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Update fmt (to 11.0.2) and spdlog (to 1.14.1), add those libraries to libcuml conda host dependencies #6071

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merged 19 commits into from
Sep 24, 2024
Merged

Update fmt (to 11.0.2) and spdlog (to 1.14.1), add those libraries to libcuml conda host dependencies #6071

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9981da1
Update fmt (to 11.0.2) and spdlog (to 1.14.1).
jameslamb Sep 18, 2024
67fbab3
Update fmt (to 11.0.2) and spdlog (to 1.14.1).
jameslamb Sep 18, 2024
6da7103
add cumlprims_mg
jameslamb Sep 18, 2024
2a286c1
Merge branch 'branch-24.10' into fmt-and-spdlog
jameslamb Sep 18, 2024
9687611
move rapids-cmake overrides [skip ci]
jameslamb Sep 18, 2024
1ca0b5f
fix testing
jameslamb Sep 19, 2024
721aa88
branch
jameslamb Sep 19, 2024
557fca6
fix clones
jameslamb Sep 19, 2024
8ca0180
run all CI
jameslamb Sep 20, 2024
c7b3321
Merge branch 'branch-24.10' into fmt-and-spdlog
jameslamb Sep 23, 2024
0654919
use cumlprims_mg packages
jameslamb Sep 23, 2024
a1d76d4
try to avoid cloning cumlprims_mg
jameslamb Sep 23, 2024
5b812f0
add host dependencies on fmt and spdlog in libcuml
jameslamb Sep 23, 2024
7724113
explicitly pin fmt and spdlog in test environment
jameslamb Sep 23, 2024
2024f9e
Merge branch 'branch-24.10' of github.com:rapidsai/cuml into fmt-and-…
jameslamb Sep 23, 2024
af19c93
remove testing-only details
jameslamb Sep 23, 2024
5382685
Merge branch 'fmt-and-spdlog' of github.com:jameslamb/cuml into fmt-a…
jameslamb Sep 23, 2024
9d3de8d
revert testing changes in dependencies.yaml
jameslamb Sep 23, 2024
c587389
remove scripts
jameslamb Sep 23, 2024
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3 changes: 3 additions & 0 deletions ci/build_cpp.sh
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Expand Up @@ -11,6 +11,9 @@ source rapids-date-string

export CMAKE_GENERATOR=Ninja

cd "$(dirname "$(realpath "${BASH_SOURCE[0]}")")"/../
source ./ci/use_conda_packages_from_prs.sh

rapids-print-env

rapids-logger "Begin cpp build"
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3 changes: 3 additions & 0 deletions ci/build_python.sh
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Expand Up @@ -11,6 +11,9 @@ source rapids-date-string

export CMAKE_GENERATOR=Ninja

cd "$(dirname "$(realpath "${BASH_SOURCE[0]}")")"/../
source ./ci/use_conda_packages_from_prs.sh

rapids-print-env

rapids-generate-version > ./VERSION
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4 changes: 4 additions & 0 deletions ci/build_wheel.sh
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Expand Up @@ -14,6 +14,10 @@ RAPIDS_PY_CUDA_SUFFIX="$(rapids-wheel-ctk-name-gen ${RAPIDS_CUDA_VERSION})"
# everywhere except in the final wheel name.
PACKAGE_CUDA_SUFFIX="-${RAPIDS_PY_CUDA_SUFFIX}"

cd "$(dirname "$(realpath "${BASH_SOURCE[0]}")")"/../
source ./ci/use_wheels_from_prs.sh
export PIP_CONSTRAINT=/tmp/constraints.txt

rapids-generate-version > ./VERSION

cd ${package_dir}
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2 changes: 2 additions & 0 deletions ci/test_cpp.sh
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Expand Up @@ -8,6 +8,8 @@ cd "$(dirname "$(realpath "${BASH_SOURCE[0]}")")"/../

. /opt/conda/etc/profile.d/conda.sh

source ./ci/use_conda_packages_from_prs.sh

rapids-logger "Downloading artifacts from previous jobs"
CPP_CHANNEL=$(rapids-download-conda-from-s3 cpp)

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1 change: 1 addition & 0 deletions ci/test_notebooks.sh
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Expand Up @@ -3,6 +3,7 @@
set -euo pipefail

