module 'numba.np' has no attribute 'sort'
时间: 2023-10-06 09:13:33 浏览: 61
This error message indicates that the 'sort' function is not available in the 'numba.np' module. It is possible that you are using an older version of Numba or NumPy that does not include this function. To resolve this issue, you can try updating to the latest version of Numba and NumPy. Alternatively, you can use the 'sort' function from the NumPy module directly instead of through the 'numba.np' module.
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AttributeError: module 'numba.cuda' has no attribute 'filter'
非常抱歉,我之前给出的代码存在错误。Numba库中没有名为`filter`的函数来应用滤波器。为了在GPU上应用滤波器,我们可以使用CuPy库的`cupyx.scipy.signal.lfilter`函数。
请尝试使用以下修改后的代码:
```python
import numpy as np
import cupy as cp
from cupyx.scipy import signal
class Channelizer(object):
"""
Channelizer object.
\param filter_coeffs: Filter coefficient array.
"""
_channel_num: int
_filter_coeffs: np.ndarray
def __init__(
self,
filter_coeffs: np.ndarray,
channel_num: int = 8):
assert isinstance(channel_num, int)
self._filter_coeffs = np.reshape(filter_coeffs, (channel_num, -1), order='F')
self._channel_num = channel_num
@RunTime # 计算代码运行时间
def dispatch(
self,
data: np.ndarray
) -> np.ndarray:
# Make the data length an integer multiple of the number of channels.
disp_len = int(np.ceil(data.size / self._channel_num))
patch_size = int(disp_len * self._channel_num - data.size)
patch_data = np.concatenate((data, np.zeros(patch_size)))
reshape_data = np.reshape(patch_data, (self._channel_num, -1), order='F')
polyphase_data = cp.flipud(cp.asarray(reshape_data))
nv = cp.arange(disp_len)
prefilt_data = polyphase_data * ((-1) ** nv)
# Polyphase filter bank
filt_data = cp.zeros(prefilt_data.shape, dtype=complex)
for k in range(self._channel_num):
filt_data[k] = signal.lfilter(self._filter_coeffs[k], [1.0], prefilt_data[k])
postfilt_data = cp.zeros(prefilt_data.shape, dtype=complex)
for k in range(self._channel_num):
postfilt_data[k] = filt_data[k] * ((-1) ** k) * cp.exp(-1j * np.pi * k / self._channel_num)
dispatch_data = cp.fft.fft(postfilt_data, axis=0)
return cp.asnumpy(dispatch_data)
```
在上述代码中,我们使用`cupyx.scipy.signal.lfilter`来应用滤波器,该函数可以在GPU上运行。我们还更新了导入语句,以确保正确导入相关函数。
请注意,这只是一个修改建议,并不能保证一定能解决问题。如果问题仍然存在,请提供详细的错误信息和相关代码,以便我们能更好地帮助您。
AttributeError: module 'numba.types' has no attribute 'Macro'
当出现"AttributeError: module 'numba.types' has no attribute 'Macro'"错误时,这说明您正在使用的numba库的types模块中没有名为"Macro"的属性。这种情况可能是因为您使用的numba库版本不兼容或者该属性在该版本中被移除了。要解决这个问题,您可以尝试以下几种方法:
1. 检查numba库的版本:首先确保您使用的是最新版本的numba库。您可以使用以下命令升级numba库:
```
pip install --upgrade numba
```
如果您仍然遇到同样的错误,请尝试降级到较旧的numba版本,并查看是否能够解决问题。
2. 检查代码中的导入语句:如果您在代码中使用了“import numba.types”,请确保该模块中的属性名称与您使用的属性名称匹配。您可以查看numba库的文档或示例代码来确认正确的属性名称。
3. 检查依赖项:请确保您的代码所依赖的其他库或模块已正确安装,并且版本与numba库兼容。有时,不兼容的库或模块可能会导致属性错误。
4. 查找替代方案:如果上述方法仍无法解决问题,您可以考虑在代码中寻找替代方案,或者尝试使用其他库来代替numba。
请注意,具体的解决方法可能会因您的代码和环境而异。建议您仔细检查代码中的导入语句和依赖项,并根据具体情况采取相应的措施来解决该错误。<span class="em">1</span><span class="em">2</span><span class="em">3</span>
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