diff --git a/samples/c_cxx/fns_candy_style_transfer/fns_candy_style_transfer.c b/samples/c_cxx/fns_candy_style_transfer/fns_candy_style_transfer.c
index 0e0acc96e4..07524e9eea 100644
--- a/samples/c_cxx/fns_candy_style_transfer/fns_candy_style_transfer.c
+++ b/samples/c_cxx/fns_candy_style_transfer/fns_candy_style_transfer.c
@@ -261,16 +261,16 @@ int main(int argc, char* argv[]) {
 
   if (execution_provider)
   {
-    if (tcscmp(execution_provider, ORT_TSTR("cpu"))) {
+    if (tcscmp(execution_provider, ORT_TSTR("cpu")) == 0) {
       // Nothing; this is the default
-    } else if (tcscmp(execution_provider, ORT_TSTR("cuda"))) {
+    } else if (tcscmp(execution_provider, ORT_TSTR("cuda")) == 0) {
     #ifdef USE_CUDA
       enable_cuda(session_options);
     #else
       puts("CUDA is not enabled in this build.");
       return -1;
     #endif
-    } else if (tcscmp(execution_provider, ORT_TSTR("dml"))) {
+    } else if (tcscmp(execution_provider, ORT_TSTR("dml")) == 0) {
     #ifdef USE_DML
       enable_dml(session_options);
     #else
diff --git a/samples/c_cxx/imagenet/README.md b/samples/c_cxx/imagenet/README.md
index ca494dc5ff..ab6a24365d 100644
--- a/samples/c_cxx/imagenet/README.md
+++ b/samples/c_cxx/imagenet/README.md
@@ -9,7 +9,7 @@ WARNING: If you want to train the model by yourself, you need at least 500GB dis
 # Install tensorflow
 Install Python 3.x from [python.org](https://www.python.org/), then execute
 ```
-pip install --upgrade tensorflow
+pip install --upgrade tensorflow==1.14
 ```
 For more information, see [Install Tensorflow](https://www.tensorflow.org/install)
 
@@ -36,10 +36,12 @@ tar -zxvf inception_v4_2016_09_09.tar.gz
 The [Inception V4] zip file only contains a single checkpoint file: inception_v4.ckpt. It can't be directly used for inferencing. 
 You need to combine the network definition and the checkpoint. Please follow the steps below:
 
-1. Export the graph
-Create an new folder. At there, execute
+1. Export the graph.
 ```
-git clone https://github.com/tensorflow/models .
+git clone https://github.com/tensorflow/models
+# Copy inception_v4.ckpt into models
+cd models
+# Ignore deprecation warnings
 python research\slim\export_inference_graph.py --model_name=inception_v4 --output_file=grpah.pb
 ```
 
@@ -56,6 +58,12 @@ pip install --upgrade tf2onnx
 python -m tf2onnx.convert --input inception_v4.pb --inputs input:0 --outputs InceptionV4/Logits/Predictions:0 --opset 10 --output inception_v4.onnx
 ```
 
+You should see messages like these:
+
+INFO - Successfully converted TensorFlow model inception_v4.pb to ONNX
+
+INFO - ONNX model is saved at inception_v4.onnx
+
 # Run the inferencing 
 In your build dir of onnxruntime_samples, search for "image_classifier.exe" and run 
 ```
diff --git a/samples/c_cxx/imagenet/main.cc b/samples/c_cxx/imagenet/main.cc
index cf3d54bcbc..e393ac89d1 100644
--- a/samples/c_cxx/imagenet/main.cc
+++ b/samples/c_cxx/imagenet/main.cc
@@ -124,11 +124,10 @@ class Validator : public OutputCollector<TCharString> {
     VerifyInputOutputCount(session_);
     Ort::AllocatorWithDefaultOptions ort_alloc;
     {
-      char* t;
-      session_.GetInputName(0, ort_alloc);
+      char* t = session_.GetInputName(0, ort_alloc);
       input_name_ = my_strdup(t);
       ort_alloc.Free(t);
-      session_.GetOutputName(0, ort_alloc);
+      t = session_.GetOutputName(0, ort_alloc);
       output_name_ = my_strdup(t);
       ort_alloc.Free(t);
     }