. /opt/conda/etc/profile.d/conda.sh
source ./ci/use_conda_packages_from_prs.sh

rapids-logger "Downloading artifacts from previous jobs"
CPP_CHANNEL=$(rapids-download-conda-from-s3 cpp)
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1 change: 1 addition & 0 deletions ci/test_python_common.sh
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Expand Up @@ -4,6 +4,7 @@
set -euo pipefail

. /opt/conda/etc/profile.d/conda.sh
source ./ci/use_conda_packages_from_prs.sh
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Not specific to this line, but just choosing a place to start a threaded conversation.

All conda-based tests are failing with issues like this:

Fatal Python error: Aborted
Thread 0x00007f1903eea640 (most recent call first):
  File "/opt/conda/envs/test/lib/python3.12/site-packages/execnet/gateway_base.py", line 534 in read
  File "/opt/conda/envs/test/lib/python3.12/site-packages/execnet/gateway_base.py", line 567 in from_io
  File "/opt/conda/envs/test/lib/python3.12/site-packages/execnet/gateway_base.py", line 1160 in _thread_receiver
  File "/opt/conda/envs/test/lib/python3.12/site-packages/execnet/gateway_base.py", line 341 in run
  File "/opt/conda/envs/test/lib/python3.12/site-packages/execnet/gateway_base.py", line 411 in _perform_spawn
Current thread 0x00007f1904b0e740 (most recent call first):
  File "/opt/conda/envs/test/lib/python3.12/site-packages/cuml/internals/api_decorators.py", line 190 in wrapper
...
Extension modules: cython.cimports.libc.math, Cython.Utils, numpy._core._multiarray_umath, numpy._core._multiarray_tests
...
.[gw13] node down: Not properly terminated

(build link)

I'll investigate this right now. I suspect it might be something related to symbol visibility (like rapidsai/cudf#15483 (comment)).

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Ah!! It looks like either I missed some dependencies in the test scripts, or something else is holding back the fmt / spdlog version?

I see that RAPIDS libraries are coming from rapidsai-nightly and not the CI artifacts, and that the older versions of fmt and spdlog are being used.

...
cudf                      24.10.00a369    cuda11_py310_240923_g9b4c4c721c_369    rapidsai-nightly
cuml                      24.10.00a70     cuda11_py310_240923_ga1d76d4da_70    file:///tmp/python_channel
...
distributed-ucxx          0.40.00a        py3.10_240923_ga07a40f_28    rapidsai-nightly
...
fmt                       10.2.1               h00ab1b0_0    conda-forge
...

(build link)

Will try replicating that conda solve locally.

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Testing locally, I found that if I added constraints like fmt>=11.0.2, spdlog>=1.14.1 in the conda environment, the solver was able to solve with all of cuml's runtime dependencies... including the versions of cudf, rmm, ucxx, etc. produced from the PRs for rapidsai/build-planning#56.

I think that libcuml conda packages need host: dependencies on spdlog and fmt.

That library's code directly uses both of those:

cuml/cpp/src/common/logger.cpp

Lines 20 to 21 in 7de8831

#include <spdlog/sinks/stdout_color_sinks.h> // NOLINT
#include <spdlog/spdlog.h> // NOLINT

cuml/cpp/include/cuml/common/callbackSink.hpp

Line 47 in 7de8831

std::string msg_string = fmt::to_string(formatted);

And having those dependencies would prevent these situations during development where the solver is able to choose to fall back to older RAPIDS nightlies from within the same release (but supporting different fmt / spdlog).

cudf is doing the same thing: https://github.com/rapidsai/cudf/blob/9b4c4c721c399bae9e88733da79daa1a10644481/conda/recipes/libcudf/meta.yaml#L69-L71

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This is probably the right solution, thanks for investigating.

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This ended up not being enough 😭

Look at https://github.com/rapidsai/cuml/actions/runs/10998530224/job/30541086357?pr=6071.

