def test_createNetworkCalled_ReturnsNetworkWithProperBetaDimensions(self):
expectedDimensions = [3, 4, 5]
(w, a, b) = neuralnetwork.create_network(expectedDimensions[0],
expectedDimensions[1],
expectedDimensions[2])
for l in range(1, len(expectedDimensions)):
self.assertEqual(len(b[l]), expectedDimensions[l])
def test_createNetworkCalled_ReturnsNetworkWithProperWeightsHeightDimensions(
self):
expectedDimensions = [3, 4, 5]
(w, a, b) = neuralnetwork.create_network(expectedDimensions[0],
expectedDimensions[1],
expectedDimensions[2])
# Assert
# We don't care about the first layer of weights because they are not applied
for l in range(1, len(expectedDimensions)):
expectedHeight = expectedDimensions[l]
self.assertEqual(len(w[l]), expectedHeight)
def test_createNetworkCalled_ReturnsTupleWithCorrectDimensions(self):
n = neuralnetwork.create_network(1)
self.assertEqual(len(n), 3)