我尝试紧跟documented example之后进行以下并行化处理:
@numba.jit(nopython=True)
def foo(uIdx, grids):
return uIdx
@numba.jit(nopython=True, parallel=True)
def bar(grid, grids):
LIdxGrid = np.zeros(len(grid))
for uIdx in numba.prange(len(grid)):
LIdxGrid[uIdx] = foo(uIdx, grids)
return LIdxGrid
if __name__ == '__main__':
import numpy as np
grid = np.arange(12)
grids = (grid, grid)
bar(grid, grids)
但是它似乎不起作用。 问题似乎源于传递grids
(甚至没有在最终的foo
函数中使用它)。如果我在foo
和bar
中删除该引用,它将起作用:
bar(grid, 0)
Out[47]: array([ 0., 1., 2., 3., 4., 5., 6., 7., 8., 9., 10., 11.])
如何解决此问题?
完整的追溯是
Traceback (most recent call last):
File "/home/foo/anaconda3/envs/myenv3/lib/python3.6/site-packages/numba/errors.py", line 491, in new_error_context
yield
File "/home/foo/anaconda3/envs/myenv3/lib/python3.6/site-packages/numba/lowering.py", line 216, in lower_block
self.lower_inst(inst)
File "/home/foo/anaconda3/envs/myenv3/lib/python3.6/site-packages/numba/lowering.py", line 365, in lower_inst
func(self, inst)
File "/home/foo/anaconda3/envs/myenv3/lib/python3.6/site-packages/numba/npyufunc/parfor.py", line 119, in _lower_parfor_parallel
index_var_typ)
File "/home/foo/anaconda3/envs/myenv3/lib/python3.6/site-packages/numba/npyufunc/parfor.py", line 691, in call_parallel_gufunc
sout, {})
File "/home/foo/anaconda3/envs/myenv3/lib/python3.6/site-packages/numba/npyufunc/parallel.py", line 251, in build_gufunc_wrapper
cache=cache)
File "/home/foo/anaconda3/envs/myenv3/lib/python3.6/site-packages/numba/npyufunc/wrappers.py", line 460, in build_gufunc_wrapper
return wrapcls(py_func, cres, sin, sout, cache).build()
File "/home/foo/anaconda3/envs/myenv3/lib/python3.6/site-packages/numba/npyufunc/wrappers.py", line 411, in build
self._build_wrapper(wrapperlib, wrapper_name)
File "/home/foo/anaconda3/envs/myenv3/lib/python3.6/site-packages/numba/npyufunc/wrappers.py", line 372, in _build_wrapper
arg_steps, i, step_offset, typ, sym, sym_dim)
File "/home/foo/anaconda3/envs/myenv3/lib/python3.6/site-packages/numba/npyufunc/wrappers.py", line 614, in __init__
"argument #{1}".format(typ, i + 1))
TypeError: scalar type tuple(array(int64, 1d, C) x 2) given for non scalar argument #2
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/home/foo/anaconda3/envs/myenv3/lib/python3.6/site-packages/IPython/core/interactiveshell.py", line 2963, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File "<ipython-input-46-b6a12a1ce616>", line 3, in <module>
bar(grid, grids)
File "/home/foo/anaconda3/envs/myenv3/lib/python3.6/site-packages/numba/dispatcher.py", line 360, in _compile_for_args
raise e
File "/home/foo/anaconda3/envs/myenv3/lib/python3.6/site-packages/numba/dispatcher.py", line 311, in _compile_for_args
return self.compile(tuple(argtypes))
File "/home/foo/anaconda3/envs/myenv3/lib/python3.6/site-packages/numba/dispatcher.py", line 618, in compile
cres = self._compiler.compile(args, return_type)
File "/home/foo/anaconda3/envs/myenv3/lib/python3.6/site-packages/numba/dispatcher.py", line 83, in compile
pipeline_class=self.pipeline_class)
File "/home/foo/anaconda3/envs/myenv3/lib/python3.6/site-packages/numba/compiler.py", line 871, in compile_extra
return pipeline.compile_extra(func)
