Initial commit

train/decoder_train.py

@@ -0,0 +1,42 @@
+#-*- coding: utf-8 -*-
+
+from keras import Model
+import typing
+from typing import List
+
+def load_decoder(input_shape, n_classes):
+    """
+    """
+
+    model = DecoderModel(input_shape, HEAD_SIZE, NUM_HEADS, FF_DIM,
+                 NUM_TRANSFORMER_BLOCKS, MLP_UNITS, n_classes,
+                 dropout=DROPOUT, mlp_dropout=MLP_DROPOUT)
+    return model
+
+def train_decoder(decoder, train, validation):
+    """
+    """
+
+    decoder = load_decoder(train_set[0].shape[1:], n_classes)
+    decoder.compile(
+        optimizer=keras.optimizers.Adam(learning_rate=4e-4),
+        loss=["mse"],
+    )
+
+def test_decoder(decoder: Model, test: List, metrics: dict):
+    """
+    """
+
+    test_eval = model.evaluate(test[1], test[0])
+    if len(metrics.keys()) == 1:
+        metrics[metrics.keys()[0]] = test_eval
+    else:
+        for i, key in enumerate(metrics.keys()):
+            metrics[key] = test_eval[i]
+
+    test_predict = model.predict(test[1])
+    return metrics, test_predict
+
+def save_decoder():
+
+# EOF