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Update tfmot compression api RFC: update img srcs.
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rfcs/20201221-tfmot-compression-api.md

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@@ -153,7 +153,7 @@ We also want to provide an example of well-known compression algorithms. Here’
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### Weight compression algorithm API
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<p align="center">
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<img src=20201221-tfmot-compression-api/class_graph.png"/>
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<img src=20201221-tfmot-compression-api/class_graph.png />
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</p>
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This is an API for a layer weight based compression algorithm.
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1. `get_compressible_weights`
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<p align="center">
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<img src=20201221-tfmot-compression-api/get_compressible_weights.png"/>
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<img src=20201221-tfmot-compression-api/get_compressible_weights.png />
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</p>
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```python
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training_model = optimize_training(model, params)
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1. `init_training_weights_repr`
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<p align="center">
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<img src=20201221-tfmot-compression-api/init_training_weights_repr.png"/>
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<img src=20201221-tfmot-compression-api/init_training_weights_repr.png />
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</p>
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```python
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training_model = optimize_training(model, params)
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1. `fake_decompress`
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<p align="center">
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<img src=20201221-tfmot-compression-api/fake_decompress.png"/>
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<img src=20201221-tfmot-compression-api/fake_decompress.png />
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</p>
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```python
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training_model.fit(x_train, y_train, epochs=2)
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1. `compress`
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<p align="center">
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<img src=20201221-tfmot-compression-api/compress.png"/>
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<img src=20201221-tfmot-compression-api/compress.png />
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</p>
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```python
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compressed_model = optimize_inference(training_model, params)
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1. `decompress`
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<p align="center">
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<img src=20201221-tfmot-compression-api/decompress.png"/>
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<img src=20201221-tfmot-compression-api/decompress.png />
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</p>
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```python
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compressed_model.evaluate(x_test, y_test, verbose=2)

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