단 하나의 열 또는 단 하나의 행만 있는 행렬로 작업할 때 Python의 cupy 라이브러리에 있는 amax 및 max 함수가 잘못됩니까?

问题内容

我尝试使用 cupy 进行 gpu 加速来实现用于机器学习和图像分类的 softmax 激活函数。我观察到，对于形状为 nx1 或 1xn 的数组，cupys max 函数会输出错误。然而，对于 nxa 的所有其他情况（其中 n 和 a 都是 1 以外的整数），它工作得很好。

我的代码：

def softmax_(z):
    max_z = cp.max(z, axis=0, keepdims=true)  # problematic max function
    exp_z = cp.exp(z - max_z)  # subtracting the maximum value for numerical stability
    sum_exp_z = cp.sum(exp_z, axis=0, keepdims=true)  # summing up the values
    return exp_z / sum_exp_z  # dividing them to get the softmax

array1 = cp.random.randn(3, 4)  # 3x4
array2 = cp.random.randn(5, 1)  # 5x1

print(softmax_(array1))  # no error
print(softmax_(array2))  # produces an error

我的操作系统错误，我对此缺乏经验：

oserror: [winerror 123] the filename, directory name, or volume label syntax is incorrect: 'c:\\users\\confidential\\.cupy\\jitify_cache\\tmp1pxgjv_g' -> 'c:\\users\\confidential/.cupy/jitify_cache/jitify_<unknown>_200200_12030_2_b3452ffa79e273adadd0403b6b0c05b78158b1e0.json'

数组 1 的输出

output:  [[0.17813469 0.20912114 0.19734889 0.30515635]  [0.42569072
0.47354802 0.4463671  0.20997539]  [0.39617459 0.31733085 0.356284   0.48486825]]

数组2的错误：

../../util_ptx.cuh(38): warning: util_type.cuh: [jitify] File not found 
../../util_ptx.cuh(41): warning: util_debug.cuh: [jitify] File not found
../../thread/thread_load.cuh(40): warning: ../util_ptx.cuh: [jitify] File not found
Traceback (most recent call last):
  File "c:\Users\confidential\Desktop\Projekte\Neural_network2\test.py", line 14, in <module>        
    print(softmax_(array2))
          ^^^^^^^^^^^^^^^^
  File "c:\Users\confidential\Desktop\Projekte\Neural_network2\test.py", line 4, in softmax_
    `max_Z = cp.max(Z, axis=0, keepdims=True)`
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\confidential\PycharmProjects\nunpy\venv\Lib\site-packages\cupy\_statistics\order.py", line 81, in amax
    return a.max(axis=axis, out=out, keepdims=keepdims)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "cupy\_core\core.pyx", line 990, in cupy._core.core._ndarray_base.max
  File "cupy\_core\core.pyx", line 998, in cupy._core.core._ndarray_base.max
  File "cupy\_core\_routines_statistics.pyx", line 43, in cupy._core._routines_statistics._ndarray_max
  File "cupy\_core\_reduction.pyx", line 618, in cupy._core._reduction._SimpleReductionKernel.__call__
  File "cupy\_core\_reduction.pyx", line 370, in cupy._core._reduction._AbstractReductionKernel._call
  File "cupy\_core\_cub_reduction.pyx", line 689, in cupy._core._cub_reduction._try_to_call_cub_reduction
  File "cupy\_core\_cub_reduction.pyx", line 540, in cupy._core._cub_reduction._launch_cub    
  File "cupy\_util.pyx", line 64, in cupy._util.memoize.decorator.ret
  File "cupy\_core\_cub_reduction.pyx", line 240, in cupy._core._cub_reduction._SimpleCubReductionKernel_get_cached_function
  File "cupy\_core\_cub_reduction.pyx", line 223, in cupy._core._cub_reduction._create_cub_reduction_function
  File "cupy\_core\core.pyx", line 2254, in cupy._core.core.compile_with_cache
  File "C:\Users\confidential\PycharmProjects\nunpy\venv\Lib\site-packages\cupy\cuda\compiler.py", line 484, in _compile_module_with_cache
    return _compile_with_cache_cuda(
           ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\confidential\PycharmProjects\nunpy\venv\Lib\site-packages\cupy\cuda\compiler.py", line 562, in _compile_with_cache_cuda
    ptx, mapping = compile_using_nvrtc(
                   ^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\confidential\PycharmProjects\nunpy\venv\Lib\site-packages\cupy\cuda\compiler.py", line 319, in compile_using_nvrtc
    return _compile(source, options, cu_path,
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\confidential\PycharmProjects\nunpy\venv\Lib\site-packages\cupy\cuda\compiler.py", line 284, in _compile
    options, headers, include_names = _jitify_prep(
                                      ^^^^^^^^^^^^^
  File "C:\Users\confidential\PycharmProjects\nunpy\venv\Lib\site-packages\cupy\cuda\compiler.py", line 233, in _jitify_prep
    jitify._init_module()
  File "cupy\cuda\jitify.pyx", line 212, in cupy.cuda.jitify._init_module
  File "cupy\cuda\jitify.pyx", line 233, in cupy.cuda.jitify._init_module
  File "cupy\cuda\jitify.pyx", line 209, in cupy.cuda.jitify._init_cupy_headers
  File "cupy\cuda\jitify.pyx", line 198, in cupy.cuda.jitify._init_cupy_headers_from_scratch  
  File "cupy\cuda\jitify.pyx", line 128, in cupy.cuda.jitify.dump_cache
OSError: [WinError 123] The syntax for the file name, directory name, or volume label is incorrect: 'C:\\Users\\confidential\\.cupy\\jitify_cache\\tmps16uxq46' -> 'C:\\Users\\confidential/.cupy/jitify_cache/jitify_<unknown>_200200_12030_2_b3452ffa79e273adadd0403b6b0c05b78158b1e0.json'

正确答案

您需要遵循的一些调试步骤。

1）更新cupy

pip install cupy --upgrade

2) 检查权限。 确保运行脚本的用户具有读取和写入 cupy_cache_dir 环境变量中指定的缓存目录的必要权限。

重塑输入数组 如果问题仍然存在，您可以尝试将输入数组重塑为 '(n,)' 的形状，而不是 '(n, 1)' 或 '(1, n)'。

4)禁用jit编译 您可以尝试通过将 cupy_cache_dir 环境变量设置为有效目录来禁用 jit 编译。

import cupy as cp
import os

os.environ['CUPY_CACHE_DIR'] = '/path/to/valid/directory'

将“/path/to/valid/directory”替换为 cupy 可以成功缓存已编译内核的目录。这可能会帮助您避免 oserror。

위 내용은 단 하나의 열 또는 단 하나의 행만 있는 행렬로 작업할 때 Python의 cupy 라이브러리에 있는 amax 및 max 함수가 잘못됩니까?의 상세 내용입니다. 자세한 내용은 PHP 중국어 웹사이트의 기타 관련 기사를 참조하세요!