python - 使用 jit nopython 了解 Numba TypingError

Question

我在使用 @jit(nopython=True) 解决(可能是基本的)Numba 错误时遇到了问题。它归结为下面的最小示例，它会产生一个 TypingError(下面是完整的日志)。如果相关，我使用的是 Python 3.6.10 和 Numba v0.49.0。

错误发生在创建 numpy 数组的 d 行(如果我删除 d 并返回 c，它工作正常)。我该如何解决这个问题？

from numba import jit
import numpy as np

n = 5
foo = np.random.rand(n,n)

@jit(nopython=True)
def bar(x):
    a = np.array([0,3,2])
    b = np.array([1,2,3])
    c = [x[i,j] for i,j in zip(a,b)]
    # print(c) # Un-commenting this line solves the issue‽ (per @Ethan's comment)
    d = np.array(c)
    return d

baz = bar(foo)

完整错误如下:

---------------------------------------------------------------------------
TypingError                               Traceback (most recent call last)
<ipython-input-13-950d2be33d72> in <module>
     14     return d
     15 
---> 16 baz = bar(foo)
     17 print(baz)

~/miniconda3/envs/py3k/lib/python3.6/site-packages/numba/core/dispatcher.py in _compile_for_args(self, *args, **kws)
    399                 e.patch_message(msg)
    400 
--> 401             error_rewrite(e, 'typing')
    402         except errors.UnsupportedError as e:
    403             # Something unsupported is present in the user code, add help info

~/miniconda3/envs/py3k/lib/python3.6/site-packages/numba/core/dispatcher.py in error_rewrite(e, issue_type)
    342                 raise e
    343             else:
--> 344                 reraise(type(e), e, None)
    345 
    346         argtypes = []

~/miniconda3/envs/py3k/lib/python3.6/site-packages/numba/core/utils.py in reraise(tp, value, tb)
     77         value = tp()
     78     if value.__traceback__ is not tb:
---> 79         raise value.with_traceback(tb)
     80     raise value
     81 

TypingError: Failed in nopython mode pipeline (step: nopython frontend)
Invalid use of Function(<intrinsic range_iter_len>) with argument(s) of type(s): (zip(iter(array(int64, 1d, C)), iter(array(int64, 1d, C))))
 * parameterized
In definition 0:
    All templates rejected with literals.
In definition 1:
    All templates rejected without literals.
This error is usually caused by passing an argument of a type that is unsupported by the named function.
[1] During: resolving callee type: Function(<intrinsic range_iter_len>)
[2] During: typing of call at <ipython-input-13-950d2be33d72> (9)


File "<ipython-input-13-950d2be33d72>", line 9:
def bar(x):
    a = np.array([0,3,2])
    ^

更新:使用以下函数以类似的方式失败(虽然 print(c) 技巧在这种情况下没有帮助):

@jit(nopython=True)
def bar(x):
    a = [0,3,2]
    b = [1,2,3]
    c = x[a, b]
    d = np.array(c)
    return d

Answer 1

函数第一个版本的问题，以及添加print(c)的事实解决它，对我来说是个谜。 Numba 应该实现 zip (显然，在这种情况下，当 print(c) 行以某种方式触发时，它可以)，所以这看起来像是一个错误。

函数的第二个版本的问题不那么神秘了。根据current Numba documentation :

Arrays support normal iteration. Full basic indexing and slicing is supported. A subset of advanced indexing is also supported: only one advanced index is allowed, and it has to be a one-dimensional array (it can be combined with an arbitrary number of basic indices as well).

由于您尝试使用两个高级索引，a和 b , 在 c = x[a, b] 行中，Numba 不支持该代码。确实，这就是罗嗦的错误信息 Invalid use of Function(<built-in function getitem>) with argument(s) of type(s): (array(float64, 2d, C), tuple(array(int64, 1d, C) x 2))是说。

如果我们写 c=x[a,2]相反，代码将起作用，这与 Numba 允许使用一个高级索引的 promise 一致。

一般来说，我发现使用 Numba 最安全的方法是以循环方式编写，而不使用 NumPy 的更高级功能。这有点不幸——因为这几乎就好像我们需要用 C 的方言而不是 Python 来编写——但从好的方面来说，它仍然比实际编写 C 方便得多。

在这种情况下，以下代码运行良好:

@jit(nopython=True)
def bar(x):
    a = np.array([0,3,2])
    b = np.array([1,2,3])
    c = np.empty(len(a))
    for i in range(len(a)):
        c[i] = x[a[i], b[i]]
    return c