| 257 | return node1 |
| 258 | |
| 259 | def get_discriminator(self, x_var, c_var): |
| 260 | x_code = self.d_image_template.construct(input=x_var) # s16 * s16 * df_dim*8 |
| 261 | |
| 262 | c_code = self.d_context_template.construct(input=c_var) |
| 263 | c_code = tf.expand_dims(tf.expand_dims(c_code, 1), 1) |
| 264 | c_code = tf.tile(c_code, [1, self.s16, self.s16, 1]) # s16 * s16 * ef_dim |
| 265 | |
| 266 | x_c_code = tf.concat(3, [x_code, c_code]) |
| 267 | return self.d_discriminator_template.construct(input=x_c_code) |
| 268 | |
| 269 | # hr_d_net |
| 270 | def hr_d_encode_image(self): |