Helper function for init_opt
(self)
| 49 | self.log_vars = [] |
| 50 | |
| 51 | def build_placeholder(self): |
| 52 | '''Helper function for init_opt''' |
| 53 | self.images = tf.placeholder( |
| 54 | tf.float32, [self.batch_size] + self.dataset.image_shape, |
| 55 | name='real_images') |
| 56 | self.wrong_images = tf.placeholder( |
| 57 | tf.float32, [self.batch_size] + self.dataset.image_shape, |
| 58 | name='wrong_images' |
| 59 | ) |
| 60 | self.embeddings = tf.placeholder( |
| 61 | tf.float32, [self.batch_size] + self.dataset.embedding_shape, |
| 62 | name='conditional_embeddings' |
| 63 | ) |
| 64 | |
| 65 | self.generator_lr = tf.placeholder( |
| 66 | tf.float32, [], |
| 67 | name='generator_learning_rate' |
| 68 | ) |
| 69 | self.discriminator_lr = tf.placeholder( |
| 70 | tf.float32, [], |
| 71 | name='discriminator_learning_rate' |
| 72 | ) |
| 73 | |
| 74 | def sample_encoded_context(self, embeddings): |
| 75 | '''Helper function for init_opt''' |