Esempio n. 1
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def test_1D_convolution_without_reduction_dim():
    c = Convolution1D(3, init=np.array([4, 2, 1]), pad=True, reduction_rank=0, bias=False)
    c.update_signature(5)
    data = [np.array([[2, 6, 4, 8, 6]])]   # like a audio sequence, in a static dimension
    out = c(data)
    exp = [[10, 24, 40, 38, 44]]
    np.testing.assert_array_equal(out, exp, err_msg='Error in 1D convolution without reduction dimension')

    # Failing call
    with pytest.raises(ValueError):
        Convolution1D((2,3))
Esempio n. 2
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def test_layers_convolution_1d():
    inC, inW = 1, 3
    y = C.input_variable((inC, inW))

    dat = np.ones([1, inC, inW], dtype = np.float32)

    model = Convolution1D((3, ),
                          num_filters=1,
                          activation=None,
                          pad=False,
                          strides=1, name='foo')
    # shape should be
    model_shape = model(y).foo.shape
    np.testing.assert_array_equal(model_shape, (1, 1), \
        "Error in convolution1D with stride = 1 and padding")

    res = model(y).eval({y: dat})

    expected_res = np.sum(model.foo.W.value)

    np.testing.assert_array_almost_equal(res[0][0][0], expected_res, decimal=5, \
        err_msg="Error in convolution1D computation with stride = 1 and zeropad = True")