Merge pull request #20466 from rogday:efficientnet_fix_34

alalek · alalek · commit 221bfa4c67d6 · 2021-08-10T22:18:17.000Z
diff --git a/modules/dnn/src/tensorflow/tf_importer.cpp b/modules/dnn/src/tensorflow/tf_importer.cpp
@@ -647,7 +647,7 @@ const TFImporter::DispatchMap TFImporter::buildDispatchMap()
     dispatch["PriorBox"] = &TFImporter::parsePriorBox;
     dispatch["Softmax"] = &TFImporter::parseSoftmax;
     dispatch["CropAndResize"] = &TFImporter::parseCropAndResize;
-    dispatch["Mean"] = dispatch["Sum"] = &TFImporter::parseMean;
+    dispatch["Mean"] = dispatch["Sum"] = dispatch["Max"] = &TFImporter::parseMean;
     dispatch["Pack"] = &TFImporter::parsePack;
     dispatch["ClipByValue"] = &TFImporter::parseClipByValue;
     dispatch["LeakyRelu"] = &TFImporter::parseLeakyRelu;
@@ -657,6 +657,7 @@ const TFImporter::DispatchMap TFImporter::buildDispatchMap()
     return dispatch;
 }
 
+// "Conv2D" "SpaceToBatchND" "DepthwiseConv2dNative" "Pad" "MirrorPad" "Conv3D"
 void TFImporter::parseConvolution(tensorflow::GraphDef& net, const tensorflow::NodeDef& layer_, LayerParams& layerParams)
 {
     tensorflow::NodeDef layer = layer_;
@@ -876,6 +877,7 @@ void TFImporter::parseConvolution(tensorflow::GraphDef& net, const tensorflow::N
         data_layouts[name] = DATA_LAYOUT_NHWC;
 }
 
+// "BiasAdd" "Add" "AddV2" "Sub" "AddN"
 void TFImporter::parseBias(tensorflow::GraphDef& net, const tensorflow::NodeDef& layer, LayerParams& layerParams)
 {
     const std::string& name = layer.name();
@@ -1087,6 +1089,7 @@ void TFImporter::parseReshape(tensorflow::GraphDef& net, const tensorflow::NodeD
     }
 }
 
+// "Flatten" "Squeeze"
 void TFImporter::parseFlatten(tensorflow::GraphDef& net, const tensorflow::NodeDef& layer, LayerParams& layerParams)
 {
     const std::string& name = layer.name();
@@ -1245,6 +1248,7 @@ void TFImporter::parseLrn(tensorflow::GraphDef& net, const tensorflow::NodeDef&
     connectToAllBlobs(layer_id, dstNet, parsePin(layer.input(0)), id, num_inputs);
 }
 
+// "Concat" "ConcatV2"
 void TFImporter::parseConcat(tensorflow::GraphDef& net, const tensorflow::NodeDef& layer, LayerParams& layerParams)
 {
     const std::string& name = layer.name();
@@ -1295,6 +1299,7 @@ void TFImporter::parseConcat(tensorflow::GraphDef& net, const tensorflow::NodeDe
     }
 }
 
+// "MaxPool" "MaxPool3D"
 void TFImporter::parseMaxPool(tensorflow::GraphDef& net, const tensorflow::NodeDef& layer, LayerParams& layerParams)
 {
     const std::string& name = layer.name();
@@ -1316,6 +1321,7 @@ void TFImporter::parseMaxPool(tensorflow::GraphDef& net, const tensorflow::NodeD
     connectToAllBlobs(layer_id, dstNet, parsePin(inputName), id, num_inputs);
 }
 
+// "AvgPool" "AvgPool3D"
 void TFImporter::parseAvgPool(tensorflow::GraphDef& net, const tensorflow::NodeDef& layer, LayerParams& layerParams)
 {
     const std::string& name = layer.name();
@@ -1502,6 +1508,7 @@ void TFImporter::parseStridedSlice(tensorflow::GraphDef& net, const tensorflow::
     connect(layer_id, dstNet, parsePin(layer.input(0)), id, 0);
 }
 
+// "Mul" "RealDiv"
 void TFImporter::parseMul(tensorflow::GraphDef& net, const tensorflow::NodeDef& layer, LayerParams& layerParams)
 {
     const std::string& name = layer.name();
@@ -1659,6 +1666,7 @@ void TFImporter::parseMul(tensorflow::GraphDef& net, const tensorflow::NodeDef&
     }
 }
 
+// "FusedBatchNorm" "FusedBatchNormV3"
 void TFImporter::parseFusedBatchNorm(tensorflow::GraphDef& net, const tensorflow::NodeDef& layer, LayerParams& layerParams)
 {
     // op: "FusedBatchNorm"
@@ -1918,6 +1926,7 @@ void TFImporter::parseBlockLSTM(tensorflow::GraphDef& net, const tensorflow::Nod
     data_layouts[name] = DATA_LAYOUT_UNKNOWN;
 }
 
+// "ResizeNearestNeighbor" "ResizeBilinear" "FusedResizeAndPadConv2D"
 void TFImporter::parseResize(tensorflow::GraphDef& net, const tensorflow::NodeDef& layer_, LayerParams& layerParams)
 {
     tensorflow::NodeDef layer = layer_;
@@ -2106,6 +2115,7 @@ void TFImporter::parseCropAndResize(tensorflow::GraphDef& net, const tensorflow:
     connect(layer_id, dstNet, parsePin(layer.input(1)), id, 1);
 }
 
+// "Mean" "Sum" "Max"
 void TFImporter::parseMean(tensorflow::GraphDef& net, const tensorflow::NodeDef& layer, LayerParams& layerParams)
 {
     // Computes the mean of elements across dimensions of a tensor.
@@ -2124,7 +2134,12 @@ void TFImporter::parseMean(tensorflow::GraphDef& net, const tensorflow::NodeDef&
     const std::string& name = layer.name();
     const std::string& type = layer.op();
     const int num_inputs = layer.input_size();
+    std::string pool_type = cv::toLowerCase(type);
 
+    if (pool_type == "mean")
+    {
+        pool_type = "ave";
+    }
     CV_CheckGT(num_inputs, 0, "");
 
     Mat indices = getTensorContent(getConstBlob(layer, value_id, 1));
@@ -2161,7 +2176,7 @@ void TFImporter::parseMean(tensorflow::GraphDef& net, const tensorflow::NodeDef&
         LayerParams avgLp;
         std::string avgName = name + "/avg";
         CV_Assert(layer_id.find(avgName) == layer_id.end());
-        avgLp.set("pool", type == "Mean" ? "ave" : "sum");
+        avgLp.set("pool", pool_type);
         // pooling kernel H x 1
         avgLp.set("global_pooling_h", true);
         avgLp.set("kernel_w", 1);
@@ -2202,7 +2217,7 @@ void TFImporter::parseMean(tensorflow::GraphDef& net, const tensorflow::NodeDef&
         int axis = toNCHW(indices.at<int>(0));
         if (axis == 2 || axis == 3)
         {
-            layerParams.set("pool", type == "Mean" ? "ave" : "sum");
+            layerParams.set("pool", pool_type);
             layerParams.set(axis == 2 ? "kernel_w" : "kernel_h", 1);
             layerParams.set(axis == 2 ? "global_pooling_h" : "global_pooling_w", true);
             int id = dstNet.addLayer(name, "Pooling", layerParams);
@@ -2234,7 +2249,7 @@ void TFImporter::parseMean(tensorflow::GraphDef& net, const tensorflow::NodeDef&
             Pin inpId = parsePin(layer.input(0));
             addPermuteLayer(order, name + "/nhwc", inpId);
 
-            layerParams.set("pool", type == "Mean" ? "ave" : "sum");
+            layerParams.set("pool", pool_type);
             layerParams.set("kernel_h", 1);
             layerParams.set("global_pooling_w", true);
             int id = dstNet.addLayer(name, "Pooling", layerParams);
@@ -2264,7 +2279,7 @@ void TFImporter::parseMean(tensorflow::GraphDef& net, const tensorflow::NodeDef&
         if (indices.total() != 2 || indices.at<int>(0) != 1 || indices.at<int>(1) != 2)
             CV_Error(Error::StsNotImplemented, "Unsupported mode of reduce_mean or reduce_sum operation.");
 
-        layerParams.set("pool", type == "Mean" ? "ave" : "sum");
+        layerParams.set("pool", pool_type);
         layerParams.set("global_pooling", true);
         int id = dstNet.addLayer(name, "Pooling", layerParams);
         layer_id[name] = id;
@@ -2368,6 +2383,7 @@ void TFImporter::parseLeakyRelu(tensorflow::GraphDef& net, const tensorflow::Nod
     connectToAllBlobs(layer_id, dstNet, parsePin(layer.input(0)), id, num_inputs);
 }
 
