[GNA] Fixed legacy tests

openvinotoolkit · Sep 7, 2021 · 007ff88 · 007ff88
1 parent 2dcb217
commit 007ff88
Showing 1 changed file with 3 additions and 6 deletions.
diff --git a/inference-engine/src/gna_plugin/frontend/scale_factor_calc.hpp b/inference-engine/src/gna_plugin/frontend/scale_factor_calc.hpp
@@ -479,7 +479,8 @@ class ScaleFactorPerLayer<InferenceEngine::CNNLayer *> {
 
                     if ((!fakeQuantize && quantSibling->_dst_quant.IsScaleSet()) ||
                         (fakeQuantize && quantSibling->_dst_quant.IsScaleSet() && !fp32eq(quantSibling->_dst_quant.GetScale(), 1.0) &&
-                        quantSibling->_dst_quant.GetScale() < inputQuant->_dst_quant.GetScale()) || infiniteLoopCount > 0) {
+                        quantSibling->_dst_quant.GetScale() < inputQuant->_dst_quant.GetScale()) ||
+                        quantSibling->_dst_quant.IsScaleSet() && infiniteLoopCount > 0) {
                         // means we already restarted propagation input memory layer
                         // need to search for requantiseable layer prior memory output layer
                         InferenceEngine::CNNLayerPtr restartedLayer;
@@ -658,7 +659,7 @@ class ScaleFactorPerLayer<InferenceEngine::EltwiseLayer*> {
         auto quantParamsOpposite =
                 InferenceEngine::getInjectedData<QuantizedLayerParams>(InferenceEngine::CNNNetPrevLayer(eltwiseLayer, !inputIx));
 
-        while (in) {
+        while (in && !LayerInfo(in).isInput() && !LayerInfo(in).isMemory() && !LayerInfo(in).isCopy()) {
             auto info = LayerInfo(in);
             if (info.isActivation() || info.isConst()) {
                 auto quantDataForInputLayer = InferenceEngine::getInjectedData<QuantizedLayerParams>(*in);
@@ -681,10 +682,6 @@ class ScaleFactorPerLayer<InferenceEngine::EltwiseLayer*> {
                 return true;
             }
 
-            if (info.has8BOr16BOutput()) {
-                return false;
-            }
-
             if (fakeQuantize && info.isWeightableIdentity()) {
                 auto quantDataForInputLayer = InferenceEngine::getInjectedData<QuantizedLayerParams>(*in);
                 if (!fp32eq(quantDataForInputLayer->_weights_quant.GetScale(), 1.0f)) {