The environment is still solving with fmt==10.2.1, spdlog==1.12.0, and older RAPIDS 24.10.* nightlies that support those (build link)... even though it used the cuml / libcuml packages from CI here.

cudf                      24.10.00a371    cuda11_py310_240923_g625590686f_371    rapidsai-nightly
cuml                      24.10.00a71     cuda11_py310_240923_g5b812f0e9_71    file:///tmp/python_channel
...
fmt                       10.2.1               h00ab1b0_0    conda-forge
...
libcudf                   24.10.00a371    cuda11_240923_g625590686f_371    rapidsai-nightly
...
libcuml                   24.10.00a71     cuda11_240923_g5b812f0e9_71    file:///tmp/cpp_channel
libcumlprims              24.10.00a       cuda11_240923_gddfb9dd_8    rapidsai-nightly
...
rmm                       24.10.00a40     cuda11_py310_240923_g58039d3c_40    rapidsai-nightly
...
spdlog                    1.12.0               hd2e6256_2    conda-forge
...

I just pushed another commit explicitly pinning fmt and spdlog in the conda test environments, to force the solver to use the newer packages.

This should be safe to do... as soon as there are librmm packages published to rapids-nightly containing the changes from rapidsai/rmm#1678, every environment containing the latest librmm / rmm will have those same pins in it.

If that works, that's evidence that the fmt / spdlog update is safe and we can start moving forward.

I think both of those changes are worth merging here

  • adding the host: dependencies = to make CPM unnecessary for spdlog and avoid unnecessary vendoring and therefore file clobbering
  • explicitly pinning in test environments = make such fallbacks during development less likely the next time we do an update like this

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🎉 I see tests now passing and fmt==11.0.2 + spdlog==1.14.1 getting installed!

Build link: https://github.com/rapidsai/cuml/actions/runs/11000193616/job/30544094053?pr=6071

Another thing that I think happened here.... it's been several days since the cudf CI artifacts being pulled in here were produced, so the rapidsai-nightly channel's versions are now newer.

e.g. rapidsai/cudf#16806 produces cudf==24.10.00a364 but rapidsai-nightly now contains cudf==24.10.00a371. That would also explain why some of the CI artifacts are being ignored, in favor of those from rapidsai-nightly.

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See here: #6071 (comment)


rapids-logger "Downloading artifacts from previous jobs"
CPP_CHANNEL=$(rapids-download-conda-from-s3 cpp)
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4 changes: 4 additions & 0 deletions ci/test_wheel.sh
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Expand Up @@ -3,6 +3,10 @@

set -euo pipefail

cd "$(dirname "$(realpath "${BASH_SOURCE[0]}")")"/../
source ./ci/use_wheels_from_prs.sh
export PIP_CONSTRAINT=/tmp/constraints.txt

mkdir -p ./dist
RAPIDS_PY_CUDA_SUFFIX="$(rapids-wheel-ctk-name-gen ${RAPIDS_CUDA_VERSION})"
RAPIDS_PY_WHEEL_NAME="cuml_${RAPIDS_PY_CUDA_SUFFIX}" rapids-download-wheels-from-s3 ./dist
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28 changes: 28 additions & 0 deletions ci/use_conda_packages_from_prs.sh
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@@ -0,0 +1,28 @@
#!/bin/bash
# Copyright (c) 2024, NVIDIA CORPORATION.

LIBRMM_CHANNEL=$(rapids-get-pr-conda-artifact rmm 1678 cpp)
RMM_CHANNEL=$(rapids-get-pr-conda-artifact rmm 1678 python)

CUDF_CPP_CHANNEL=$(rapids-get-pr-conda-artifact cudf 16806 cpp)
CUDF_PYTHON_CHANNEL=$(rapids-get-pr-conda-artifact cudf 16806 python)

UCXX_CHANNEL=$(rapids-get-pr-conda-artifact ucxx 278 cpp)

LIBRAFT_CHANNEL=$(rapids-get-pr-conda-artifact raft 2433 cpp)
RAFT_CHANNEL=$(rapids-get-pr-conda-artifact raft 2433 python)