+// "Abs" "Tanh" "Sigmoid" "Relu" "Elu" "Exp" "Identity" "Relu6"
 void TFImporter::parseActivation(tensorflow::GraphDef& net, const tensorflow::NodeDef& layer, LayerParams& layerParams)
 {
     const std::string& name = layer.name();
diff --git a/modules/dnn/test/test_tf_importer.cpp b/modules/dnn/test/test_tf_importer.cpp
@@ -128,18 +128,35 @@ TEST_P(Test_TensorFlow_layers, reduce_mean)
     runTensorFlowNet("global_pool_by_axis");
 }
 
+TEST_P(Test_TensorFlow_layers, reduce_max)
+{
+    if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019)
+        applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER);
+    runTensorFlowNet("max_pool_by_axis");
+}
+
 TEST_P(Test_TensorFlow_layers, reduce_sum)
 {
     if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019)
         applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER);
     runTensorFlowNet("sum_pool_by_axis");
 }
 
+TEST_P(Test_TensorFlow_layers, reduce_max_channel)
+{
+    runTensorFlowNet("reduce_max_channel");
+}
+
 TEST_P(Test_TensorFlow_layers, reduce_sum_channel)
 {
     runTensorFlowNet("reduce_sum_channel");
 }
 
+TEST_P(Test_TensorFlow_layers, reduce_max_channel_keep_dims)
+{
+    runTensorFlowNet("reduce_max_channel", false, 0.0, 0.0, false, "_keep_dims");
+}
+
 TEST_P(Test_TensorFlow_layers, reduce_sum_channel_keep_dims)
 {
     runTensorFlowNet("reduce_sum_channel", false, 0.0, 0.0, false, "_keep_dims");
@@ -386,6 +403,11 @@ TEST_P(Test_TensorFlow_layers, pooling_reduce_mean)
     runTensorFlowNet("reduce_mean");  // an average pooling over all spatial dimensions.
 }
 
+TEST_P(Test_TensorFlow_layers, pooling_reduce_max)
+{
+    runTensorFlowNet("reduce_max");  // a MAX pooling over all spatial dimensions.
+}
+
 TEST_P(Test_TensorFlow_layers, pooling_reduce_sum)
 {
     runTensorFlowNet("reduce_sum");  // a SUM pooling over all spatial dimensions.

