| CPC G06V 40/172 (2022.01) [G06T 5/77 (2024.01)] | 16 Claims |

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1. A method for image generation comprising:
identifying, by a machine learning model, an image generation network that includes an encoder and a decoder;
pruning channels of a first layer of a block of the encoder;
pruning channels of a second layer of the block of the encoder based on the pruned channels of the first layer of the block of the encoder;
pruning channels of a block of the decoder that is connected to the block of the encoder by a skip connection, wherein the channels of the block of the decoder are pruned based on the pruned channels of the block of the encoder;
wherein pruning channels of the block of the decoder comprises:
pruning channels of a first layer of the block of the decoder based on the pruned channels of the first layer of the block of the encoder; and
pruning channels of a second layer of the block of the decoder based on the pruned channels of the second layer of the block of the encoder; and
generating an image using the image generation network based on the pruned channels of the block of the encoder and the pruned channels of the block of the decoder.
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