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release numpy <2 pin, and support python 3.13 #719

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release numpy <2 pin, and support python 3.13 #719

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5a2f2dc
release numpy <2 pin
DanielYang59 Oct 22, 2024
3753d5e
TEST: to show error
DanielYang59 Oct 22, 2024
a264fb8
revert pin
DanielYang59 Oct 22, 2024
c1639c0
drop torch pin
DanielYang59 Oct 23, 2024
d7a6d02
try to test python 3.13
DanielYang59 Oct 23, 2024
7c39f8f
exclude torch for python 3.13
DanielYang59 Oct 23, 2024
0a3b012
exclude pint
DanielYang59 Oct 23, 2024
82f6dd1
limit upper python version
DanielYang59 Oct 23, 2024
89c03fe
maximize test coverage as monty test is pretty cheap
DanielYang59 Oct 23, 2024
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4 changes: 2 additions & 2 deletions pyproject.toml
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Original file line number Diff line number Diff line change
Expand Up @@ -20,7 +20,7 @@ classifiers = [
]
dependencies = [
"ruamel.yaml",
"numpy<2.0.0",
"numpy",
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]
version = "2024.10.21"

Expand All @@ -44,7 +44,7 @@ json = [
"pandas",
"pydantic",
"pint",
"torch",
"torch", # need torch>=2.3.0 for numpy 2
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@DanielYang59 DanielYang59 Oct 22, 2024 •
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It seems only torch>=2.3.0 works NumPy 2, I don't want to pin torch>=2.3.0 directly because there could be NumPy 1 user that needs torch < 2.3.0. But as torch is an optional dependency, I would prioritize numpy.

I'm not a torch user at all, is there a workaround?

import torch
import numpy as np  # np is available


tensor = torch.tensor([1,2,3])
print(tensor.numpy().tolist())
A module that was compiled using NumPy 1.x cannot be run in
NumPy 2.1.2 as it may crash. To support both 1.x and 2.x
versions of NumPy, modules must be compiled with NumPy 2.0.
Some module may need to rebuild instead e.g. with 'pybind11>=2.12'.

If you are a user of the module, the easiest solution will be to
downgrade to 'numpy<2' or try to upgrade the affected module.
We expect that some modules will need time to support NumPy 2.

Traceback (most recent call last):  File "/Users/yang/developer/monty/debug/test_dump_torch_tensor.py", line 1, in <module>
    import torch
  File "/Users/yang/developer/monty/venv/lib/python3.12/site-packages/torch/__init__.py", line 1477, in <module>
    from .functional import *  # noqa: F403
  File "/Users/yang/developer/monty/venv/lib/python3.12/site-packages/torch/functional.py", line 9, in <module>
    import torch.nn.functional as F
  File "/Users/yang/developer/monty/venv/lib/python3.12/site-packages/torch/nn/__init__.py", line 1, in <module>
    from .modules import *  # noqa: F403
  File "/Users/yang/developer/monty/venv/lib/python3.12/site-packages/torch/nn/modules/__init__.py", line 35, in <module>
    from .transformer import TransformerEncoder, TransformerDecoder, \
  File "/Users/yang/developer/monty/venv/lib/python3.12/site-packages/torch/nn/modules/transformer.py", line 20, in <module>
    device: torch.device = torch.device(torch._C._get_default_device()),  # torch.device('cpu'),
/Users/yang/developer/monty/venv/lib/python3.12/site-packages/torch/nn/modules/transformer.py:20: UserWarning: Failed to initialize NumPy: _ARRAY_API not found (Triggered internally at /Users/runner/work/pytorch/pytorch/pytorch/torch/csrc/utils/tensor_numpy.cpp:84.)
  device: torch.device = torch.device(torch._C._get_default_device()),  # torch.device('cpu'),
Traceback (most recent call last):
  File "/Users/yang/developer/monty/debug/test_dump_torch_tensor.py", line 4, in <module>
    print(tensor.numpy().tolist())
          ^^^^^^^^^^^^^^
RuntimeError: Numpy is not available

]
multiprocessing = ["tqdm"]
optional = ["monty[dev,json,multiprocessing,serialization]"]
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