Original file line number	Diff line number	Diff line change
`@@ -647,7 +647,7 @@ const TFImporter::DispatchMap TFImporter::buildDispatchMap()`
`647`	`647`	`dispatch["PriorBox"] = &TFImporter::parsePriorBox;`
`648`	`648`	`dispatch["Softmax"] = &TFImporter::parseSoftmax;`
`649`	`649`	`dispatch["CropAndResize"] = &TFImporter::parseCropAndResize;`
`650`		`- dispatch["Mean"] = dispatch["Sum"] = &TFImporter::parseMean;`
	`650`	`+ dispatch["Mean"] = dispatch["Sum"] = dispatch["Max"] = &TFImporter::parseMean;`
`651`	`651`	`dispatch["Pack"] = &TFImporter::parsePack;`
`652`	`652`	`dispatch["ClipByValue"] = &TFImporter::parseClipByValue;`
`653`	`653`	`dispatch["LeakyRelu"] = &TFImporter::parseLeakyRelu;`
`@@ -657,6 +657,7 @@ const TFImporter::DispatchMap TFImporter::buildDispatchMap()`
`657`	`657`	`return dispatch;`
`658`	`658`	`}`
`659`	`659`
	`660`	`+// "Conv2D" "SpaceToBatchND" "DepthwiseConv2dNative" "Pad" "MirrorPad" "Conv3D"`
`660`	`661`	`void TFImporter::parseConvolution(tensorflow::GraphDef& net, const tensorflow::NodeDef& layer_, LayerParams& layerParams)`
`661`	`662`	`{`
`662`	`663`	`tensorflow::NodeDef layer = layer_;`
`@@ -876,6 +877,7 @@ void TFImporter::parseConvolution(tensorflow::GraphDef& net, const tensorflow::N`
`876`	`877`	`data_layouts[name] = DATA_LAYOUT_NHWC;`
`877`	`878`	`}`
`878`	`879`
	`880`	`+// "BiasAdd" "Add" "AddV2" "Sub" "AddN"`
`879`	`881`	`void TFImporter::parseBias(tensorflow::GraphDef& net, const tensorflow::NodeDef& layer, LayerParams& layerParams)`
`880`	`882`	`{`
`881`	`883`	`const std::string& name = layer.name();`
`@@ -1087,6 +1089,7 @@ void TFImporter::parseReshape(tensorflow::GraphDef& net, const tensorflow::NodeD`
`1087`	`1089`	`}`
`1088`	`1090`	`}`
`1089`	`1091`
	`1092`	`+// "Flatten" "Squeeze"`
`1090`	`1093`	`void TFImporter::parseFlatten(tensorflow::GraphDef& net, const tensorflow::NodeDef& layer, LayerParams& layerParams)`
`1091`	`1094`	`{`
`1092`	`1095`	`const std::string& name = layer.name();`
`@@ -1245,6 +1248,7 @@ void TFImporter::parseLrn(tensorflow::GraphDef& net, const tensorflow::NodeDef&`
`1245`	`1248`	`connectToAllBlobs(layer_id, dstNet, parsePin(layer.input(0)), id, num_inputs);`
`1246`	`1249`	`}`
`1247`	`1250`
	`1251`	`+// "Concat" "ConcatV2"`
`1248`	`1252`	`void TFImporter::parseConcat(tensorflow::GraphDef& net, const tensorflow::NodeDef& layer, LayerParams& layerParams)`
`1249`	`1253`	`{`
`1250`	`1254`	`const std::string& name = layer.name();`
`@@ -1295,6 +1299,7 @@ void TFImporter::parseConcat(tensorflow::GraphDef& net, const tensorflow::NodeDe`
`1295`	`1299`	`}`
`1296`	`1300`	`}`
`1297`	`1301`
	`1302`	`+// "MaxPool" "MaxPool3D"`
`1298`	`1303`	`void TFImporter::parseMaxPool(tensorflow::GraphDef& net, const tensorflow::NodeDef& layer, LayerParams& layerParams)`
`1299`	`1304`	`{`
`1300`	`1305`	`const std::string& name = layer.name();`
`@@ -1316,6 +1321,7 @@ void TFImporter::parseMaxPool(tensorflow::GraphDef& net, const tensorflow::NodeD`
`1316`	`1321`	`connectToAllBlobs(layer_id, dstNet, parsePin(inputName), id, num_inputs);`
`1317`	`1322`	`}`
`1318`	`1323`
	`1324`	`+// "AvgPool" "AvgPool3D"`
`1319`	`1325`	`void TFImporter::parseAvgPool(tensorflow::GraphDef& net, const tensorflow::NodeDef& layer, LayerParams& layerParams)`
`1320`	`1326`	`{`
`1321`	`1327`	`const std::string& name = layer.name();`
`@@ -1502,6 +1508,7 @@ void TFImporter::parseStridedSlice(tensorflow::GraphDef& net, const tensorflow::`
`1502`	`1508`	`connect(layer_id, dstNet, parsePin(layer.input(0)), id, 0);`
