Added 'how to test manually' document (#5205)

Added 'how to test manually' document

Signed-off-by: Ivan Vagin <ivan.vagin@samsung.com>

2 files changed, 65 insertions, 0 deletions

diff --git a/docs/howto.md b/docs/howto.md
index 76d3b0707..48e26a28a 100644
--- a/docs/howto.md
+++ b/docs/howto.md
@@ -34,3 +34,4 @@ Google provides several pre-built T/F Lite models. Please check [this page](http
 - [How to setup XU3 with Ubuntu 16.04](howto/device/xu3_ubuntu.md)
 - [How to setup XU4 with Ubuntu 16.04](howto/device/xu4_ubuntu.md)
 - [How to add unittest using gtest](howto/HowToAddUnittest.md)
+- [How to manually test NNFW on single model/input pair](howto/HowToTestManualy.md)
diff --git a/docs/howto/HowToTestManualy.md b/docs/howto/HowToTestManualy.md
new file mode 100644
index 000000000..980c0305a
--- /dev/null
+++ b/docs/howto/HowToTestManualy.md
@@ -0,0 +1,64 @@
+# How to test NNFW on single model/input pair
+
+1. Select backend through environment variables:
+    * acl_cl: `export OP_BACKEND_ALLOPS=acl_cl`
+    * acl_neon: `export OP_BACKEND_ALLOPS=acl_neon`
+    * cpu: `export OP_BACKEND_ALLOPS=cpu`
+    * different backends for different operations:
+        ``` 
+        unset OP_BACKEND_ALLOPS
+        export OP_BACKEND_Conv2DNode=cpu
+        export OP_BACKEND_MaxPool2DNode=acl_cl
+        export OP_BACKEND_AvgPool2DNode=acl_neon
+        ```
+        
+2. Select executor through environment variable:
+    * linear: `export EXECUTOR=Linear`
+    * dataflow: `export EXECUTOR=Dataflow`
+    * parallel: `export EXECUTOR=Parallel`
+    
+3. Set library path: `export LD_LIBRARY_PATH=/path/to/nnfw/Product/armv7l-linux.debug/out/lib`
+
+## Test NNFW through NNAPI
+
+### Testing on random input
+1. Generate random input, get reference result using tflite interpreter, dump input and result into file:
+    ```
+    USE_NNAPI=0 /path/to/tflite_run --tflite /path/to/model.tflite --dump /path/to/out.dat
+    ```
+2. Inference with NNFW NNAPI and compare result with reference one:
+    ```
+    USE_NNAPI=1 /path/to/tflite_run --tflite /path/to/model.tflite ---compare /path/to/out.dat
+    ```
+
+### Testing on particular input
+1. Prepare input:
+
+    `tflite_run` consumes input as sequence of floats.
+    
+    For example, you could convert `.jpg` image into such format file with next python3 script:
+    ```
+    from PIL import Image
+    import numpy as np
+    
+    img = Image.open("./image.jpg")
+    np_img = np.array(img.getdata()).reshape(img.size[0], img.size[1], 3).astype(np.float32) / 255.
+    
+    with open('./converted_image.dat', 'wb') as f:
+        for i in np_img.flatten('C'):
+            f.write(i)
+    ```
+
+2. Get reference result using tflite interpreter, dump input and result into file:
+
+    ```
+    USE_NNAPI=0 /path/to/tflite_run --tflite /path/to/model.tflite --input /path/to/input.dat --dump /path/to/out.dat
+    ```
+3. Inference with NNFW NNAPI and compare result with reference one:
+    ```
+    USE_NNAPI=1 /path/to/tflite_run --tflite /path/to/model.tflite ---compare /path/to/out.dat
+    ```
+
+## Test NNFW through NNPackage
+
+TODO: fill this section when NNPackage will be implemented