(self, z, y)
| 45 | tf.TensorSpec((None,), tf.int32, 'label')] |
| 46 | |
| 47 | def generator(self, z, y): |
| 48 | l = FullyConnected('fc0', tf.concat([z, y], 1), 1024, activation=BNReLU) |
| 49 | l = FullyConnected('fc1', tf.concat([l, y], 1), 64 * 2 * 7 * 7, activation=BNReLU) |
| 50 | l = tf.reshape(l, [-1, 7, 7, 64 * 2]) |
| 51 | |
| 52 | y = tf.reshape(y, [-1, 1, 1, 10]) |
| 53 | l = tf.concat([l, tf.tile(y, [1, 7, 7, 1])], 3) |
| 54 | l = Conv2DTranspose('deconv1', l, 64 * 2, 5, 2, activation=BNReLU) |
| 55 | |
| 56 | l = tf.concat([l, tf.tile(y, [1, 14, 14, 1])], 3) |
| 57 | l = Conv2DTranspose('deconv2', l, 1, 5, 2, activation=tf.identity) |
| 58 | l = tf.nn.tanh(l, name='gen') |
| 59 | return l |
| 60 | |
| 61 | @auto_reuse_variable_scope |
| 62 | def discriminator(self, imgs, y): |
no test coverage detected