Corrected DNN elementwise multiplication

pull/19765/head
Anastasia Murzova 4 years ago
parent 551d4a8ec1
commit 7a2b3ed471
  1. 6
      modules/dnn/src/tensorflow/tf_importer.cpp
  2. 6
      modules/dnn/test/test_tf_importer.cpp

@ -12,6 +12,7 @@ Implementation of Tensorflow models parser
#include "../precomp.hpp" #include "../precomp.hpp"
#include <opencv2/core/utils/logger.defines.hpp> #include <opencv2/core/utils/logger.defines.hpp>
#include <opencv2/dnn/shape_utils.hpp>
#undef CV_LOG_STRIP_LEVEL #undef CV_LOG_STRIP_LEVEL
#define CV_LOG_STRIP_LEVEL CV_LOG_LEVEL_DEBUG + 1 #define CV_LOG_STRIP_LEVEL CV_LOG_LEVEL_DEBUG + 1
#include <opencv2/core/utils/logger.hpp> #include <opencv2/core/utils/logger.hpp>
@ -1825,6 +1826,7 @@ void TFImporter::parseNode(const tensorflow::NodeDef& layer_)
{ {
// Check if all the inputs have the same shape. // Check if all the inputs have the same shape.
bool equalInpShapes = true; bool equalInpShapes = true;
bool isShapeOnes = false;
MatShape outShape0; MatShape outShape0;
for (int ii = 0; ii < num_inputs && !netInputShapes.empty(); ii++) for (int ii = 0; ii < num_inputs && !netInputShapes.empty(); ii++)
{ {
@ -1845,12 +1847,14 @@ void TFImporter::parseNode(const tensorflow::NodeDef& layer_)
else if (outShape != outShape0) else if (outShape != outShape0)
{ {
equalInpShapes = false; equalInpShapes = false;
isShapeOnes = isAllOnes(outShape, 2, outShape.size()) ||
isAllOnes(outShape0, 2, outShape0.size());
break; break;
} }
} }
int id; int id;
if (equalInpShapes || netInputShapes.empty()) if (equalInpShapes || netInputShapes.empty() || (!equalInpShapes && isShapeOnes))
{ {
layerParams.set("operation", type == "RealDiv" ? "div" : "prod"); layerParams.set("operation", type == "RealDiv" ? "div" : "prod");
id = dstNet.addLayer(name, "Eltwise", layerParams); id = dstNet.addLayer(name, "Eltwise", layerParams);

@ -210,6 +210,12 @@ TEST_P(Test_TensorFlow_layers, eltwise_add_vec)
runTensorFlowNet("eltwise_add_vec"); runTensorFlowNet("eltwise_add_vec");
} }
TEST_P(Test_TensorFlow_layers, eltwise_mul_vec)
{
runTensorFlowNet("eltwise_mul_vec");
}
TEST_P(Test_TensorFlow_layers, channel_broadcast) TEST_P(Test_TensorFlow_layers, channel_broadcast)
{ {
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019) if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019)

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