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|
module MindTest (suite) where
import Test.Tasty
import Test.Tasty.HUnit
import Mind
suite :: TestTree
suite = testGroup "mind tests" $
[ neuronIndexTests
, networkTests
]
neuronIndexTests :: TestTree
neuronIndexTests = testGroup "neuron index tests" $
[ testCase "get input index" $ getNeuronIndex (Input 4) @?= 4
, testCase "get internal index" $ getNeuronIndex (Internal 12) @?= 12
, testCase "get output index" $ getNeuronIndex (Output 0) @?= 0
]
networkTests :: TestTree
networkTests = testGroup "network tests" $
[ testCase "create empty network" $
(createEmptyNetwork 3 2 1) @?= Network 3 [[], []] [[]]
-- neuron connections
, testCase "output network connection" $
let network = Network 3 [[], []] [[]]
in (connectNeurons network (Input 0) (Output 0) (negate 1.0))
@?= (Just $ Network 3 [[], []] [[Edge (Input 0, (negate 1.0))]])
, testCase "internal network connection" $
let network = Network 3 [[], []] [[]]
in (connectNeurons network (Internal 0) (Internal 1) (negate 1.0))
@?= (Just $ Network 3 [[], [Edge (Internal 0, negate 1.0)]] [[]])
, testCase "internal self-connection" $
let network = Network 3 [[], []] [[]]
in (connectNeurons network (Internal 0) (Internal 0) (negate 1.0))
@?= (Just $ Network 3 [[Edge (Internal 0, negate 1.0)], []] [[]])
, testCase "internal source out of range" $
let network = Network 3 [[], []] [[]]
in (connectNeurons network (Internal 5) (Internal 0) (negate 1.0))
@?= Nothing
, testCase "internal sink out of range" $
let network = Network 3 [[], []] [[]]
in (connectNeurons network (Internal 1) (Internal (negate 1)) (negate 1.0))
@?= Nothing
, testCase "input source out of range" $
let network = Network 3 [[], []] [[]]
in (connectNeurons network (Input (negate 1)) (Internal 0) (negate 1.0))
@?= Nothing
, testCase "input sink" $
let network = Network 3 [[], []] [[]]
in (connectNeurons network (Input 0) (Input 0) (negate 1.0))
@?= Nothing
, testCase "output source" $
let network = Network 3 [[], []] [[]]
in (connectNeurons network (Output 0) (Output 0) (negate 1.0))
@?= Nothing
, testCase "output sink out of range" $
let network = Network 3 [[], []] [[]]
in (connectNeurons network (Input 0) (Output 1) (negate 1.0))
@?= Nothing
-- network computations
, testCase "single input, single output" $
let
net = Network 1 [] [[Edge (Input 0, 2.0)]]
Just (output, state) = compute net [negate 0.5] []
in (output, state) @?=
( [tanh (2.0 * (negate 0.5))]
, []
)
, testCase "multiple inputs, single output" $
let
net = Network 4 [] [
[ Edge (Input 0, negate 1.0)
, Edge (Input 1, negate 2.0)
, Edge (Input 2, 1.0)
, Edge (Input 3, 2.0)
]]
Just (output, state) = compute net [1, 2, 3, 5] []
in (output, state) @?=
(
[tanh
( (1 * (negate 1.0))
+ (2 * (negate 2.0))
+ (3 * 1.0)
+ (5 * 2.0)
)
]
, []
)
, testCase "multiple inputs, multiple outputs" $
let
net = Network 4 []
[ [ Edge (Input 0, negate 1.0)
, Edge (Input 1, 1.0)
]
, [ Edge (Input 2, negate 1.0)
, Edge (Input 3, 1.0)
]
]
Just (output, state) = compute net [1, 2, 3, 5] []
in (output, state) @?=
(
[ tanh (2 - 1)
, tanh (5 - 3)
]
, []
)
, testCase "hidden neurons" $
let
net = Network 4
-- hidden neurons
[ [ Edge (Input 0, negate 1.0)
, Edge (Input 1, 1.0)
]
, [ Edge (Input 2, negate 1.0)
, Edge (Input 3, 1.0)
]
]
-- output neurons
[ [ Edge (Internal 0, negate 1.0)
, Edge (Internal 1, 1.0)
]
]
Just (output, state) = compute net [1, 2, 3, 5] [0, 0]
in (output, state) @?=
(
[ tanh ( (tanh (5-3)) - (tanh (2-1)) ) ]
, [ tanh (2-1)
, tanh (5-3)
]
)
, testCase "computing with self-connection" $
let
net = Network 0
-- hidden neurons
[ [ Edge (Internal 0, negate 0.5) ] ]
-- output neurons
[ [ Edge (Internal 0, 2) ] ]
Just result = compute net [] [1.0]
in result @?=
( [ tanh $ 2 * (tanh (negate 0.5)) ]
, [ tanh (negate 0.5) ]
)
]
|
