def test_torch_different_beta(self):
data = torch.tensor([[1.0], [3.0], [4.5]])
expected = torch.tensor([[2.75], [2], [3.75]])
mu = MixUpBatch(inputs="x", outputs=["x", "lambda"], alpha=1.0, mode="train", shared_beta=False)
mu.build('torch')
mu.beta = MyTorchBeta()
output = mu.forward(data=[data], state={})
self.assertTrue(is_equal(output[0], expected))
def test_tf_shared_beta(self):
data = tf.constant([[1.0], [3.0], [4.5]])
expected = tf.constant([[2.75], [2], [3.75]])
mu = MixUpBatch(inputs="x", outputs=["x", "lambda"], alpha=1.0, mode="train", shared_beta=True)
mu.build('tf')
mu.beta = MyTFBeta()
output = mu.forward(data=[data], state={})
self.assertTrue(is_equal(output[0], expected))