Adding horovod

recipes/horovod/build.sh

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+#!/bin/bash
+
+set -ex
+
+# See https://github.com/horovod/horovod/issues/3956
+flatc -c -o horovod/common/wire horovod/common/wire/message.fbs
+flatc -c -I . --include-prefix ../common/wire -o horovod/tensorflow horovod/tensorflow/custom_call_config.fbs
+
+if [[ ${cuda_compiler_version} != "None" ]]; then
+    export HOROVOD_GPU_OPERATIONS=NCCL
+    export HOROVOD_NCCL_LINK=SHARED
+    export HOROVOD_CUDA_HOME=/usr/local/cuda
+fi
+export HOROVOD_WITH_TENSORFLOW=1
+export HOROVOD_WITH_PYTORCH=1
+# mxnet is not available on conda-forge
+# https://github.com/conda-forge/staged-recipes/issues/4447
+export HOROVOD_WITHOUT_MXNET=1
+export HOROVOD_WITH_MPI=1
+# gloo is not avaiable on conda-forge
+export HOROVOD_WITHOUT_GLOO=1
+if [[ "${target_platform}" == osx-* ]]; then
+    # https://conda-forge.org/docs/maintainer/knowledge_base.html#newer-c-features-with-old-sdk
+    export CXXFLAGS="${CXXFLAGS} -D_LIBCPP_DISABLE_AVAILABILITY"
+fi
+
+# default is -j8
+export MAKEFLAGS="-j${CPU_COUNT}"
+python -m pip install . -vv

recipes/horovod/conda_build_config.yaml

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+mpi:
+  - mpich
+  - openmpi

recipes/horovod/meta.yaml

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+{% set name = "horovod" %}
+{% set version = "0.28.1" %}
+{% set proc_type = "cuda" if cuda_compiler_version != "None" else "cpu" %}
+
+package:
+  name: {{ name|lower }}
+  version: {{ version }}
+
+source:
+  url: https://github.com/horovod/horovod/archive/refs/tags/v{{ version }}.tar.gz
+  sha256: 88fbcd2815083607a5d27962f323eae5752e3eb96511aaac98258f280cac0f8e
+
+build:
+  number: 0
+  skip: true  # [win]
+  string: {{ proc_type }}_mpi_{{ mpi }}_h{{ PKG_HASH }}_{{ PKG_BUILDNUM }}
+  ignore_run_exports_from:
+    - flatbuffers
+    - tensorflow
+    - pytorch
+  # Horovod supports multiple frameworks, and the package is built against TensorFlow and PyTorch.
+  # However, usually, the user only uses one of them simultaneously. (by importing either horovod.tensorflow or horovod.torch)
+  # Thus, TensorFlow and PyTorch are not listed in the `run` section, but in the `run_constrained` section.
+  # Users can manually install Horovod and only one of them.
+  # Both TensorFlow and PyTorch libraries are listed in `missing_dso_whitelist`, and a test is added to ensure Horovod libraries can be 
+  # correctly loaded when TensorFlow and PyTorch are installed.
+  # (horovod.tensorflow loads Horovod TensorFlow library and horovod.torch loads Horovod PyTorch library)
+  missing_dso_whitelist:
+    - "*/libtensorflow_framework.so.*"  # [linux]
+    - "*/libtensorflow_cc.so.*"  # [linux]
+    - "*/torch/lib/*.so"  # [linux]
+    - "*/libtensorflow_framework.*.dylib"  # [osx]
+    - "*/libtensorflow_cc.*.dylib"  # [osx]
+    - "*/_pywrap_tensorflow_internal.so"
+    - "*/torch/lib/*.dylib"  # [osx]
+
+requirements:
+  build:
+    - {{ compiler('cxx') }}
+    - {{ compiler('cuda') }}  # [cuda_compiler_version != 'None']
+    - cmake >=3.13
+    - make  # [unix]
+    - python  # [build_platform != target_platform]
+    - cross-python_{{ target_platform }}  # [build_platform != target_platform]
+    - flatbuffers
+  host:
+    - python
+    - pip
+    - wheel
+    - setuptools
+    - pyyaml
+    - cloudpickle
+    - packaging
+    - psutil
+    - nccl  # [cuda_compiler_version != 'None']
+    - {{ mpi }}
+    - mpi4py
+    - tensorflow
+    - tensorflow * {{ proc_type }}*
+    - pytorch
+    - pytorch * {{ proc_type }}*
+    # for flatc
+    - flatbuffers
+    - libboost-headers
+    - lbfgspp
+
+  run:
+    - python
+    - pyyaml
+    - cloudpickle
+    - packaging 
+    - psutil
+    - nccl  # [cuda_compiler_version != 'None']
+    - {{ mpi }}
+    - mpi4py
+
+  run_constrained:
+    - {{ pin_compatible('tensorflow', max_pin='x.x') }} {{ proc_type }}*
+    - {{ pin_compatible('pytorch', max_pin='x.x') }} {{ proc_type }}*
+
+test:
+  requires:
+    - pip
+    - tensorflow
+    - pytorch 
+  imports:
+    - horovod
+    - horovod.tensorflow
+    - horovod.torch
+  commands:
+    - pip check
+    - horovodrun -h
+
+about:
+  home: https://horovod.ai/
+  license: Apache-2.0
+  license_family: Apache
+  license_file: LICENSE
+  summary: 'Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.'
+  doc_url: https://horovod.readthedocs.io/
+  dev_url: https://github.com/horovod/horovod
+
+extra:
+  recipe-maintainers:
+    - njzjz