add toy LSTM model

mlair/model_modules/model_class.py

@@ -477,3 +477,34 @@ class MyPaperModel(AbstractModelClass):
         self.optimizer = keras.optimizers.SGD(lr=self.initial_lr, momentum=0.9)
         self.compile_options = {"loss": [keras.losses.mean_squared_error, keras.losses.mean_squared_error],
                                 "metrics": ['mse', 'mae']}
+
+
+class MyLSTMModel(AbstractModelClass):
+
+    def __init__(self, input_shape: list, output_shape: list):
+
+        super().__init__(input_shape[0], output_shape[0])
+
+        # settings
+        self.dropout_rate = 0.2
+
+        # apply to model
+        self.set_model()
+        self.set_compile_options()
+        self.set_custom_objects(loss=self.compile_options['loss'])
+
+    def set_model(self):
+        x_input = keras.layers.Input(shape=self._input_shape)
+        x_in = keras.layers.LSTM(32, return_sequences=True, name="First_LSTM")(x_input)
+        x_in = keras.layers.LSTM(64, name="Second_LSTM")(x_in)
+        out_main = keras.layers.Dense(self._output_shape, name='Output_Dense')(x_in)
+        self.model = keras.Model(inputs=x_input, outputs=[out_main])
+
+    def set_compile_options(self):
+        self.initial_lr = 1e-4
+        self.optimizer = keras.optimizers.SGD(lr=self.initial_lr, momentum=0.9)
+        self.lr_decay = mlair.model_modules.keras_extensions.LearningRateDecay(base_lr=self.initial_lr,
+                                                                               drop=.94,
+                                                                               epochs_drop=10)
+        self.loss = keras.losses.mean_squared_error
+        self.compile_options = {"metrics": ["mse", "mae"]}