def test_upsample(self):
"""
Test the conversion of 2D convolutional layer + upsample
"""
from keras.layers import Convolution2D, UpSampling2D
# Create a simple Keras model
model = Sequential()
model.add(Convolution2D(input_shape=(64, 64, 3), nb_filter=32,
nb_row=5, nb_col=5))
model.add(UpSampling2D(size = (2, 2)))
input_names = ['input']
output_names = ['output']
spec = keras.convert(model, input_names, output_names).get_spec()
self.assertIsNotNone(spec)
# Test the model class
self.assertIsNotNone(spec.description)
self.assertTrue(spec.HasField('neuralNetwork'))
# Test the inputs and outputs
self.assertEquals(len(spec.description.input), len(input_names))
self.assertItemsEqual(input_names,
map(lambda x: x.name, spec.description.input))
self.assertEquals(len(spec.description.output), len(output_names))
self.assertItemsEqual(output_names,
map(lambda x: x.name, spec.description.output))
# Test the layer parameters.
layers = spec.neuralNetwork.layers
layer_0 = layers[0]
self.assertIsNotNone(layer_0.convolution)
layer_1 = layers[1]
self.assertIsNotNone(layer_1.upsample)
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