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Fix bunch of links broken after refactor.

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PiperOrigin-RevId: 236702815
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Pulkit Bhuwalka 2019-03-04 12:28:01 -08:00 committed by TensorFlower Gardener
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tensorflow/lite/g3doc/guide/inference.md
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@ -50,15 +50,15 @@ On Android, TensorFlow Lite inference can be performed using either Java or C++
APIs. The Java APIs provide convenience and can be used directly within your APIs. The Java APIs provide convenience and can be used directly within your
Android Activity classes. The C++ APIs on the other hand may offer more Android Activity classes. The C++ APIs on the other hand may offer more
flexibility and speed, but may require writing JNI wrappers to move data between flexibility and speed, but may require writing JNI wrappers to move data between
Java and C++ layers. You can find an example [here](./demo_android.md) Java and C++ layers. You can find an example [here](./android.md).
#### iOS #### iOS
TensorFlow Lite provides Swift/Objective C++ APIs for inference on iOS. An TensorFlow Lite provides Swift/Objective C++ APIs for inference on iOS. An
example can be found [here](./demo_ios.md) example can be found [here](./ios.md).
#### Linux #### Linux
On Linux platforms such as [Raspberry Pi](./rpi.md), TensorFlow Lite C++ and On Linux platforms such as [Raspberry Pi](./build_rpi.md), TensorFlow Lite C++
Python APIs can be used to run inference. and Python APIs can be used to run inference.
## API Guides ## API Guides
@ -68,9 +68,10 @@ experimental bindings for several other languages (C, Swift, Objective-C). In
most cases, the API design reflects a preference for performance over ease of most cases, the API design reflects a preference for performance over ease of
use. TensorFlow Lite is designed for fast inference on small devices so it use. TensorFlow Lite is designed for fast inference on small devices so it
should be no surprise that the APIs try to avoid unnecessary copies at the should be no surprise that the APIs try to avoid unnecessary copies at the
expense of convenience. Similarly, consistency with TensorFlow APIs was not an explicit goal and some variance is to be expected. expense of convenience. Similarly, consistency with TensorFlow APIs was not an
explicit goal and some variance is to be expected.
There is also a [Python API for TensorFlow Lite](./convert/python_api.md). There is also a [Python API for TensorFlow Lite](./../convert/python_api.md).
### Loading a Model ### Loading a Model
@ -202,9 +203,10 @@ interpreter.runForMultipleInputsOutputs(inputs, map_of_indices_to_outputs);
where each entry in `inputs` corresponds to an input tensor and where each entry in `inputs` corresponds to an input tensor and
`map_of_indices_to_outputs` maps indices of output tensors to the corresponding `map_of_indices_to_outputs` maps indices of output tensors to the corresponding
output data. In both cases the tensor indices should correspond to the values output data. In both cases the tensor indices should correspond to the values
given to the [TensorFlow Lite Optimized Converter](convert/cmdline_examples.md) given to the
when the model was created. Be aware that the order of tensors in `input` must [TensorFlow Lite Optimized Converter](./../convert/cmdline_examples.md) when the
match the order given to the `TensorFlow Lite Optimized Converter`. model was created. Be aware that the order of tensors in `input` must match the
order given to the `TensorFlow Lite Optimized Converter`.
The Java API also provides convenient functions for app developers to get the The Java API also provides convenient functions for app developers to get the
index of any model input or output using a tensor name: index of any model input or output using a tensor name: