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Change numpy pinning to 1.20 #18

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merged 1 commit into from
Dec 3, 2021

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charlesbluca
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As of rapidsai/cudf#9687, the latest cuDF / dask-cudf nightlies implicitly require numpy >=1.17,<1.21; this changes our pinning to 1.20 to allow us to grab the latest nightlies again.

cc @pentschev @quasiben

@quasiben
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quasiben commented Dec 3, 2021

I'm approving so we can unblcok CI but I think we should probably remove the pin or set a minimum instead to 1.20.1 rather a true pin

@quasiben quasiben merged commit 0c77517 into rapidsai:main Dec 3, 2021
@charlesbluca
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That makes sense! If this unblocks CI happy to turn this into a constraint

@pentschev
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Yes, I agree, we should set a minimum of NumPy 1.20. I don't see it, where's the implicit pinning to <1.21 coming from in rapidsai/cudf#9687 ?

@charlesbluca
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charlesbluca commented Dec 3, 2021

We bumped numba's minimum version to 0.54, which places additional constraints on Numpy:

$ mamba create -n test -c rapidsai-nightly -c conda-forge "numba>=0.54" numpy=1.21
...
Encountered problems while solving:
  - package numba-0.54.1-py37h51133e4_0 has constraint numpy >=1.17,<1.21 conflicting with numpy-1.21.0-py37h038b26d_0

Versus the older version:

$ mamba create -n test -c rapidsai-nightly -c conda-forge "numba>=0.53.1" numpy=1.21
...
  + numba                0.53.1  py39h56b8d98_1       conda-forge/linux-64        4 MB
  + numpy                1.21.4  py39hdbf815f_0       conda-forge/linux-64        6 MB

@pentschev
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So Numba 0.53 had no constraint on NumPy maximum version, but 0.54 has? Looks a bit odd, but seems due to Python 3.10 support: numba/numba#7563 .

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esc commented Dec 3, 2021

So Numba 0.53 had no constraint on NumPy maximum version, but 0.54 has? Looks a bit odd, but seems due to Python 3.10 support: numba/numba#7563 .

I think that is correct. NumPy pinning was introduced because future versions were causing breakage. IIRC usually the pin for NumPy is created on release branches.

@pentschev
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Yeah, that makes sense, at first it surprised me but now it's all clear. Thanks @esc for the details! 🙂

@charlesbluca
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Looks like the max version here isn't being specified explicitly by Numba either? Inspecting the linux-64 packages, it looks like their max Numpy version is 2.0a0:

image

@pentschev
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I think you only read depends @charlesbluca , as numpy>=1.17,<1.21 is stated in the constraints field.

@charlesbluca
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Ah thanks @pentschev, missed that section 😄 to follow up, this resolved Dask's gpuCI, and with #19 and #20 I switched the Numpy pinning to be a minimum version constraint

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4 participants