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

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merged 9 commits into from
Dec 10, 2024
Merged

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",
]
version = "2024.10.21"

Expand All @@ -44,7 +44,7 @@ json = [
"pandas",
"pydantic",
"pint",
"torch",
"torch", # Note: need torch>=2.3.0 for numpy 2 # 719
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@DanielYang59 DanielYang59 Oct 23, 2024 •
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I decide to drop this pin entirely because I believe it's something torch should resolve instead of monty (i.e. torch should correctly list supported numpy)

Unless tensor.numpy() should not be used at certain versions? I'm not a torch user, input appreciated!

Plan B (which I don't really like because it would narrow the default supported NumPy version) is to have something like:

json = [
...,
monty[torch_with_numpy2,...]
]

torch_with_numpy2 = [
  "numpy>=2",
  "torch>=2.3.0",  # Torch version compatible with numpy 2
]
torch_with_numpy1 = [
  "numpy<2",
  "torch",  
]

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