tfmot.quantization.keras.experimental.default_n_bit.default_n_bit_transforms.Conv2DBatchNormReLUQuantize

Ensure FQ does not get placed between Conv, BatchNorm and ReLU.

Inherits From: Conv2DBatchNormQuantize, Transform

Methods

custom_objects

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Dictionary of custom objects introduced by the replacement function.

A Transform may introduce custom Classes and types unknown to Keras. This function should return a dictionary containing these objects in case such types are introduced. It allows model construction to serialize/deserialize these objects.

Returns
Custom objects introduced by the transform as a dictionary.

pattern

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Return the LayerPattern to find in the model graph.

replacement

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Generate a replacement sub-graph for the matched sub-graph.

The fundamental constraint of the replacement is that the replacement sub-graph should consume the same input tensors as the original sub-graph and also produce a final list of tensors which are same in number and shape as the original sub-graph. Not following this could crash model creation, or introduce bugs in the new model graph.

sub-graph, and output layers feeding from the tip of the tree as parameters. These would be needed for complex replace cases.

Args
match_layer Matched sub-graph based on self.pattern().