***numba.errors.TypingError:在nopython模式管道中失败（步骤：nopython前端）

我对

UMAP（…）.transform（）有问题。

。我用

trans=pickle.load（）

加载了模型

由于UMAP使用

numba

包，我在解析类型时遇到了问题。下面是显示的错误

ipdb> trans.transform(X_test.reshape(X_test.shape[0], -1))                                                                                  
*** numba.errors.TypingError: Failed in nopython mode pipeline (step: nopython frontend)
Invalid use of type(CPUDispatcher(<function rdist at 0x7f36c7ce4e18>)) with parameters (array(float32, 1d, C), array(float64, 1d, C))
Known signatures:
 * (array(float32, 1d, A), array(float32, 1d, A)) -> float32
 * parameterized
[1] During: resolving callee type: type(CPUDispatcher(<function rdist at 0x7f36c7ce4e18>))
[2] During: typing of call at /home/infinity/anaconda3/envs/HFT/lib/python3.6/site-packages/umap/umap_.py (776)


File "../../../anaconda3/envs/HFT/lib/python3.6/site-packages/umap/umap_.py", line 776:
def optimize_layout(
    <source elided>

                dist_squared = rdist(current, other)
                ^

This is not usually a problem with Numba itself but instead often caused by
the use of unsupported features or an issue in resolving types.

To see Python/NumPy features supported by the latest release of Numba visit:
http://numba.pydata.org/numba-doc/dev/reference/pysupported.html
and
http://numba.pydata.org/numba-doc/dev/reference/numpysupported.html

For more information about typing errors and how to debug them visit:
http://numba.pydata.org/numba-doc/latest/user/troubleshoot.html#my-code-doesn-t-compile

If you think your code should work with Numba, please report the error message
and traceback, along with a minimal reproducer at:
https://github.com/numba/numba/issues/new

形状是

（5839,45,41）

如何修复该类型错误

更新

我通知说问题出在

@numba.njit("f4(f4[:],f4[:])", fastmath=True)
def rdist(x, y):
    """Reduced Euclidean distance.

    Parameters
    ----------
    x: array of shape (embedding_dim,)
    y: array of shape (embedding_dim,)

    Returns
    -------
    The squared euclidean distance between x and y
    """
    result = 0.0
    for i in range(x.shape[0]):
        result += (x[i] - y[i]) ** 2

    return result

x = [-4.3200183,   0.2443985,   0.24419938]
y = [-3.7033827,   0.91038215,  4.292648  ]

test = rdist(x,y)

但是，我没有资格解决这个问题

---

如果我运行上面的代码，我会得到以下错误

TypeError:reflectedlist（float64）参数类型没有匹配的定义，reflectedlist（float64）

输入数据的真实示例是什么？您正在向函数传递一个列表，但是您声明了两个1d float32数组作为输入。除此之外，如果您的阵列较大，则可以改进算法。

array([[[-7.84867750e-05, -3.92410776e-05, -1.17713994e-04, ...,
          0.00000000e+00,  0.00000000e+00, -5.88910810e-05],
        [ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00, ...,
          3.22361913e+01,  3.36224857e+01,  0.00000000e+00],
        [-1.17741714e-04, -1.56979711e-04,  0.00000000e+00, ...,
         -3.22361913e+01, -3.36224857e+01, -2.35599012e-04],
        ...,
        [ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00, ...,
          0.00000000e+00,  0.00000000e+00,  3.92395378e-05],
        [ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00, ...,
          0.00000000e+00,  0.00000000e+00,  0.00000000e+00],
        [ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00, ...,
          0.00000000e+00,  0.00000000e+00,  0.00000000e+00]],

       [[ 0.00000000e+00,  0.00000000e+00,  7.98615775e-04, ...,
          0.00000000e+00,  0.00000000e+00, -2.66778461e-04],
        [ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00, ...,
          0.00000000e+00,  0.00000000e+00,  0.00000000e+00],
        [ 1.10377388e-03,  1.86421709e-03,  3.04066897e-04, ...,
          0.00000000e+00,  0.00000000e+00,  5.52533571e-04],
        ...,
        [ 0.00000000e+00,  1.14074947e-04,  3.80220908e-05, ...,
          0.00000000e+00,  0.00000000e+00,  0.00000000e+00],
        [-1.36996749e-03, -4.18338442e-04, -4.18322533e-04, ...,
          0.00000000e+00,  0.00000000e+00, -1.21918711e-03],
        [-3.80814562e-05, -1.10373187e-03, -3.80380000e-05, ...,
          0.00000000e+00,  0.00000000e+00, -1.90615976e-05]]])

@numba.njit("f4(f4[:],f4[:])", fastmath=True)
def rdist(x, y):
    """Reduced Euclidean distance.

    Parameters
    ----------
    x: array of shape (embedding_dim,)
    y: array of shape (embedding_dim,)

    Returns
    -------
    The squared euclidean distance between x and y
    """
    result = 0.0
    for i in range(x.shape[0]):
        result += (x[i] - y[i]) ** 2

    return result

x = [-4.3200183,   0.2443985,   0.24419938]
y = [-3.7033827,   0.91038215,  4.292648  ]

test = rdist(x,y)