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benchmark mark accuracy use only 1 tensor

This commit is contained in:
cjh9368 2020-08-05 12:51:20 +08:00
parent 1e3f83ce50
commit 6bb057ea27
1 changed files with 15 additions and 11 deletions
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26
mindspore/lite/tools/benchmark/benchmark.cc
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@ -234,17 +234,21 @@ int Benchmark::CompareOutput() {
MS_LOG(ERROR) << "Cannot find output node: " << nodeName.c_str() << " , compare output data fail."; MS_LOG(ERROR) << "Cannot find output node: " << nodeName.c_str() << " , compare output data fail.";
return RET_ERROR; return RET_ERROR;
} }
for (auto tensor : tensors) { // make sure tensor size is 1
MS_ASSERT(tensor->GetDataType() == DataType_DT_FLOAT); if (tensors.size() != 1) {
MS_ASSERT(tensor->GetData() != nullptr); MS_LOG(ERROR) << "Only support 1 tensor with a name now.";
float bias = CompareData(nodeName, tensor->shape(), static_cast<float *>(tensor->MutableData())); return RET_ERROR;
if (bias >= 0) { }
totalBias += bias; auto &tensor = tensors.front();
totalSize++; MS_ASSERT(tensor->GetDataType() == DataType_DT_FLOAT);
} else { MS_ASSERT(tensor->GetData() != nullptr);
hasError = true; float bias = CompareData(nodeName, tensor->shape(), static_cast<float *>(tensor->MutableData()));
break; if (bias >= 0) {
} totalBias += bias;
totalSize++;
} else {
hasError = true;
break;
} }
} }