# NOTE: cloning private repos with rapids-get-pr-conda-artifact doesn't work,
# so need to explicitly set the SHA to use
CUMLPRIMS_CHANNEL=$(
RAPIDS_SHA=6f9f474 rapids-get-pr-conda-artifact cumlprims_mg 211 cpp 6f9f474
)

conda config --system --add channels "${LIBRMM_CHANNEL}"
conda config --system --add channels "${RMM_CHANNEL}"
conda config --system --add channels "${CUDF_CPP_CHANNEL}"
conda config --system --add channels "${CUDF_PYTHON_CHANNEL}"
conda config --system --add channels "${UCXX_CHANNEL}"
conda config --system --add channels "${LIBRAFT_CHANNEL}"
conda config --system --add channels "${RAFT_CHANNEL}"
conda config --system --add channels "${CUMLPRIMS_CHANNEL}"
59 changes: 59 additions & 0 deletions ci/use_wheels_from_prs.sh
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@@ -0,0 +1,59 @@
#!/bin/bash
# Copyright (c) 2024, NVIDIA CORPORATION.

RAPIDS_PY_CUDA_SUFFIX="$(rapids-wheel-ctk-name-gen ${RAPIDS_CUDA_VERSION})"

LIBRMM_CHANNEL=$(
RAPIDS_PY_WHEEL_NAME=rmm_${RAPIDS_PY_CUDA_SUFFIX} rapids-get-pr-wheel-artifact rmm 1678 cpp
)
RMM_CHANNEL=$(
RAPIDS_PY_WHEEL_NAME=rmm_${RAPIDS_PY_CUDA_SUFFIX} rapids-get-pr-wheel-artifact rmm 1678 python
)

UCXX_CHANNEL=$(
RAPIDS_PY_WHEEL_NAME=ucxx_${RAPIDS_PY_CUDA_SUFFIX} rapids-get-pr-wheel-artifact ucxx 278 python
)
LIBUCXX_CHANNEL=$(
RAPIDS_PY_WHEEL_NAME=libucxx_${RAPIDS_PY_CUDA_SUFFIX} rapids-get-pr-wheel-artifact ucxx 278 cpp
)
DISTRIBUTED_UCXX_CHANNEL=$(
RAPIDS_PY_WHEEL_NAME=distributed_ucxx_${RAPIDS_PY_CUDA_SUFFIX} rapids-get-pr-wheel-artifact ucxx 278 python
)

CUDF_CHANNEL=$(
RAPIDS_PY_WHEEL_NAME=cudf_${RAPIDS_PY_CUDA_SUFFIX} rapids-get-pr-wheel-artifact cudf 16806 python
)
LIBCUDF_CHANNEL=$(
RAPIDS_PY_WHEEL_NAME=libcudf_${RAPIDS_PY_CUDA_SUFFIX} rapids-get-pr-wheel-artifact cudf 16806 cpp
)
PYLIBCUDF_CHANNEL=$(
RAPIDS_PY_WHEEL_NAME=pylibcudf_${RAPIDS_PY_CUDA_SUFFIX} rapids-get-pr-wheel-artifact cudf 16806 python
)
DASK_CUDF_CHANNEL=$(
RAPIDS_PY_WHEEL_NAME=dask_cudf_${RAPIDS_PY_CUDA_SUFFIX} \
RAPIDS_PY_WHEEL_PURE=1 \
rapids-get-pr-wheel-artifact cudf 16806 python
)

RAFT_DASK_CHANNEL=$(
RAPIDS_PY_WHEEL_NAME=raft_dask_${RAPIDS_PY_CUDA_SUFFIX} rapids-get-pr-wheel-artifact raft 2433 python
)
PYLIBRAFT_CHANNEL=$(
RAPIDS_PY_WHEEL_NAME=pylibraft_${RAPIDS_PY_CUDA_SUFFIX} rapids-get-pr-wheel-artifact raft 2433 python
)

