+1

如何复现行为
在我的Dockerfile中，我运行了以下命令：

FROM --platform=linux/amd64 python:3.12.4

RUN pip install --upgrade pip

RUN pip install torch --index-url https://download.pytorch.org/whl/cpu
RUN pip install spacy

RUN python -m spacy download en_core_web_lg

它返回了以下错误(和堆栈跟踪):

2.519 Traceback (most recent call last):
2.519   File "<frozen runpy>", line 189, in _run_module_as_main
2.519   File "<frozen runpy>", line 148, in _get_module_details
2.519   File "<frozen runpy>", line 112, in _get_module_details
2.519   File "/usr/local/lib/python3.12/site-packages/spacy/__init__.py", line 6, in <module>
2.521     from .errors import setup_default_warnings
2.522   File "/usr/local/lib/python3.12/site-packages/spacy/errors.py", line 3, in <module>
2.522     from .compat import Literal
2.522   File "/usr/local/lib/python3.12/site-packages/spacy/compat.py", line 39, in <module>
2.522     from thinc.api import Optimizer  # noqa: F401
2.522     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
2.522   File "/usr/local/lib/python3.12/site-packages/thinc/api.py", line 1, in <module>
2.522     from .backends import (
2.522   File "/usr/local/lib/python3.12/site-packages/thinc/backends/__init__.py", line 17, in <module>
2.522     from .cupy_ops import CupyOps
2.522   File "/usr/local/lib/python3.12/site-packages/thinc/backends/cupy_ops.py", line 16, in <module>
2.522     from .numpy_ops import NumpyOps
2.522   File "thinc/backends/numpy_ops.pyx", line 1, in init thinc.backends.numpy_ops
2.524 ValueError: numpy.dtype size changed, may indicate binary incompatibility. Expected 96 from C header, got 88 from PyObject

锁定到numpy的先前版本将解决此问题：

FROM --platform=linux/amd64 python:3.12.4

RUN pip install --upgrade pip

RUN pip install torch --index-url https://download.pytorch.org/whl/cpu
RUN pip install numpy==1.26.4 spacy

RUN python -m spacy download en_core_web_lg

这个解决方案有帮助，谢谢

+1 I also had this problem. Thanks for posting the solution 👍

Those solutions indeed works, but I would still like to see a fix in the codebase itself. This issue is that inside the requirements.txt of the project (just an assumption after a short look at the codebase), the version is specified as such:

numpy>=1.15.0; python_version < "3.9"
numpy>=1.19.0; python_version >= "3.9"

I am a huge fan, in all of my projects, of always pinning dependencies even up to the patch version.
I would suggest a PR that looks like this:

numpy>=1.15.0,<2.0.0; python_version < "3.9"
numpy>=1.19.0,<2.0.0; python_version >= "3.9"

This at least pins the version down to major releases, which should anyway always be the case, as major version can (and most likely will always) contain breaking changes.

@DoctorManhattan123 为了澄清，我发布的解决方案仅作为临时措施。
理想情况下，所有使用numpy的下游用户(包括库维护者)都应该完成向numpy 2.0.0的迁移。考虑到发布的大小，我认为这需要时间。
固定版本是为了帮助那些寻求快速修复他们的CI/CD或其他受影响过程的人，直到在受影响的代码库中实施更稳健的解决方案。

关于tinc的问题已经被注意到了。

这很有帮助。谢谢！