def test_softmax_activation():
# Simple case
lay = SoftmaxLayer(1, 1)
input_arr = np.array([[7]])
expected_arr = np.array([[1]])
actual_arr = lay.activation(input_arr)
np.testing.assert_array_equal(expected_arr, actual_arr)
# Simple case with batches
lay = SoftmaxLayer(1, 1)
input_arr = np.array([[2], [7]])
expected_arr = np.array([[1], [1]])
actual_arr = lay.activation(input_arr)
np.testing.assert_array_equal(expected_arr, actual_arr)
# Multiple inputs
lay = SoftmaxLayer(4, 4)
input_arr = np.array([[1, 2, 3, 4]])
exp_sum = np.exp(1) + np.exp(2) + np.exp(3) + np.exp(4)
expected_arr = np.exp(np.array([[1, 2, 3, 4]])) / exp_sum
actual_arr = lay.activation(input_arr)
# round down to nearest 10 decimal places
# because floating point sucks
expected_arr = np.round(expected_arr, 10)
actual_arr = np.round(actual_arr, 10)
np.testing.assert_array_equal(expected_arr, actual_arr)
# Multiple inputs
lay = SoftmaxLayer(4, 4)
input_arr = np.array([[1, 2, 3, 4], [5, 6, 7, 8]])
exp_sum = np.exp(1) + np.exp(2) + np.exp(3) + np.exp(4)
expected_arr1 = np.exp(np.array([1, 2, 3, 4])) / exp_sum
exp_sum = np.exp(5) + np.exp(6) + np.exp(7) + np.exp(8)
expected_arr2 = np.exp(np.array([5, 6, 7, 8])) / exp_sum
expected_arr = np.array([expected_arr1, expected_arr2])
actual_arr = lay.activation(input_arr)
# round down to nearest 10 decimal places
# because floating point sucks
expected_arr = np.round(expected_arr, 10)
actual_arr = np.round(actual_arr, 10)
np.testing.assert_array_equal(expected_arr, actual_arr)
