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当我尝试运行此代码:是什么导致Numba的AttributeError:'NoneType'对象没有属性'pysig'?
from numba import njit, int64
from numba.types import List
@njit(int64(List(int64, True)))
def f(a):
a[0] = 0
return a[0]
@njit(List(int64)())
def g(): return [f([0])]
我得到以下。为什么是这样?我如何使它正确地找出类型?
Traceback (most recent call last):
File "Temp.py", line 9, in <module>
@njit(List(int64)())
File "numba\decorators.py", line 172, in wrapper
disp.compile(sig)
File "numba\dispatcher.py", line 350, in compile
flags=flags, locals=self.locals)
File "numba\compiler.py", line 644, in compile_extra
return pipeline.compile_extra(func)
File "numba\compiler.py", line 361, in compile_extra
return self.compile_bytecode(bc, func_attr=self.func_attr)
File "numba\compiler.py", line 370, in compile_bytecode
return self._compile_bytecode()
File "numba\compiler.py", line 631, in _compile_bytecode
return pm.run(self.status)
File "numba\compiler.py", line 251, in run
raise patched_exception
numba.errors.TypingError: Caused By:
Traceback (most recent call last):
File "numba\compiler.py", line 243, in run
res = stage()
File "numba\compiler.py", line 458, in stage_nopython_frontend
self.locals)
File "numba\compiler.py", line 759, in type_inference_stage
infer.propagate()
File "numba\typeinfer.py", line 510, in propagate
raise errors[0]
TypingError: Internal error at <numba.typeinfer.CallConstraint object at 0x00000000071C82E8>:
--%<-----------------------------------------------------------------
Traceback (most recent call last):
File "numba\typeinfer.py", line 111, in propagate
constraint(typeinfer)
File "numba\typeinfer.py", line 270, in __call__
self.resolve(typeinfer, typevars, fnty)
File "numba\typeinfer.py", line 297, in resolve
sig = context.resolve_function_type(fnty, pos_args, kw_args)
File "numba\typing\context.py", line 113, in resolve_function_type
return func.get_call_type(self, args, kws)
File "numba\types.py", line 334, in get_call_type
sig.pysig = self.pysig
AttributeError: 'NoneType' object has no attribute 'pysig'
--%<-----------------------------------------------------------------
File "Temp.py", line 10
事实证明,我看到的核心问题是我的Numba版本的问题(但你提到的问题也存在)。谢谢! (PS,让Numba弄清楚这些类型的一个问题是它会延迟到调用之前,这会增加额外的延迟,我不喜欢,尤其是在分析时)。 – Mehrdad