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When representing the optimized image using CPPN network, current implementation allows for optimizing for a single image per run. This limitation prevents using, e.g., "diversity" objectives during optimization.
This PR adds support for batching for cppn image representation by creating a batch of networks.

here's an example of generating a diverse batch=2 images for objective "mixed4d_3x3_bottleneck_pre_relu_conv:139" of inception network.

image

… a batch of networks. this should allow for forcing diversity when representing images via cppn networks
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