I calculated logarithm in GPU with math.log, which is one of the Supported Python features in CUDA Python. But failed.
My code:
import os,sys,time,math
import pandas as pd
import numpy as np
from numba import cuda, float32
import os
bpg = (3,1)
tpb = (2,3)
@cuda.jit
def calcu_T(D,T):
bx = cuda.blockIdx.x
tx = cuda.threadIdx.x
ty = cuda.threadIdx.y
c_num = D.shape[1]
ml = math.log(D[tx,ty],2)
D = np.array([[ 0.42487645,0.41607881,0.42027071,0.43751907,0.43512794,0.43656972,0.43940639,0.43864551,0.43447691,0.43120232],
[2.989578,2.834707,2.942902,3.294948,2.868170,2.975180,3.066900,2.712719,2.835360,2.607334]], dtype=np.float32)
T = np.empty([1,1])
dD = cuda.to_device(D)
dT = cuda.device_array_like(T)
calcu_T[bpg, tpb](dD,dT)
The error report:
Traceback (most recent call last):
File "G:\myworkspace\python3.5\forte\forte170327\test7.py", line 104, in <module>
calcu_T[bpg, tpb](dD,dT)
File "D:\python3.5.3\lib\site-packages\numba\cuda\compiler.py", line 701, in __call__
kernel = self.specialize(*args)
File "D:\python3.5.3\lib\site-packages\numba\cuda\compiler.py", line 712, in specialize
kernel = self.compile(argtypes)
File "D:\python3.5.3\lib\site-packages\numba\cuda\compiler.py", line 727, in compile
**self.targetoptions)
File "D:\python3.5.3\lib\site-packages\numba\cuda\compiler.py", line 36, in core
return fn(*args, **kwargs)
File "D:\python3.5.3\lib\site-packages\numba\cuda\compiler.py", line 75, in compile_kernel
cres = compile_cuda(pyfunc, types.void, args, debug=debug, inline=inline)
File "D:\python3.5.3\lib\site-packages\numba\cuda\compiler.py", line 36, in core
return fn(*args, **kwargs)
File "D:\python3.5.3\lib\site-packages\numba\cuda\compiler.py", line 64, in compile_cuda
locals={})
File "D:\python3.5.3\lib\site-packages\numba\compiler.py", line 699, in compile_extra
return pipeline.compile_extra(func)
File "D:\python3.5.3\lib\site-packages\numba\compiler.py", line 352, in compile_extra
return self._compile_bytecode()
File "D:\python3.5.3\lib\site-packages\numba\compiler.py", line 660, in _compile_bytecode
return self._compile_core()
File "D:\python3.5.3\lib\site-packages\numba\compiler.py", line 647, in _compile_core
res = pm.run(self.status)
File "D:\python3.5.3\lib\site-packages\numba\compiler.py", line 238, in run
raise patched_exception
File "D:\python3.5.3\lib\site-packages\numba\compiler.py", line 230, in run
stage()
File "D:\python3.5.3\lib\site-packages\numba\compiler.py", line 444, in stage_nopython_frontend
self.locals)
File "D:\python3.5.3\lib\site-packages\numba\compiler.py", line 800, in type_inference_stage
infer.propagate()
File "D:\python3.5.3\lib\site-packages\numba\typeinfer.py", line 767, in propagate
raise errors[0]
File "D:\python3.5.3\lib\site-packages\numba\typeinfer.py", line 128, in propagate
constraint(typeinfer)
File "D:\python3.5.3\lib\site-packages\numba\typeinfer.py", line 379, in __call__
self.resolve(typeinfer, typevars, fnty)
File "D:\python3.5.3\lib\site-packages\numba\typeinfer.py", line 401, in resolve
raise TypingError(msg, loc=self.loc)
numba.errors.TypingError: Failed at nopython (nopython frontend)
Invalid usage of Function(<built-in function log>) with parameters (float32, int64)
Known signatures:
* (int64,) -> float64
* (uint64,) -> float64
* (float32,) -> float32
* (float64,) -> float64
File "G:\myworkspace\python3.5\forte\forte170327\test7.py", line 28
[1] During: resolving callee type: Function(<built-in function log>)
[2] During: typing of call at G:\myworkspace\python3.5\forte\forte170327\test7.py (28)
It's a TypingError? How could I correct it?
I run these code with the the CUDA Simulator( here shows in detial), it has no error. Why?
The numba runtime is telling you the problem
Invalid usage of Function(<built-in function log>) with parameters (float32, int64)
Known signatures:
* (int64,) -> float64
* (uint64,) -> float64
* (float32,) -> float32
* (float64,) -> float64
i.e. the only signatures available have one argument. A base argument is not implemented. If you look here at the source you can see that math.log appears to bind directly to the CUDA log function, which only calculates the natural logarithm.
My guess is that this is a documentation error in Numba. If it bothers you, I suggest you report it.