Learning module Args: input_layer: input to the leaning module Returns: learning_layer3: output of learning module
(input_layer)
| 226 | return permute_2 |
| 227 | |
| 228 | def learning_module(input_layer): |
| 229 | """ |
| 230 | Learning module |
| 231 | Args: |
| 232 | input_layer: input to the leaning module |
| 233 | Returns: |
| 234 | learning_layer3: output of learning module |
| 235 | """ |
| 236 | learning_layer1 = conv_block(input_layer, |
| 237 | conv_type="conv", |
| 238 | filters=16, |
| 239 | kernel_size=(3, 3), |
| 240 | strides=(2, 2), |
| 241 | padding="same", |
| 242 | relu=True) |
| 243 | learning_layer2 = conv_block(learning_layer1, |
| 244 | conv_type="ds", |
| 245 | filters=32, |
| 246 | kernel_size=(3, 3), |
| 247 | strides=(2, 2), |
| 248 | padding="same", |
| 249 | relu=True) |
| 250 | learning_layer3 = conv_block(learning_layer2, |
| 251 | conv_type="ds", |
| 252 | filters=48, |
| 253 | kernel_size=(3, 3), |
| 254 | strides=(2, 2), |
| 255 | padding="same", |
| 256 | relu=True) |
| 257 | |
| 258 | return learning_layer1, learning_layer2, learning_layer3 |
| 259 | |
| 260 | def feature_extractor(input_layer): |
| 261 | """ |
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