnode->fullname_with_scope() << " primitive is null";
continue;
}
primitive_c->ClearInputOutputQuantParam();
}
return RET_OK;
}

2
mindspore/lite/tools/converter/quantizer/post_training_quantizer.h
View File

@ -107,7 +107,7 @@ class PostTrainingQuantizer : public Quantizer {
STATUS QuantNode();
STATUS DoQuantInput(double scale, int32_t zeropoint, struct MaxMin *max_min,
std::shared_ptr<PrimitiveC> lite_primitive, const size_t &index);
std::shared_ptr<PrimitiveC> lite_primitive);
STATUS DoQuantOutput(double scale, int32_t zeropoint, struct MaxMin *max_min, std::shared_ptr<PrimitiveC>);
STATUS DoWeightQuant(AnfNodePtr weight, std::shared_ptr<PrimitiveC> primitive_c, bool perchannel);

6
mindspore/lite/tools/converter/quantizer/quantize_util.h
View File

@ -283,7 +283,11 @@ STATUS QuantFilter(ParamValueLitePtr weight, std::shared_ptr<PrimitiveC> primiti
MS_LOG(ERROR) << "quant_params empty";
return RET_ERROR;
}
primitive_c->SetInputQuantParam(WEIGHT_INDEX, quant_params);
if (quantType == QuantType_PostTraining) {
primitive_c->AddInputQuantParam(quant_params);
} else {
primitive_c->SetInputQuantParam(WEIGHT_INDEX, quant_params);
}
return RET_OK;
}