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update iOS.md
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Oct 9, 2019
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| ## Quickstart with a HelloWorld example | ||
| ## Quickstart with a Hello World example |
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| ```shell | ||
| python trace_model.py | ||
| ``` | ||
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| If everything works well, we should have our model - `model.pt` generated in the same folder. Now copy the model file to our application folder `HelloWorld/model`. | ||
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| More details about TorchScript you can find in [tutorials on pytorch.org](https://pytorch.org/docs/stable/jit.html) |
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The sentence refers to tutorials but the link is to the documentation. Suggestion to change wording to say "More details about TorchScript you can find in [the TorchScript documentation on pytorch.org]."
| ### Install PyTorch C++ libraries via Cocoapods | ||
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| The PyTorch C++ library is available in [Cocoapods](https://cocoapods.org/), to integrate it to our project, we can run | ||
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| ```ruby | ||
| pod install | ||
| ``` | ||
| Now it's time to open the `HelloWorld.xcworkspace` in XCode, select an iOS simulator and hit the build and run button (cmd + R). If everything works well, we should see a wolf picture on the simulator screen along with the prediction result. | ||
| Now it's time to open the `HelloWorld.xcworkspace` in XCode, select an iOS simulator and launch it (cmd + R). If everything works well, we should see a wolf picture on the simulator screen along with the prediction result. |
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Suggestion to add link to wolf picture.
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| #### Init JIT interpreter | ||
| The code might look weird at first glance, but it’ll make sense once we understand our model. The input data of our model is a 3-channel RGB image of shape (3 x H x W), where H and W are expected to be at least 224. The image have to be loaded in to a range of [0, 1] and then normalized using mean = [0.485, 0.456, 0.406] and std = [0.229, 0.224, 0.225]. |
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Change have to has.
"The image have..." --> "The image ..."
| #### Init JIT interpreter | ||
| The code might look weird at first glance, but it’ll make sense once we understand our model. The input data of our model is a 3-channel RGB image of shape (3 x H x W), where H and W are expected to be at least 224. The image have to be loaded in to a range of [0, 1] and then normalized using mean = [0.485, 0.456, 0.406] and std = [0.229, 0.224, 0.225]. | ||
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| #### TorchScript module |
| Finally, we can call this `forward` function to get the output tensor as the results. | ||
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| ```cpp | ||
| auto outputTensor = _impl.forward({tensor}).toTensor(); | ||
| ``` | ||
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| ### Collect results |
| @@ -120,9 +141,7 @@ let sortedResults = zippedResults.sorted { $0.1.floatValue > $1.1.floatValue }.p | |||
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Capitalize "PyTorch Demo App"
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| For more complex use cases, we recommend to check out the PyTorch demo application. | ||
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| The demo app contains two showcases. A camera app that runs a quantized model to predict the images coming from device’s rear-facing camera in real time. And a text-based app that uses a self-trained NLP model to predict the topic from the input string. | ||
| For more complex use cases, we recommend to check out the PyTorch demo application. The demo app contains two showcases. A camera app that runs a quantized model to predict the images coming from device’s rear-facing camera in real time. And a text-based app that uses a self-trained NLP model to predict the topic from the input string. |
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Add link to PyTorch demo application
I can't leave comments for the lines below so consolidating them here:
- Capitalization "Build PyTorch iOS Libraries from Source"
- Capitalization "Setup Local Python Development Environment"
- Capitalization "Build LibTorch.a for iOS Simulator"
- Lines 161 and 170: Add an "s" ---> "After the build succeed(s)..."
- Capitalization "Build LibTorch.a for arm64 Devices"
- Capitalization "XCode Setup"
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| Before we jump into details, we highly recommend following the Pytorch Github page to set up the Python development environment on your local machine. | ||
| Before we jump into details, we highly recommend following the [Pytorch Github page](https://github.com/pytorch/pytorch) to set up the Python development environment on your local machine. | ||
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| ### Model preparation |
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Capitalize "'Model Preparation"
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| ### Code Walkthrough | ||
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| In this part, we are going to walk through the code step by step. The `ViewController.swift` contains most of the code. | ||
| In this part, we are going to walk through the code step by step. All logic happens in `ViewController.swift`. | ||
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| #### Image loading |
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Add some detail to the C++ code