Mercurial > repos > iuc > decontaminator
comparison models/model_10.py @ 0:b856d3d95413 draft default tip
planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/decontaminator commit 3f8e87001f3dfe7d005d0765aeaa930225c93b72
author | iuc |
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date | Mon, 09 Jan 2023 13:27:09 +0000 |
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-1:000000000000 | 0:b856d3d95413 |
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1 from tensorflow.keras import layers, models | |
2 | |
3 | |
4 def launch(input_layer, hidden_layers): | |
5 output = input_layer | |
6 for hidden_layer in hidden_layers: | |
7 output = hidden_layer(output) | |
8 return output | |
9 | |
10 | |
11 def model(length, kernel_size=10, filters=512, dense_ns=512): | |
12 forward_input = layers.Input(shape=(length, 4)) | |
13 reverse_input = layers.Input(shape=(length, 4)) | |
14 hidden_layers = [ | |
15 layers.Conv1D(filters=filters, kernel_size=kernel_size), | |
16 layers.LeakyReLU(alpha=0.1), | |
17 layers.GlobalMaxPooling1D(), | |
18 layers.Dropout(0.1), | |
19 ] | |
20 forward_output = launch(forward_input, hidden_layers) | |
21 reverse_output = launch(reverse_input, hidden_layers) | |
22 output = layers.Concatenate()([forward_output, reverse_output]) | |
23 output = layers.Dense(dense_ns, activation='relu')(output) | |
24 output = layers.Dropout(0.1)(output) | |
25 output = layers.Dense(2, activation='softmax')(output) | |
26 model_ = models.Model(inputs=[forward_input, reverse_input], outputs=output) | |
27 model_.compile(optimizer="adam", loss='binary_crossentropy', metrics='accuracy') | |
28 return model_ |