Inception block from GoogleNet
(input_tensor)
| 151 | |
| 152 | |
| 153 | def inception_block(input_tensor): |
| 154 | """ |
| 155 | Inception block from GoogleNet |
| 156 | """ |
| 157 | b1x1 = tf.keras.layers.Conv2D(filters=12, kernel_size=(1, 1), padding="same")( |
| 158 | input_tensor |
| 159 | ) |
| 160 | b1x1 = relu_bn(b1x1) |
| 161 | |
| 162 | b5x5 = tf.keras.layers.Conv2D(filters=12, kernel_size=(1, 1), padding="same")( |
| 163 | input_tensor |
| 164 | ) |
| 165 | b5x5 = tf.keras.layers.Conv2D(filters=24, kernel_size=(5, 5), padding="same")(b5x5) |
| 166 | b5x5 = relu_bn(b5x5) |
| 167 | |
| 168 | b3x3 = tf.keras.layers.Conv2D(filters=12, kernel_size=(1, 1), padding="same")( |
| 169 | input_tensor |
| 170 | ) |
| 171 | b3x3 = tf.keras.layers.Conv2D(filters=20, kernel_size=(3, 3), padding="same")(b3x3) |
| 172 | b3x3 = tf.keras.layers.Conv2D(filters=24, kernel_size=(3, 3), padding="same")(b3x3) |
| 173 | b3x3 = relu_bn(b3x3) |
| 174 | |
| 175 | out = tf.keras.layers.Concatenate()([b1x1, b5x5]) |
| 176 | return out |
| 177 | |
| 178 | |
| 179 | def identity_block_bn(input_tensor): |
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