cat > /tmp/constraints.txt <<EOF
librmm-${RAPIDS_PY_CUDA_SUFFIX} @ file://$(echo ${LIBRMM_CHANNEL}/librmm_*.whl)
rmm-${RAPIDS_PY_CUDA_SUFFIX} @ file://$(echo ${RMM_CHANNEL}/rmm_*.whl)
cudf-${RAPIDS_PY_CUDA_SUFFIX} @ file://$(echo ${CUDF_CHANNEL}/cudf_*.whl)
libcudf-${RAPIDS_PY_CUDA_SUFFIX} @ file://$(echo ${LIBCUDF_CHANNEL}/libcudf_*.whl)
pylibcudf-${RAPIDS_PY_CUDA_SUFFIX} @ file://$(echo ${PYLIBCUDF_CHANNEL}/pylibcudf_*.whl)
dask-cudf-${RAPIDS_PY_CUDA_SUFFIX} @ file://$(echo ${DASK_CUDF_CHANNEL}/dask_cudf_*.whl)
ucxx-${RAPIDS_PY_CUDA_SUFFIX} @ file://$(echo ${UCXX_CHANNEL}/ucxx_*.whl)
libucxx-${RAPIDS_PY_CUDA_SUFFIX} @ file://$(echo ${LIBUCXX_CHANNEL}/libucxx_*.whl)
distributed-ucxx-${RAPIDS_PY_CUDA_SUFFIX} @ file://$(echo ${DISTRIBUTED_UCXX_CHANNEL}/distributed_ucxx_*.whl)
raft-dask-${RAPIDS_PY_CUDA_SUFFIX} @ file://$(echo ${RAFT_DASK_CHANNEL}/raft_dask_*.whl)
pylibraft-${RAPIDS_PY_CUDA_SUFFIX} @ file://$(echo ${PYLIBRAFT_CHANNEL}/pylibraft_*.whl)
EOF

export PIP_CONSTRAINT=/tmp/constraints.txt
2 changes: 2 additions & 0 deletions conda/environments/all_cuda-118_arch-x86_64.yaml
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Expand Up @@ -20,6 +20,7 @@ dependencies:
- dask-cudf==24.10.*,>=0.0.0a0
- dask-ml
- doxygen=1.9.1
- fmt>=11.0.2,<12
- gcc_linux-64=11.*
- graphviz
- hdbscan>=0.8.38,<0.8.39
Expand Down Expand Up @@ -69,6 +70,7 @@ dependencies:
- scipy>=1.8.0
- seaborn
- setuptools
- spdlog>=1.14.1,<1.15
- sphinx-copybutton
- sphinx-markdown-tables
- sphinx<6
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2 changes: 2 additions & 0 deletions conda/environments/all_cuda-125_arch-x86_64.yaml
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Expand Up @@ -22,6 +22,7 @@ dependencies:
- dask-cudf==24.10.*,>=0.0.0a0
- dask-ml
- doxygen=1.9.1
- fmt>=11.0.2,<12
- gcc_linux-64=11.*
- graphviz
- hdbscan>=0.8.38,<0.8.39
Expand Down Expand Up @@ -65,6 +66,7 @@ dependencies:
- scipy>=1.8.0
- seaborn
- setuptools
- spdlog>=1.14.1,<1.15
- sphinx-copybutton
- sphinx-markdown-tables
- sphinx<6
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2 changes: 2 additions & 0 deletions conda/environments/clang_tidy_cuda-118_arch-x86_64.yaml
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Expand Up @@ -14,6 +14,7 @@ dependencies:
- cuda-version=11.8
- cudatoolkit
- cxx-compiler
- fmt>=11.0.2,<12
- gcc_linux-64=11.*
- libcublas-dev=11.11.3.6
- libcublas=11.11.3.6
Expand All @@ -31,6 +32,7 @@ dependencies:
- librmm==24.10.*,>=0.0.0a0
- ninja
- nvcc_linux-64=11.8
- spdlog>=1.14.1,<1.15
- sysroot_linux-64==2.17
- tomli
name: clang_tidy_cuda-118_arch-x86_64
2 changes: 2 additions & 0 deletions conda/environments/cpp_all_cuda-118_arch-x86_64.yaml
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Expand Up @@ -12,6 +12,7 @@ dependencies:
- cuda-version=11.8
- cudatoolkit
- cxx-compiler
- fmt>=11.0.2,<12
- gcc_linux-64=11.*
- libcublas-dev=11.11.3.6
- libcublas=11.11.3.6
Expand All @@ -29,5 +30,6 @@ dependencies:
- librmm==24.10.*,>=0.0.0a0
- ninja
- nvcc_linux-64=11.8
- spdlog>=1.14.1,<1.15
- sysroot_linux-64==2.17
name: cpp_all_cuda-118_arch-x86_64
2 changes: 2 additions & 0 deletions conda/environments/cpp_all_cuda-125_arch-x86_64.yaml
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Expand Up @@ -14,6 +14,7 @@ dependencies:
- cuda-profiler-api
- cuda-version=12.5
- cxx-compiler
- fmt>=11.0.2,<12
- gcc_linux-64=11.*
- libcublas-dev
- libcufft-dev
Expand All @@ -25,5 +26,6 @@ dependencies:
- libraft==24.10.*,>=0.0.0a0
- librmm==24.10.*,>=0.0.0a0
- ninja
- spdlog>=1.14.1,<1.15
- sysroot_linux-64==2.17
name: cpp_all_cuda-125_arch-x86_64
6 changes: 6 additions & 0 deletions conda/recipes/libcuml/conda_build_config.yaml
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Expand Up @@ -19,6 +19,12 @@ c_stdlib_version:
cmake_version:
- ">=3.26.4,!=3.30.0"