File "/home/foo/anaconda3/envs/myenv3/lib/python3.6/site-packages/numba/compiler.py", line 365, in compile_extra
return self._compile_bytecode()
File "/home/foo/anaconda3/envs/myenv3/lib/python3.6/site-packages/numba/compiler.py", line 802, in _compile_bytecode
return self._compile_core()
File "/home/foo/anaconda3/envs/myenv3/lib/python3.6/site-packages/numba/compiler.py", line 789, in _compile_core
res = pm.run(self.status)
File "/home/foo/anaconda3/envs/myenv3/lib/python3.6/site-packages/numba/compiler.py", line 251, in run
raise patched_exception
File "/home/foo/anaconda3/envs/myenv3/lib/python3.6/site-packages/numba/compiler.py", line 243, in run
stage()
File "/home/foo/anaconda3/envs/myenv3/lib/python3.6/site-packages/numba/compiler.py", line 676, in stage_nopython_backend
self._backend(lowerfn, objectmode=False)
File "/home/foo/anaconda3/envs/myenv3/lib/python3.6/site-packages/numba/compiler.py", line 626, in _backend
lowered = lowerfn()
File "/home/foo/anaconda3/envs/myenv3/lib/python3.6/site-packages/numba/compiler.py", line 613, in backend_nopython_mode
self.flags)
File "/home/foo/anaconda3/envs/myenv3/lib/python3.6/site-packages/numba/compiler.py", line 990, in native_lowering_stage
lower.lower()
File "/home/foo/anaconda3/envs/myenv3/lib/python3.6/site-packages/numba/lowering.py", line 135, in lower
self.lower_normal_function(self.fndesc)
File "/home/foo/anaconda3/envs/myenv3/lib/python3.6/site-packages/numba/lowering.py", line 176, in lower_normal_function
entry_block_tail = self.lower_function_body()
File "/home/foo/anaconda3/envs/myenv3/lib/python3.6/site-packages/numba/lowering.py", line 201, in lower_function_body
self.lower_block(block)
File "/home/foo/anaconda3/envs/myenv3/lib/python3.6/site-packages/numba/lowering.py", line 216, in lower_block
self.lower_inst(inst)
File "/home/foo/anaconda3/envs/myenv3/lib/python3.6/contextlib.py", line 99, in __exit__
self.gen.throw(type, value, traceback)
File "/home/foo/anaconda3/envs/myenv3/lib/python3.6/site-packages/numba/errors.py", line 499, in new_error_context
six.reraise(type(newerr), newerr, tb)
File "/home/foo/anaconda3/envs/myenv3/lib/python3.6/site-packages/numba/six.py", line 659, in reraise
raise value
numba.errors.LoweringError: Failed at nopython (nopython mode backend)
scalar type tuple(array(int64, 1d, C) x 2) given for non scalar argument #2
File "<ipython-input-44-ec97cbf0b87b>", line 9:
def bar(grid, grids):
<source elided>
LIdxGrid = np.zeros(len(grid))
^
[1] During: lowering "id=7[LoopNest(index_variable = parfor_index.317, range = (0, grid_size0.315, 1))]{51: <ir.Block at <ipython-input-44-ec97cbf0b87b> (9)>}Var(parfor_index.317, <ipython-input-44-ec97cbf0b87b> (9))" at <ipython-input-44-ec97cbf0b87b> (9)
-------------------------------------------------------------------------------
This should not have happened, a problem has occurred in Numba's internals.
答案 0 :(得分:1)
对引用计数项(例如np.ndarray
)的支持是非常新的(自numba 0.39起),我不确定是否可以使用tuple
s ref。计数项目已经有效。参考的Afaik tuple
s。尚不支持计数的项目。因此,为确保您的代码有效,您必须将tuple
替换为list
:
if __name__ == '__main__':
import numpy as np
grid = np.arange(12)
grids = [grid, grid]
bar(grid, grids)
并确保您安装了numba版本0.39!否则,该方法也将无法正常运行。
当然,列表不是元组,因此这只是一种解决方法。但是,只要引用元组,没有其他方法可以解决此问题。不完全支持计数的项目。