4

我正在使用 numba 来加速我的代码,没有 numba 可以正常工作。但是在使用@jit 之后,它会因以下错误而崩溃:

Traceback (most recent call last):
  File "C:\work_asaaki\code\gbc_classifier_train_7.py", line 54, in <module>
    gentlebooster.train(X_train, y_train, boosting_rounds)
  File "C:\work_asaaki\code\gentleboost_c_class_jit_v7_nolimit.py", line 298, in train
    self.g_per_round, self.g = train_function(X, y, H)  
  File "C:\Anaconda\lib\site-packages\numba\dispatcher.py", line 152, in _compile_for_args
    return self.jit(sig)
  File "C:\Anaconda\lib\site-packages\numba\dispatcher.py", line 143, in jit
    return self.compile(sig, **kws)
  File "C:\Anaconda\lib\site-packages\numba\dispatcher.py", line 250, in compile
    locals=self.locals)
  File "C:\Anaconda\lib\site-packages\numba\compiler.py", line 183, in compile_bytecode
    flags.no_compile)
  File "C:\Anaconda\lib\site-packages\numba\compiler.py", line 323, in native_lowering_stage
    lower.lower()
  File "C:\Anaconda\lib\site-packages\numba\lowering.py", line 219, in lower
    self.lower_block(block)
  File "C:\Anaconda\lib\site-packages\numba\lowering.py", line 254, in lower_block
    raise LoweringError(msg, inst.loc)
numba.lowering.LoweringError: Internal error:
NotImplementedError: ('cast', <llvm.core.Instruction object at 0x000000001801D320>, slice3_type, int64)
File "gentleboost_c_class_jit_v7_nolimit.py", line 103

第 103 行如下,在一个循环中:

weights = np.empty([n,m])
for curr_n in range(n):
    weights[curr_n,:] = 1.0/(n) # this is line 103

wheren是我的代码中已经在上面某处定义的常量。

我怎样才能消除错误?正在发生什么“降价”?我在 64 位机器上使用 Anaconda 2.0.1 和 Numba 0.13.x 和 Numpy 1.8.x。

4

1 回答 1

5

基于此: https ://gist.github.com/cc7768/bc5b8b7b9052708f0c0a ,

我想出了如何避免这个问题。我没有使用冒号:来引用任何行/列,而是将循环打开为两个循环,以显式引用数组每个维度中的索引:

weights = np.empty([n,m])
for curr_n in range(n):
    for curr_m in range (m):
        weights[curr_n,curr_m] = 1.0/(n)

在此之后我的代码中还有其他实例使用了冒号,但它们并没有进一步导致错误,不知道为什么。

于 2014-09-07T16:20:56.977 回答