How to use the minet.network_routine function in minet
To help you get started, we’ve selected a few minet examples, based on popular ways it is used in public projects.
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rdevon / cortex / arch / shelf / adversarial_clustering.py View on Github 
data.add_noise('y', dist=noise_type, size=dim_l, **noise_parameters)
Encoder, encoder_args = update_encoder_args(x_shape, model_type=encoder_type,
encoder_args=encoder_args)
Decoder, decoder_args = update_decoder_args(x_shape, model_type=decoder_type,
decoder_args=decoder_args)
build_mine_discriminator(models, x_shape, dim_l, Encoder, key='mine_discriminator',
**encoder_args)
build_noise_discriminator(models, dim_l, key='noise_discriminator')
build_encoder(models, x_shape, dim_l, Encoder, **encoder_args)
build_extra_networks(models, x_shape, dim_l, dim_l, Decoder, **decoder_args)
TRAIN_ROUTINES = dict(mine_discriminator=mine_discriminator_routine,
noise_discriminator=noise_discriminator_routine,
encoder=encoder_routine, nets=network_routine)
DEFAULT_CONFIG = dict(data=dict(batch_size=dict(train=64, test=640), duplicate=2))minet
A webmining CLI tool & library for python.
