Python spike_latency_encode Examples

Example #1

File: test_encode.py Project: xiatiandeairen/norse

def test_spike_latency_encode_without_batch_3():
    spikes = torch.as_tensor([
        [
            [1.0, 1.0, 0.0, 1.0, 1.0],
            [0.0, 0.0, 0.0, 0.0, 1.0],
            [1.0, 0.0, 1.0, 0.0, 0.0],
            [1.0, 0.0, 1.0, 0.0, 1.0],
            [0.0, 1.0, 1.0, 0.0, 0.0],
            [1.0, 0.0, 0.0, 0.0, 1.0],
            [0.0, 0.0, 0.0, 1.0, 0.0],
        ],
        [
            [1.0, 1.0, 1.0, 1.0, 1.0],
            [1.0, 1.0, 1.0, 1.0, 1.0],
            [1.0, 1.0, 1.0, 1.0, 1.0],
            [1.0, 1.0, 1.0, 1.0, 1.0],
            [1.0, 1.0, 1.0, 1.0, 1.0],
            [1.0, 1.0, 1.0, 1.0, 1.0],
            [1.0, 1.0, 1.0, 1.0, 1.0],
        ],
    ])
    actual = spike_latency_encode(spikes)
    expected = spikes.clone()
    expected[1] = torch.as_tensor([
        [0.0, 0.0, 1.0, 0.0, 0.0],
        [1.0, 1.0, 1.0, 1.0, 0.0],
        [0.0, 1.0, 0.0, 1.0, 1.0],
        [0.0, 1.0, 0.0, 1.0, 0.0],
        [1.0, 0.0, 0.0, 1.0, 1.0],
        [0.0, 1.0, 1.0, 1.0, 0.0],
        [1.0, 1.0, 1.0, 0.0, 1.0],
    ])
    assert torch.equal(actual, expected)

Example #2

File: test_encode.py Project: xiatiandeairen/norse

def test_spike_latency_encode_with_batch():
    data = torch.as_tensor([[100, 100], [100, 100]])
    spikes = constant_current_lif_encode(data, 5)
    actual = spike_latency_encode(spikes)
    expected = torch.zeros((5, 2, 2))
    expected[0] = torch.as_tensor([[1, 1], [1, 1]])
    assert torch.equal(actual, expected)

Example #3

File: encode.py Project: george-hu-1019/norse

 def forward(self, input_spikes):
     return encode.spike_latency_encode(input_spikes)

Example #4

File: test_encode.py Project: xiatiandeairen/norse

def test_spike_latency_encode_without_batch_2():
    spikes = torch.as_tensor([[[0, 1, 1], [1, 1, 1]], [[1, 1, 1], [1, 1, 1]]])
    actual = spike_latency_encode(spikes)
    expected = torch.as_tensor([[[0, 1, 1], [1, 1, 1]], [[1, 0, 0], [0, 0,
                                                                     0]]])
    assert torch.equal(actual, expected)

Example #5

File: test_encode.py Project: xiatiandeairen/norse

def test_spike_latency_encode_without_batch():
    spikes = torch.as_tensor([[0, 1, 1, 0], [1, 1, 1, 0]])
    actual = spike_latency_encode(spikes)
    assert torch.equal(actual, torch.as_tensor([[0, 1, 1, 0], [1, 0, 0, 0]]))