无法使用带有 *args 参数的函数使用 jit 编译函数
Cannot compile function with jit with function that takes *args parameters
我正在尝试编译一个接受 numpy 数组和元组的函数
使用 numba 的 *arg 形式的参数。
import numba as nb
import numpy as np
@nb.njit(cache=True)
def myfunc(t, *p):
val = 0
for j in range(0, len(p), 2):
val += p[j]*np.exp(-p[j+1]*t)
return val
T = np.arange(12)
pars = (1.0, 2.0, 3.0, 4.0)
mfunc = myfunc(T, *pars)
但是我得到了这个结果
In [1]: run numba_test.py
---------------------------------------------------------------------------
TypingError Traceback (most recent call last)
~/Programs/my-python/numba_test.py in <module>
12
13 T = np.arange(12)
---> 14 mfunc = myfunc(T, 1.0, 2.0, 3.0, 4.0)
...
...
TypingError: Failed in nopython mode pipeline (step: nopython frontend)
Invalid use of Function(<built-in function iadd>) with argument(s) of type(s): (Literal[int](0), array(float64, 1d, C))
Known signatures:
* (int64, int64) -> int64
* (int64, uint64) -> int64
* (uint64, int64) -> int64
* (uint64, uint64) -> uint64
* (float32, float32) -> float32
* (float64, float64) -> float64
* (complex64, complex64) -> complex64
* (complex128, complex128) -> complex128
* parameterized
In definition 0:
All templates rejected with literals.
...
...
All templates rejected without literals.
This error is usually caused by passing an argument of a type that is unsupported by the named function.
[1] During: typing of intrinsic-call at /home/cshugert/Programs/my-python/numba_test.py (9)
File "numba_test.py", line 9:
def myfunc(t, *p):
<source elided>
for j in range(0, len(p), 2):
val += p[j]*np.exp(-p[j+1]*t)
^
Numba 确实支持使用元组，所以我认为可能有
我可以在 jit 编译器中添加一些签名。但是，我不确定
究竟放在那里。难道是numba编译器的情况
无法处理以 *args 作为参数的函数？我可以做些什么来让我的功能正常工作吗？
我们再看看错误信息
TypingError: Failed in nopython mode pipeline (step: nopython frontend)
Invalid use of Function(<built-in function iadd>) with argument(s)
of type(s): (Literal[int](0), array(float64, 1d, C))
Known signatures:
* (int64, int64) -> int64
* (int64, uint64) -> int64
* (uint64, int64) -> int64
* (uint64, uint64) -> uint64
* (float32, float32) -> float32
* (float64, float64) -> float64
* (complex64, complex64) -> complex64
* (complex128, complex128) -> complex128
* parameterized
错误是针对 <built-in function iadd>，即 +。如果您查看错误，则不是由于 *args 的传递，而是由于以下语句：
val += p[j]*np.exp(-p[j+1]*t)
基本上提到的 + 的所有兼容类型中，它不支持将 integer 添加到 array（有关更多信息，请参阅错误消息和已知签名）。
您可以解决此问题，方法是使用 np.zeros 将 val 设置为零数组（参见文档 here）。
import numba as nb
import numpy as np
@nb.njit
def myfunc(t, *p):
val = np.zeros(12) #<------------ Set it as an array of zeros
for j in range(0, len(p), 2):
val += p[j]*np.exp(-p[j+1]*t)
return val
T = np.arange(12)
pars = (1.0, 2.0, 3.0, 4.0)
mfunc_val = myfunc(T, *pars)
您可以在 this Google Colab notebook 中查看代码。
我正在尝试编译一个接受 numpy 数组和元组的函数 使用 numba 的 *arg 形式的参数。
import numba as nb
import numpy as np
@nb.njit(cache=True)
def myfunc(t, *p):
val = 0
for j in range(0, len(p), 2):
val += p[j]*np.exp(-p[j+1]*t)
return val
T = np.arange(12)
pars = (1.0, 2.0, 3.0, 4.0)
mfunc = myfunc(T, *pars)
但是我得到了这个结果
In [1]: run numba_test.py
---------------------------------------------------------------------------
TypingError Traceback (most recent call last)
~/Programs/my-python/numba_test.py in <module>
12
13 T = np.arange(12)
---> 14 mfunc = myfunc(T, 1.0, 2.0, 3.0, 4.0)
...
...
TypingError: Failed in nopython mode pipeline (step: nopython frontend)
Invalid use of Function(<built-in function iadd>) with argument(s) of type(s): (Literal[int](0), array(float64, 1d, C))
Known signatures:
* (int64, int64) -> int64
* (int64, uint64) -> int64
* (uint64, int64) -> int64
* (uint64, uint64) -> uint64
* (float32, float32) -> float32
* (float64, float64) -> float64
* (complex64, complex64) -> complex64
* (complex128, complex128) -> complex128
* parameterized
In definition 0:
All templates rejected with literals.
...
...
All templates rejected without literals.
This error is usually caused by passing an argument of a type that is unsupported by the named function.
[1] During: typing of intrinsic-call at /home/cshugert/Programs/my-python/numba_test.py (9)
File "numba_test.py", line 9:
def myfunc(t, *p):
<source elided>
for j in range(0, len(p), 2):
val += p[j]*np.exp(-p[j+1]*t)
^
Numba 确实支持使用元组，所以我认为可能有 我可以在 jit 编译器中添加一些签名。但是，我不确定 究竟放在那里。难道是numba编译器的情况 无法处理以 *args 作为参数的函数？我可以做些什么来让我的功能正常工作吗？
我们再看看错误信息
TypingError: Failed in nopython mode pipeline (step: nopython frontend)
Invalid use of Function(<built-in function iadd>) with argument(s)
of type(s): (Literal[int](0), array(float64, 1d, C))
Known signatures:
* (int64, int64) -> int64
* (int64, uint64) -> int64
* (uint64, int64) -> int64
* (uint64, uint64) -> uint64
* (float32, float32) -> float32
* (float64, float64) -> float64
* (complex64, complex64) -> complex64
* (complex128, complex128) -> complex128
* parameterized
错误是针对 <built-in function iadd>，即 +。如果您查看错误，则不是由于 *args 的传递，而是由于以下语句：
val += p[j]*np.exp(-p[j+1]*t)
基本上提到的 + 的所有兼容类型中，它不支持将 integer 添加到 array（有关更多信息，请参阅错误消息和已知签名）。
您可以解决此问题，方法是使用 np.zeros 将 val 设置为零数组（参见文档 here）。
import numba as nb
import numpy as np
@nb.njit
def myfunc(t, *p):
val = np.zeros(12) #<------------ Set it as an array of zeros
for j in range(0, len(p), 2):
val += p[j]*np.exp(-p[j+1]*t)
return val
T = np.arange(12)
pars = (1.0, 2.0, 3.0, 4.0)
mfunc_val = myfunc(T, *pars)
您可以在 this Google Colab notebook 中查看代码。