add readme.md

Author: zhangxiang1993

Samples/BatchSupport/forReadMe/fixBatchSize.png

@@ -0,0 +1,96 @@
+# Sample of Using Batch
+
+## Overview
+
+This sample tells how to bind and evaluate batches of input in WinML
+
+## Requirements
+
+- [Visual Studio 2017 - 15.4 or higher](https://developer.microsoft.com/en-us/windows/downloads)
+- [Windows 10 - Build 18362 or higher](https://www.microsoft.com/en-us/software-download/windowsinsiderpreviewiso)
+- [Windows SDK - Build 18362 or higher](https://www.microsoft.com/en-us/software-download/windowsinsiderpreviewSDK)
+- Visual Studio Extension for C++/WinRT
+
+  Do the following to add the C++/WinRT extension in Visual Studio.
+  1. Go to **Tools > Extensions and Updates**. 
+  2. Select **Online** in the left pane and search for "WinRT" using the search box.
+  3. Select the **C++/WinRT** extension, click **Download**, and close Visual Studio. The extension should install automatically.
+  4. When the extension has finished installing, re-open Visual Studio.
+
+
+## Build the sample
+
+1. If you download the samples ZIP, be sure to unzip the entire archive, not just the folder with the sample you want to build.
+2. Start Microsoft Visual Studio 2017 and select **File > Open > Project/Solution**.
+3. Starting in the folder where you unzipped the samples, go to the **Samples** subfolder, then the subfolder for this specific sample (**Sample\BatchSupport**). Double-click the Visual Studio solution file (BatchSupport.sln).
+4. Confirm that the project is pointed to the correct SDK that you installed (e.g. 18362). You can do this by right-clicking the project in the **Solution Explorer**, selecting **Properties**, and modifying the **Windows SDK Version**.
+5. Confirm that you are set for the right configuration and platform (for example: Debug, x64).
+6. Build the solution (**Ctrl+Shift+B**).
+
+## Run the sample
+
+1. Open a Command Prompt (in the Windows 10 search bar, type **cmd** and press **Enter**).
+2. Change the current folder to the folder containing the built EXE (`cd <path-to-exe>`).
+3. Run the executable as shown below. Make sure to replace the install location with what matches yours:
+  ```
+  SqueezeNetObjectDetection.exe [fixedBatchSize|freeBatchSize] [TensorFloat|VideoFrame]
+  ```
+4. You should get output similar to the following:
+    ```
+    Loading modelfile 'E:\xianz\Windows-Machine-Learning\Samples\BatchSupport\x64\Debug\SqueezeNet.onnx' on the CPU
+    model file loaded in 906 ticks
+    Binding...
+    Running the model...
+    model run took 31 ticks
+    Result for No.0 input
+    tench, Tinca tinca with confidence of 0.738503
+    Result for No.1 input
+    tabby, tabby cat with confidence of 0.931461
+    Result for No.2 input
+    tench, Tinca tinca with confidence of 0.738503
+    ```
+
+## Prepare Model
+1. Download [WinMLDashboard](https://github.com/microsoft/Windows-Machine-Learning/releases/tag/v0.6.1) 
+2. change the batch dimension of model input and output to a fixed number or -1 (free dimension)
+   <img src='.\forReadMe\fixBatchSize.png' width=400 />  <img src='.\forReadMe\freeBatchSize.png' width=400 /> 
+
+## Create Session and Bind Inputs
+Take binding batches of VideoFrame as example:
+
+### 1. Create Session:
+1.1 for fixed batch dimension:
+   ```C++
+    //create a session and binding
+    LearningModelDeviceKind deviceKind = LearningModelDeviceKind::Cpu;
+    LearningModelSession session(model, LearningModelDevice(deviceKind));
+    LearningModelBinding binding(session);
+   ```
+
+1.2 for free-dimensional batch size:
+   ```C++
+    // create a session and binding
+    LearningModelDeviceKind deviceKind = LearningModelDeviceKind::Cpu;
+    LearningModelSessionOptions options;
+    if ("freeBatchSize" == modelType) { 
+        // If the model has free dimentional batch, override the free dimension with batch_size
+        options.BatchSizeOverride(static_cast<uint32_t>(BATCH_SIZE));
+    }
+    LearningModelSession session(model, LearningModelDevice(deviceKind), options);
+    LearningModelBinding binding(session);
+   ```
+
+### 2. Bind Inputs
+```C++
+    // Create Batches of VideoFrame
+    std::vector<VideoFrame> inputVideoFrames = {};
+    for (hstring imageName : imageNames) {
+        auto imagePath = static_cast<hstring>(GetModulePath().c_str()) + imageName;
+        auto imageFrame = LoadImageFile(imagePath);
+        inputVideoFrames.emplace_back(imageFrame);
+    }
+    auto videoFrames = winrt::single_threaded_vector(std::move(inputFrames));
+
+    // Bind
+    binding.Bind(inputFeatureDescriptor.Current().Name(), inputVideoFrames);
+```