(x, name, chan)
| 46 | |
| 47 | |
| 48 | def convnormrelu(x, name, chan): |
| 49 | x = Conv2D(name, x, chan, 3) |
| 50 | if args.norm == 'bn': |
| 51 | x = BatchNorm(name + '_bn', x) |
| 52 | elif args.norm == 'gn': |
| 53 | with tf.variable_scope(name + '_gn'): |
| 54 | x = GroupNorm(x, 32) |
| 55 | x = tf.nn.relu(x, name=name + '_relu') |
| 56 | return x |
| 57 | |
| 58 | |
| 59 | class Model(ImageNetModel): |