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bump NCCL floor to 2.18.1.1, relax PyTorch pin #218

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Sep 25, 2024
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4 changes: 2 additions & 2 deletions conda/environments/all_cuda-118_arch-x86_64.yaml
Original file line number Diff line number Diff line change
Expand Up @@ -28,7 +28,7 @@ dependencies:
- librmm==24.10.*,>=0.0.0a0
- nanobind>=0.2.0
- nbsphinx
- nccl
- nccl>=2.18.1.1
- ninja
- numpy>=1.23,<3.0a0
- numpydoc
Expand All @@ -40,7 +40,7 @@ dependencies:
- pytest-xdist
- python>=3.10,<3.13
- pytorch-cuda=11.8
- pytorch=2.0.0
- pytorch>=2.0,<2.4.0a0
- rapids-build-backend>=0.3.0,<0.4.0.dev0
- recommonmark
- scikit-build-core>=0.10.0
Expand Down
2 changes: 1 addition & 1 deletion conda/environments/all_cuda-125_arch-x86_64.yaml
Original file line number Diff line number Diff line change
Expand Up @@ -30,7 +30,7 @@ dependencies:
- librmm==24.10.*,>=0.0.0a0
- nanobind>=0.2.0
- nbsphinx
- nccl
- nccl>=2.18.1.1
- ninja
- numpy>=1.23,<3.0a0
- numpydoc
Expand Down
2 changes: 1 addition & 1 deletion conda/recipes/libwholegraph/conda_build_config.yaml
Original file line number Diff line number Diff line change
Expand Up @@ -17,7 +17,7 @@ doxygen_version:
- ">=1.8.11"

nccl_version:
- ">=2.9.9"
- ">=2.18.1.1"

c_stdlib:
- sysroot
Expand Down
12 changes: 6 additions & 6 deletions dependencies.yaml
Original file line number Diff line number Diff line change
Expand Up @@ -87,7 +87,7 @@ dependencies:
- libraft-headers==24.10.*,>=0.0.0a0
- librmm==24.10.*,>=0.0.0a0
- nanobind>=0.2.0
- nccl
- &nccl nccl>=2.18.1.1
specific:
- output_types: conda
matrices:
Expand Down Expand Up @@ -216,14 +216,14 @@ dependencies:
common:
- output_types: [conda]
packages:
- nccl
- *nccl
test_python:
common:
- output_types: [conda]
packages:
- c-compiler
- cxx-compiler
- nccl
- *nccl
- output_types: [conda, requirements]
packages:
- ninja
Expand Down Expand Up @@ -285,13 +285,13 @@ dependencies:
# If conda-forge supports the new cuda-* packages for CUDA 11.8
# at some point, then we can fully support/properly specify
# this environment.
- pytorch=2.0.0
- &pytorch pytorch>=2.0,<2.4.0a0
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docs build here have been failing like this:

LibMambaUnsatisfiableError: Encountered problems while solving:
  - nothing provides _python_rc needed by python-3.12.0rc3-rc3_hab00c5b_1_cpython

Could not solve for environment specs
The following packages are incompatible
├─ cpuonly is requested and can be installed;
├─ python 3.12**  is installable with the potential options
│  ├─ python [3.12.0|3.12.1|...|3.12.5] would require
│  │  └─ python_abi 3.12.* *_cp312, which can be installed;
│  └─ python 3.12.0rc3 would require
│     └─ _python_rc, which does not exist (perhaps a missing channel);
└─ pytorch 2.0.0**  is not installable because there are no viable options
   ├─ pytorch 2.0.0 would require
   │  └─ python_abi 3.8.* *_cp38, which conflicts with any installable versions previously reported;
   ├─ pytorch 2.0.0 would require
   │  └─ python >=3.10,<3.11.0a0 , which conflicts with any installable versions previously reported;
   ├─ pytorch 2.0.0 would require
   │  └─ cpuonly <0 , which conflicts with any installable versions previously reported;
   ├─ pytorch 2.0.0 would require
   │  └─ python >=3.8,<3.9.0a0 , which conflicts with any installable versions previously reported;
   ├─ pytorch 2.0.0 would require
   │  └─ python >=3.9,<3.10.0a0 , which conflicts with any installable versions previously reported;
   ├─ pytorch 2.0.0 would require
   │  └─ python_abi 3.10.* *_cp310, which conflicts with any installable versions previously reported;
   ├─ pytorch 2.0.0 would require
   │  └─ python_abi 3.11.* *_cp311, which conflicts with any installable versions previously reported;
   ├─ pytorch 2.0.0 would require
   │  └─ python_abi 3.9.* *_cp39, which conflicts with any installable versions previously reported;
   └─ pytorch 2.0.0 would require
      └─ __cuda, which is missing on the system.

(build link)

because:

This PR proposes loosening the pin on pytorch here.

cugraph currently pins to pytorch>=2.0,<2.2.0a0 (code link), but might go to <2.4.0a0 in rapidsai/cugraph#4615 (comment).

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Agree this seems sensible (especially for this release). In 24.12 we can look at relaxing this further

- pytorch-cuda=11.8
- matrix:
arch: aarch64
cuda: "11.8"
packages:
- pytorch=2.0.0
- *pytorch
- pytorch-cuda=11.8
- matrix:
packages:
Expand All @@ -318,7 +318,7 @@ dependencies:
common:
- output_types: [conda]
packages:
- pytorch=2.0.0
- *pytorch
- cpuonly
clang_tools:
common:
Expand Down