Fix bunch of links broken after refactor.
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@ -50,15 +50,15 @@ On Android, TensorFlow Lite inference can be performed using either Java or C++
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APIs. The Java APIs provide convenience and can be used directly within your
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Android Activity classes. The C++ APIs on the other hand may offer more
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flexibility and speed, but may require writing JNI wrappers to move data between
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Java and C++ layers. You can find an example [here](./demo_android.md)
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Java and C++ layers. You can find an example [here](./android.md).
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#### iOS
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TensorFlow Lite provides Swift/Objective C++ APIs for inference on iOS. An
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example can be found [here](./demo_ios.md)
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example can be found [here](./ios.md).
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#### Linux
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On Linux platforms such as [Raspberry Pi](./rpi.md), TensorFlow Lite C++ and
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Python APIs can be used to run inference.
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On Linux platforms such as [Raspberry Pi](./build_rpi.md), TensorFlow Lite C++
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and Python APIs can be used to run inference.
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## API Guides
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@ -68,9 +68,10 @@ experimental bindings for several other languages (C, Swift, Objective-C). In
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most cases, the API design reflects a preference for performance over ease of
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use. TensorFlow Lite is designed for fast inference on small devices so it
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should be no surprise that the APIs try to avoid unnecessary copies at the
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expense of convenience. Similarly, consistency with TensorFlow APIs was not an explicit goal and some variance is to be expected.
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expense of convenience. Similarly, consistency with TensorFlow APIs was not an
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explicit goal and some variance is to be expected.
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There is also a [Python API for TensorFlow Lite](./convert/python_api.md).
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There is also a [Python API for TensorFlow Lite](./../convert/python_api.md).
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### Loading a Model
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@ -202,9 +203,10 @@ interpreter.runForMultipleInputsOutputs(inputs, map_of_indices_to_outputs);
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where each entry in `inputs` corresponds to an input tensor and
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`map_of_indices_to_outputs` maps indices of output tensors to the corresponding
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output data. In both cases the tensor indices should correspond to the values
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given to the [TensorFlow Lite Optimized Converter](convert/cmdline_examples.md)
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when the model was created. Be aware that the order of tensors in `input` must
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match the order given to the `TensorFlow Lite Optimized Converter`.
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given to the
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[TensorFlow Lite Optimized Converter](./../convert/cmdline_examples.md) when the
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model was created. Be aware that the order of tensors in `input` must match the
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order given to the `TensorFlow Lite Optimized Converter`.
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The Java API also provides convenient functions for app developers to get the
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index of any model input or output using a tensor name:
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