`1503`	`1509`	`}`
`1504`	`1510`
	`1511`	`+// "Mul" "RealDiv"`
`1505`	`1512`	`void TFImporter::parseMul(tensorflow::GraphDef& net, const tensorflow::NodeDef& layer, LayerParams& layerParams)`
`1506`	`1513`	`{`
`1507`	`1514`	`const std::string& name = layer.name();`
`@@ -1659,6 +1666,7 @@ void TFImporter::parseMul(tensorflow::GraphDef& net, const tensorflow::NodeDef&`
`1659`	`1666`	`}`
`1660`	`1667`	`}`
`1661`	`1668`
	`1669`	`+// "FusedBatchNorm" "FusedBatchNormV3"`
`1662`	`1670`	`void TFImporter::parseFusedBatchNorm(tensorflow::GraphDef& net, const tensorflow::NodeDef& layer, LayerParams& layerParams)`
`1663`	`1671`	`{`
`1664`	`1672`	`// op: "FusedBatchNorm"`
`@@ -1918,6 +1926,7 @@ void TFImporter::parseBlockLSTM(tensorflow::GraphDef& net, const tensorflow::Nod`
`1918`	`1926`	`data_layouts[name] = DATA_LAYOUT_UNKNOWN;`
`1919`	`1927`	`}`
`1920`	`1928`
	`1929`	`+// "ResizeNearestNeighbor" "ResizeBilinear" "FusedResizeAndPadConv2D"`
`1921`	`1930`	`void TFImporter::parseResize(tensorflow::GraphDef& net, const tensorflow::NodeDef& layer_, LayerParams& layerParams)`
`1922`	`1931`	`{`
`1923`	`1932`	`tensorflow::NodeDef layer = layer_;`
`@@ -2106,6 +2115,7 @@ void TFImporter::parseCropAndResize(tensorflow::GraphDef& net, const tensorflow:`
`2106`	`2115`	`connect(layer_id, dstNet, parsePin(layer.input(1)), id, 1);`
`2107`	`2116`	`}`
`2108`	`2117`
	`2118`	`+// "Mean" "Sum" "Max"`
`2109`	`2119`	`void TFImporter::parseMean(tensorflow::GraphDef& net, const tensorflow::NodeDef& layer, LayerParams& layerParams)`
`2110`	`2120`	`{`
`2111`	`2121`	`// Computes the mean of elements across dimensions of a tensor.`
`@@ -2124,7 +2134,12 @@ void TFImporter::parseMean(tensorflow::GraphDef& net, const tensorflow::NodeDef&`
`2124`	`2134`	`const std::string& name = layer.name();`
`2125`	`2135`	`const std::string& type = layer.op();`
`2126`	`2136`	`const int num_inputs = layer.input_size();`
	`2137`	`+ std::string pool_type = cv::toLowerCase(type);`
`2127`	`2138`
	`2139`	`+ if (pool_type == "mean")`
	`2140`	`+ {`
	`2141`	`+ pool_type = "ave";`
	`2142`	`+ }`
`2128`	`2143`	`CV_CheckGT(num_inputs, 0, "");`
`2129`	`2144`
`2130`	`2145`	`Mat indices = getTensorContent(getConstBlob(layer, value_id, 1));`
`@@ -2161,7 +2176,7 @@ void TFImporter::parseMean(tensorflow::GraphDef& net, const tensorflow::NodeDef&`
`2161`	`2176`	`LayerParams avgLp;`
`2162`	`2177`	`std::string avgName = name + "/avg";`
`2163`	`2178`	`CV_Assert(layer_id.find(avgName) == layer_id.end());`
`2164`		`- avgLp.set("pool", type == "Mean" ? "ave" : "sum");`
	`2179`	`+ avgLp.set("pool", pool_type);`
`2165`	`2180`	`// pooling kernel H x 1`
`2166`	`2181`	`avgLp.set("global_pooling_h", true);`
`2167`	`2182`	`avgLp.set("kernel_w", 1);`
`@@ -2202,7 +2217,7 @@ void TFImporter::parseMean(tensorflow::GraphDef& net, const tensorflow::NodeDef&`
`2202`	`2217`	`int axis = toNCHW(indices.at<int>(0));`
`2203`	`2218`	`if (axis == 2 \|\| axis == 3)`
`2204`	`2219`	`{`
`2205`		`- layerParams.set("pool", type == "Mean" ? "ave" : "sum");`
	`2220`	`+ layerParams.set("pool", pool_type);`
`2206`	`2221`	`layerParams.set(axis == 2 ? "kernel_w" : "kernel_h", 1);`
`2207`	`2222`	`layerParams.set(axis == 2 ? "global_pooling_h" : "global_pooling_w", true);`
`2208`	`2223`	`int id = dstNet.addLayer(name, "Pooling", layerParams);`
`@@ -2234,7 +2249,7 @@ void TFImporter::parseMean(tensorflow::GraphDef& net, const tensorflow::NodeDef&`
`2234`	`2249`	`Pin inpId = parsePin(layer.input(0));`
`2235`	`2250`	`addPermuteLayer(order, name + "/nhwc", inpId);`
