def build(self):
model = Sequential()
model.add(InputLayer(input_shape=INPUT_SHAPE, name="in"))
encoder = Sequential(name="encoder")
add_pool_convolution(encoder, 16, activation="prelu")
add_pool_convolution(encoder, 32, activation="prelu")
add_pool_convolution(encoder, 64, activation="prelu")
add_pool_convolution(encoder, 128, activation="prelu")
add_pool_convolution(encoder, 128, activation="prelu")
model.add(encoder)
decoder = Sequential(name="decoder")
add_upsampling_convolution(decoder, 128, activation="prelu")
add_upsampling_convolution(decoder, 128, activation="prelu")
add_upsampling_convolution(decoder, 64, activation="prelu")
add_upsampling_convolution(decoder, 32, activation="prelu")
add_upsampling_convolution(decoder, 16, activation="prelu")
add_convolution(decoder, INPUT_SHAPE[1]) # TODO: Add prelu
model.add(decoder)
model.compile(optimizer="adam", loss="mse", metrics=["acc"])
self.model = model
self.build_encoder()
self.build_decoder()
def build(self):
model = Sequential()
model.add(InputLayer(input_shape=(INPUT_COUNT, 1), name="in"))
encoder = Sequential(name="encoder")
add_pool_convolution(encoder, 32)
add_pool_convolution(encoder, 64)
add_pool_convolution(encoder, 128)
add_pool_convolution(encoder, 256)
encoder.add(Flatten())
add_fully_connected(encoder, BOTTLENECK_SIZE)
model.add(encoder)
decoder = Sequential(name="decoder")
add_fully_connected(decoder, 1024 * 256)
decoder.add(Reshape((1024, 256)))
add_upsampling_convolution(decoder, 256)
add_upsampling_convolution(decoder, 128)
add_upsampling_convolution(decoder, 64)
add_upsampling_convolution(decoder, 32)
add_convolution(decoder, 1)
model.add(decoder)
model.summary()
model.compile(optimizer="adam", loss="mse", metrics=["acc"])
self.model = model
self.build_encoder()
self.build_decoder()
def build(self):
model = Sequential()
model.add(InputLayer(input_shape=(INPUT_COUNT, 1), name="in"))
encoder = Sequential(name="encoder")
add_pool_convolution(encoder, 4) # TODO: Make prelu
add_pool_convolution(encoder, 4)
add_pool_convolution(encoder, 8)
add_pool_convolution(encoder, 16)
model.add(encoder)
decoder = Sequential(name="decoder")
add_upsampling_convolution(decoder, 16)
add_upsampling_convolution(decoder, 8)
add_upsampling_convolution(decoder, 4)
add_upsampling_convolution(decoder, 4)
add_convolution(decoder, 1)
model.add(decoder)
model.compile(optimizer="adam", loss="mse", metrics=["acc"])
self.model = model
self.build_encoder()
self.build_decoder()