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#This encoder is random multinomial noise
import tensorflow as tf
import hyperchamber as hc
from hypergan.encoders.base_encoder import BaseEncoder
TINY = 1e-12
class CategoryEncoder(BaseEncoder):
def required(self):
return "categories".split()
def create(self):
gan = self.gan
ops = self.ops
config = self.config
categories = [self.random_category(gan.batch_size(), size, ops.dtype) for size in config.categories]
self.categories = categories
categories = tf.concat(axis=1, values=categories)
self.sample = categories
return categories
def random_category(self, batch_size, size, dtype):
prior = tf.ones([batch_size, size])*1./size
dist = tf.log(prior + TINY)
sample=tf.multinomial(dist, num_samples=1)[:, 0]
return tf.one_hot(sample, size, dtype=dtype)
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