`2236`	`2251`
`2237`		`- layerParams.set("pool", type == "Mean" ? "ave" : "sum");`
	`2252`	`+ layerParams.set("pool", pool_type);`
`2238`	`2253`	`layerParams.set("kernel_h", 1);`
`2239`	`2254`	`layerParams.set("global_pooling_w", true);`
`2240`	`2255`	`int id = dstNet.addLayer(name, "Pooling", layerParams);`
`@@ -2264,7 +2279,7 @@ void TFImporter::parseMean(tensorflow::GraphDef& net, const tensorflow::NodeDef&`
`2264`	`2279`	`if (indices.total() != 2 \|\| indices.at<int>(0) != 1 \|\| indices.at<int>(1) != 2)`
`2265`	`2280`	`CV_Error(Error::StsNotImplemented, "Unsupported mode of reduce_mean or reduce_sum operation.");`
`2266`	`2281`
`2267`		`- layerParams.set("pool", type == "Mean" ? "ave" : "sum");`
	`2282`	`+ layerParams.set("pool", pool_type);`
`2268`	`2283`	`layerParams.set("global_pooling", true);`
`2269`	`2284`	`int id = dstNet.addLayer(name, "Pooling", layerParams);`
`2270`	`2285`	`layer_id[name] = id;`
`@@ -2368,6 +2383,7 @@ void TFImporter::parseLeakyRelu(tensorflow::GraphDef& net, const tensorflow::Nod`
`2368`	`2383`	`connectToAllBlobs(layer_id, dstNet, parsePin(layer.input(0)), id, num_inputs);`
`2369`	`2384`	`}`
`2370`	`2385`
	`2386`	`+// "Abs" "Tanh" "Sigmoid" "Relu" "Elu" "Exp" "Identity" "Relu6"`
`2371`	`2387`	`void TFImporter::parseActivation(tensorflow::GraphDef& net, const tensorflow::NodeDef& layer, LayerParams& layerParams)`
`2372`	`2388`	`{`
`2373`	`2389`	`const std::string& name = layer.name();`
Original file line number	Diff line number	Diff line change
`@@ -128,18 +128,35 @@ TEST_P(Test_TensorFlow_layers, reduce_mean)`
`128`	`128`	`runTensorFlowNet("global_pool_by_axis");`
`129`	`129`	`}`
`130`	`130`
	`131`	`+TEST_P(Test_TensorFlow_layers, reduce_max)`
	`132`	`+{`
	`133`	`+ if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019)`
	`134`	`+ applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER);`
	`135`	`+ runTensorFlowNet("max_pool_by_axis");`
	`136`	`+}`
	`137`	`+`
`131`	`138`	`TEST_P(Test_TensorFlow_layers, reduce_sum)`
`132`	`139`	`{`
`133`	`140`	`if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019)`
`134`	`141`	`applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER);`
`135`	`142`	`runTensorFlowNet("sum_pool_by_axis");`
`136`	`143`	`}`
`137`	`144`
	`145`	`+TEST_P(Test_TensorFlow_layers, reduce_max_channel)`
	`146`	`+{`
	`147`	`+ runTensorFlowNet("reduce_max_channel");`
	`148`	`+}`
	`149`	`+`
`138`	`150`	`TEST_P(Test_TensorFlow_layers, reduce_sum_channel)`
`139`	`151`	`{`
`140`	`152`	`runTensorFlowNet("reduce_sum_channel");`
`141`	`153`	`}`
`142`	`154`
	`155`	`+TEST_P(Test_TensorFlow_layers, reduce_max_channel_keep_dims)`
	`156`	`+{`
	`157`	`+ runTensorFlowNet("reduce_max_channel", false, 0.0, 0.0, false, "_keep_dims");`
	`158`	`+}`
	`159`	`+`
`143`	`160`	`TEST_P(Test_TensorFlow_layers, reduce_sum_channel_keep_dims)`
`144`	`161`	`{`
`145`	`162`	`runTensorFlowNet("reduce_sum_channel", false, 0.0, 0.0, false, "_keep_dims");`
`@@ -386,6 +403,11 @@ TEST_P(Test_TensorFlow_layers, pooling_reduce_mean)`
`386`	`403`	`runTensorFlowNet("reduce_mean"); // an average pooling over all spatial dimensions.`
`387`	`404`	`}`
`388`	`405`
	`406`	`+TEST_P(Test_TensorFlow_layers, pooling_reduce_max)`
	`407`	`+{`
	`408`	`+ runTensorFlowNet("reduce_max"); // a MAX pooling over all spatial dimensions.`
	`409`	`+}`
	`410`	`+`
`389`	`411`	`TEST_P(Test_TensorFlow_layers, pooling_reduce_sum)`
`390`	`412`	`{`
`391`	`413`	`runTensorFlowNet("reduce_sum"); // a SUM pooling over all spatial dimensions.`