Question

我正在将函数转换为numba（nopython模式）。在此函数中，我需要访问2D数组的某些元素，其行索引包含在列表中，并且列是固定的。在通常的python中，我这样做：

array[list,column_index]

但是在numba中编译时，出现以下错误：

TypingError: Invalid use of Function(<built-in function getitem>) with argument(s) of type(s): (array(float64, 2d, C), (reflected list(int64), int64))
 * parameterized
In definition 0:
    All templates rejected with literals.
In definition 1:
    All templates rejected without literals.
In definition 2:
    All templates rejected with literals.
In definition 3:
    All templates rejected without literals.
In definition 4:
    All templates rejected with literals.
In definition 5:
    All templates rejected without literals.
In definition 6:
    TypeError: unsupported array index type reflected list(int64) in (reflected list(int64), int64)
    raised from C:\ProgramData\Anaconda2\envs\Python 3.5\lib\site-packages\numba\typing\arraydecl.py:71
In definition 7:
    TypeError: unsupported array index type reflected list(int64) in (reflected list(int64), int64)
    raised from C:\ProgramData\Anaconda2\envs\Python 3.5\lib\site-packages\numba\typing\arraydecl.py:71
This error is usually caused by passing an argument of a type that is unsupported by the named function.

我已经尝试过将列表转换为数组，因为从https://numba.pydata.org/numba-doc/dev/reference/numpysupported.html看来是正确的方法

“还支持高级索引的一个子集：只允许一个高级索引，并且它必须是一维数组（它也可以与任意数量的基本索引结合使用”）

但编码：

array[np.array(list),column_index]

产生以下错误：

Traceback (most recent call last):

  File "<ipython-input-123-c5ca441bb6b7>", line 1, in <module>
    tmp = L.numba_montecarlo_barab(SEED,w,R,T,mpx,0.5)

  File "C:\ProgramData\Anaconda2\envs\Python 3.5\lib\site-packages\numba\dispatcher.py", line 367, in _compile_for_args
    raise e

  File "C:\ProgramData\Anaconda2\envs\Python 3.5\lib\site-packages\numba\dispatcher.py", line 324, in _compile_for_args
    return self.compile(tuple(argtypes))

  File "C:\ProgramData\Anaconda2\envs\Python 3.5\lib\site-packages\numba\compiler_lock.py", line 32, in _acquire_compile_lock
    return func(*args, **kwargs)

  File "C:\ProgramData\Anaconda2\envs\Python 3.5\lib\site-packages\numba\dispatcher.py", line 655, in compile
    cres = self._compiler.compile(args, return_type)

  File "C:\ProgramData\Anaconda2\envs\Python 3.5\lib\site-packages\numba\dispatcher.py", line 82, in compile
    pipeline_class=self.pipeline_class)

  File "C:\ProgramData\Anaconda2\envs\Python 3.5\lib\site-packages\numba\compiler.py", line 926, in compile_extra
    return pipeline.compile_extra(func)

  File "C:\ProgramData\Anaconda2\envs\Python 3.5\lib\site-packages\numba\compiler.py", line 374, in compile_extra
    return self._compile_bytecode()

  File "C:\ProgramData\Anaconda2\envs\Python 3.5\lib\site-packages\numba\compiler.py", line 857, in _compile_bytecode
    return self._compile_core()

  File "C:\ProgramData\Anaconda2\envs\Python 3.5\lib\site-packages\numba\compiler.py", line 844, in _compile_core
    res = pm.run(self.status)

  File "C:\ProgramData\Anaconda2\envs\Python 3.5\lib\site-packages\numba\compiler_lock.py", line 32, in _acquire_compile_lock
    return func(*args, **kwargs)

  File "C:\ProgramData\Anaconda2\envs\Python 3.5\lib\site-packages\numba\compiler.py", line 255, in run
    raise patched_exception

  File "C:\ProgramData\Anaconda2\envs\Python 3.5\lib\site-packages\numba\compiler.py", line 246, in run
    stage()

  File "C:\ProgramData\Anaconda2\envs\Python 3.5\lib\site-packages\numba\compiler.py", line 717, in stage_nopython_backend
    self._backend(lowerfn, objectmode=False)

  File "C:\ProgramData\Anaconda2\envs\Python 3.5\lib\site-packages\numba\compiler.py", line 666, in _backend
    lowered = lowerfn()

  File "C:\ProgramData\Anaconda2\envs\Python 3.5\lib\site-packages\numba\compiler.py", line 653, in backend_nopython_mode
    self.metadata)

  File "C:\ProgramData\Anaconda2\envs\Python 3.5\lib\site-packages\numba\compiler.py", line 1050, in native_lowering_stage
    lower.create_cpython_wrapper(flags.release_gil)

  File "C:\ProgramData\Anaconda2\envs\Python 3.5\lib\site-packages\numba\lowering.py", line 272, in create_cpython_wrapper
    release_gil=release_gil)

  File "C:\ProgramData\Anaconda2\envs\Python 3.5\lib\site-packages\numba\targets\cpu.py", line 149, in create_cpython_wrapper
    builder.build()

  File "C:\ProgramData\Anaconda2\envs\Python 3.5\lib\site-packages\numba\callwrapper.py", line 122, in build
    self.build_wrapper(api, builder, closure, args, kws)

  File "C:\ProgramData\Anaconda2\envs\Python 3.5\lib\site-packages\numba\callwrapper.py", line 155, in build_wrapper
    val = cleanup_manager.add_arg(builder.load(obj), ty)

  File "C:\ProgramData\Anaconda2\envs\Python 3.5\lib\site-packages\numba\callwrapper.py", line 58, in add_arg
    cleanup_arg()

  File "C:\ProgramData\Anaconda2\envs\Python 3.5\lib\site-packages\numba\callwrapper.py", line 41, in cleanup_arg
    self.api.reflect_native_value(ty, native.value, self.env_manager)

  File "C:\ProgramData\Anaconda2\envs\Python 3.5\lib\site-packages\numba\pythonapi.py", line 1417, in reflect_native_value
    impl(typ, val, c)

  File "C:\ProgramData\Anaconda2\envs\Python 3.5\lib\site-packages\numba\targets\boxing.py", line 740, in reflect_list
    raise TypeError(msg)

TypeError: Failed in nopython mode pipeline (step: nopython mode backend)
cannot reflect element of reflected container: reflected list(reflected list(reflected list(int64)))

也不能转换为元组，但是我知道不支持元组。

在numba nopython模式下使用高级索引的正确方法是什么？

numba中的numpy数组高级索引

0 个答案: