我试图开始使用Numba,并安装了它,我的初次经验是使用以下代码:
from numba import autojit
@autojit
def trial(a,b):
return a+b
trial(1,1)
我收到以下错误,这告诉我autojit错误地解释了变量类型,但并没有告诉我更多。 (其他包装函数的方式也是如此,例如
@jit(...)
。)问题与this类似,但不是特定于操作的:无论函数在做什么或多么简单,都会发生此问题。 (如示例所示)。有什么建议可能是什么问题?在Ubuntu 12.04上运行,并根据Github上的说明进行安装。---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-1-653102b59b98> in <module>()
5 return a+b
6
----> 7 trial(1,1)
/usr/local/lib/python2.7/dist-packages/numba/numbawrapper.so in numba.numbawrapper._NumbaSpecializingWrapper.__call__ (numba/numbawrapper.c:3934)()
/usr/local/lib/python2.7/dist-packages/numba/wrapping/compiler.pyc in compile_from_args(self, args, kwargs)
67 def compile_from_args(self, args, kwargs):
68 signature = self.resolve_argtypes(args, kwargs)
---> 69 return self.compile(signature)
70
71 def compile(self, signature):
/usr/local/lib/python2.7/dist-packages/numba/wrapping/compiler.pyc in compile(self, signature)
86 env=self.env, func_ast=self.ast, **self.flags)
87
---> 88 compiled_function = dec(self.py_func)
89 return compiled_function
90
/usr/local/lib/python2.7/dist-packages/numba/decorators.pyc in _jit_decorator(func)
222 sig, lfunc, wrapper = compile_function(env, func, argtys,
223 restype=return_type,
--> 224 nopython=nopython, func_ast=func_ast, **kwargs)
225 return numbawrapper.create_numba_wrapper(func, wrapper, sig, lfunc)
226
/usr/local/lib/python2.7/dist-packages/numba/decorators.pyc in compile_function(env, func, argtypes, restype, func_ast, **kwds)
131 assert kwds.get('llvm_module') is None, kwds.get('llvm_module')
132
--> 133 func_env = pipeline.compile2(env, func, restype, argtypes, func_ast=func_ast, **kwds)
134
135 function_cache.register_specialization(func_env)
/usr/local/lib/python2.7/dist-packages/numba/pipeline.pyc in compile2(env, func, restype, argtypes, ctypes, compile_only, func_ast, **kwds)
142 pipeline = env.get_pipeline(kwds.get('pipeline_name', None))
143 func_ast.pipeline = pipeline
--> 144 post_ast = pipeline(func_ast, env)
145 func_signature = func_env.func_signature
146 symtab = func_env.symtab
/usr/local/lib/python2.7/dist-packages/numba/pipeline.pyc in __call__(self, ast, env)
189
190 if self.is_composed:
--> 191 ast = self.transform(ast, env)
192 else:
193 try:
/usr/local/lib/python2.7/dist-packages/numba/pipeline.pyc in transform(self, ast, env)
654 stage_tuple = (stage, utils.ast2tree(ast))
655 logger.debug(pprint.pformat(stage_tuple))
--> 656 ast = stage(ast, env)
657 return ast
658
/usr/local/lib/python2.7/dist-packages/numba/pipeline.pyc in _stage(ast, env)
639 def _stage(ast, env):
640 stage_obj = getattr(env.pipeline_stages, name)
--> 641 return _check_stage_object(stage_obj)(ast, env)
642 _stage.__name__ = name
643 stage = _stage
/usr/local/lib/python2.7/dist-packages/numba/pipeline.pyc in __call__(self, ast, env)
192 else:
193 try:
--> 194 ast = self.transform(ast, env)
195 except error.NumbaError as e:
196 func_env = env.translation.crnt
/usr/local/lib/python2.7/dist-packages/numba/pipeline.pyc in transform(self, ast, env)
551 **func_env.kwargs)
552
--> 553 func_env.translator.translate()
554 func_env.lfunc = func_env.translator.lfunc
555 return ast
/usr/local/lib/python2.7/dist-packages/numba/codegen/translate.pyc in translate(self)
327 self.lfunc = None
328 try:
--> 329 self.setup_func()
330 if isinstance(self.ast, ast.FunctionDef):
331 # Handle the doc string for the function
/usr/local/lib/python2.7/dist-packages/numba/codegen/translate.pyc in setup_func(self)
304
305 # TODO: Put current function into symbol table for recursive call
--> 306 self.setup_return()
307
308 if self.have_cfg:
/usr/local/lib/python2.7/dist-packages/numba/codegen/translate.pyc in setup_return(self)
471 llvm_ret_type = self.func_signature.return_type.to_llvm(self.context)
472 self.return_value = self.builder.alloca(llvm_ret_type,
--> 473 "return_value")
474
475 # All non-NULL object emporaries are DECREFed here
/usr/local/lib/python2.7/dist-packages/llvm/core.pyc in alloca(self, ty, size, name)
2303
2304 def alloca(self, ty, size=None, name=""):
-> 2305 sizeptr = size._ptr if size else None
2306 return _make_value(self._ptr.CreateAlloca(ty._ptr, sizeptr, name))
2307
AttributeError: 'str' object has no attribute '_ptr'
编辑:响应@JoshAdel,我在我的
LLVM_BUILD_DIR=/opt/
上使用了Github页面上“自定义Python环境”的说明。从仓库中的CHANGE_LOG中,我将安装的版本设为0.11。如果我运行您提供的示例,我将得到from numba import autojit, typeof
@autojit
def trial(a,b):
print typeof(a), typeof(b)
return a+b
trial(1,1)
到哪
File "<unknown file>", line 2
print typeof(a), typeof(b)
^
SyntaxError: invalid syntax
如果我删除
@autojit
,就可以了。在调用SyntaxError
的情况下抛出@autojit
肯定是一个线索,但是我对此很陌生,我无法说什么...另外,如果有关系,我将在IPython Notebook中运行它,以便在启动时自动加载numpy,scipy和matplotlib。
最佳答案
我认为问题可能与该提交有关:
https://github.com/llvmpy/llvmpy/commit/b9752e1e981499879823f1f371e61b037706be4b
您将看到alloca的API发生了更改(第二个参数现在是size,而不是name)。 NUMBA代码似乎正在传递名称(即'return_value')作为第二个参数。乍一看,我想您可以更改所有的numba调用以传递None。例如,这是我遇到相同错误的一行:
self.return_value = self.builder.alloca(llvm_ret_type,
"return_value")
切换到:
self.return_value = self.builder.alloca(llvm_ret_type, None,
"return_value")
这样您将获得正确的行为。