fmt_version:
- ">=11.0.2,<12"

spdlog_version:
- ">=1.14.1,<1.15"

treelite_version:
- "=4.3.0"

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2 changes: 2 additions & 0 deletions conda/recipes/libcuml/meta.yaml
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Expand Up @@ -68,10 +68,12 @@ requirements:
- libcusolver-dev
- libcusparse-dev
{% endif %}
- fmt {{ fmt_version }}
- libcumlprims ={{ minor_version }}
- libraft ={{ minor_version }}
- libraft-headers ={{ minor_version }}
- librmm ={{ minor_version }}
- spdlog {{ spdlog_version }}
Comment on lines +71 to +76
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These are in the global list for the split recipe but also need to be in the libcuml package below in order to have run-exports on the appropriate packages. That would eliminate the need for test-time pinnings. I'm not sure which direction we want to go: do we add run-exported dependencies on these to "runtime" packages (these aren't "dev" packages) to enforce consistency, or use test-time pinnings to only ensure that we get compatible builds of librmm, etc. which are exporting these dependencies (and with which we need to avoid conflicts)?

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Ah ok! I'm not that familiar with the ways that split recipes are different from single-package ones, thank you for pointing this out.

I'm not sure precisely what you mean about those two choices... but I can say at least that I think cuml / libcuml should explicitly pin fmt and spdlog, given that it directly uses them: #6071 (comment) (instead of getting that pinning transitively from librmm or similar).

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We talked offline and decided to add these pinnings in the top-level host environment and the build environment created from the common_build: list in dependencies.yaml, but to not mess with run exports or adding explicit run dependencies on fmt / spdlog.

- treelite {{ treelite_version }}

outputs:
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8 changes: 8 additions & 0 deletions dependencies.yaml
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Expand Up @@ -140,10 +140,12 @@ dependencies:
packages:
- c-compiler
- cxx-compiler
- &fmt fmt>=11.0.2,<12
- libcumlprims==24.10.*,>=0.0.0a0
- libraft==24.10.*,>=0.0.0a0
- libraft-headers==24.10.*,>=0.0.0a0
- librmm==24.10.*,>=0.0.0a0
- &spdlog spdlog>=1.14.1,<1.15
specific:
- output_types: conda
matrices:
Expand Down Expand Up @@ -518,6 +520,8 @@ dependencies:
- setuptools # Needed on Python 3.12 for dask-glm, which requires pkg_resources but Python 3.12 doesn't have setuptools by default
- output_types: conda
packages:
- *fmt
- *spdlog
- pip
- pip:
- dask-glm==0.3.0
Expand All @@ -536,3 +540,7 @@ dependencies:
- *scikit_learn
- seaborn
- xgboost
- output_types: conda
packages:
- *fmt
- *spdlog
2 changes: 2 additions & 0 deletions rapids_config.cmake
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Expand Up @@ -26,6 +26,8 @@ else()
)
endif()

set(rapids-cmake-repo jameslamb/rapids-cmake)
set(rapids-cmake-branch fmt-and-spdlog)
if(NOT EXISTS "${CMAKE_CURRENT_BINARY_DIR}/CUML_RAPIDS-${RAPIDS_VERSION_MAJOR_MINOR}.cmake")
file(
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