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!12385 [MSLITE] Fix bug of batchnorm_convert_to_scale_pass" 

From: @wang_shaocong
Reviewed-by: @zhang_xue_tong,@zhanghaibo5
Signed-off-by: @zhanghaibo5
This commit is contained in:
mindspore-ci-bot 2021-02-18 19:08:00 +08:00 committed by Gitee
parent 176afda078 fa2e454af3
commit fb4330c878
1 changed files with 12 additions and 2 deletions
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14
mindspore/lite/tools/converter/legacy_optimizer/graph/batchnorm_convert_scale_pass.cc
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@ -40,6 +40,7 @@ namespace {
constexpr const float EPS = 1e-8; constexpr const float EPS = 1e-8;
constexpr const float EPS_DEFAULT_FLOAT = 1e-8; constexpr const float EPS_DEFAULT_FLOAT = 1e-8;
constexpr const float POW_NUM = 0.5; constexpr const float POW_NUM = 0.5;
constexpr uint32_t kQuadrupleNum = 4;
} // namespace } // namespace
STATUS BatchNormConvertScalePass::Run(MetaGraphT *graph) { STATUS BatchNormConvertScalePass::Run(MetaGraphT *graph) {
@ -52,6 +53,11 @@ STATUS BatchNormConvertScalePass::Run(MetaGraphT *graph) {
continue; continue;
} }
auto input_index = node->inputIndex.at(0);
if (graph->allTensors.at(input_index)->dims.empty()) {
MS_LOG(WARNING) << "The shape of input tensor is uncertain.";
return RET_OK;
}
auto status = GenNewScaleTensor(graph, node); auto status = GenNewScaleTensor(graph, node);
if (status != RET_OK) { if (status != RET_OK) {
MS_LOG(ERROR) << "GenNewScaleTensor failed: " << status; MS_LOG(ERROR) << "GenNewScaleTensor failed: " << status;
@ -75,9 +81,13 @@ STATUS BatchNormConvertScalePass::ConvertBNToScale(MetaGraphT *graph, const std:
return RET_ERROR; return RET_ERROR;
} }
// after fusion bn must NHWC // after fusion bn must NHWC
scaleParam->axis = -1;
bnNode->primitive->value.value = scaleParam.release();
auto input0 = bnNode->inputIndex.at(0); auto input0 = bnNode->inputIndex.at(0);
if (graph->allTensors.at(input0)->dims.size() == kQuadrupleNum) {
scaleParam->axis = -1;
} else {
scaleParam->axis = 1;
}
bnNode->primitive->value.value = scaleParam.release();
bnNode->inputIndex.clear(); bnNode->inputIndex.clear();
bnNode->inputIndex.push_back(input0); bnNode->inputIndex.push_back(input0);
graph->allTensors.emplace_back(std::move(newScaleWeightTensor)); graph->allTensors.emplace_back(std::move(newScaleWeightTensor));