build libmxnet, add mxnetw

conda-forge · Jan 20, 2022 · ccf73d3 · ccf73d3
1 parent 0cab488
commit ccf73d3
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diff --git a/recipes/mxnet/build.sh b/recipes/mxnet/build.sh
@@ -0,0 +1,35 @@
+#!/bin/env bash
+
+if [[ "$target_platform" == osx-* ]]; then
+    cp config/darwin.cmake config.cmake
+    CXXFLAGS="${CXXFLAGS} -D_LIBCPP_DISABLE_AVAILABILITY"
+elif [[ "$target_platform" == linux-* ]]; then
+  if [[ "$cuda_compiler_version" == "None" ]]; then
+      cp config/linux.cmake config.cmake
+  else
+     if [[ ${cuda_compiler_version} == 9.2* ]]; then
+         cp config/distribution/linux_cu92.cmake config.cmake
+     elif [[ ${cuda_compiler_version} == 10.0* ]]; then
+         cp config/distribution/linux_cu100.cmake config.cmake
+     elif [[ ${cuda_compiler_version} == 10.1* ]]; then
+         cp config/distribution/linux_cu101.cmake config.cmake
+     elif [[ ${cuda_compiler_version} == 10.2* ]]; then
+         cp config/distribution/linux_cu102.cmake config.cmake
+     elif [[ ${cuda_compiler_version} == 11.0* ]]; then
+         cp config/distribution/linux_cu110.cmake config.cmake
+     elif [[ ${cuda_compiler_version} == 11.2* ]]; then
+         cp config/distribution/linux_cu112.cmake config.cmake
+     fi
+  fi
+fi
+
+mkdir build && cd build
+cmake ${CMAKE_ARGS} DCMAKE_INSTALL_PREFIX=${PREFIX} -DCMAKE_INSTALL_LIBDIR="lib" ..
+cmake --build . --parallel ${CPU_COUNT}
+
+cd ..
+
+export MXNET_LIBRARY_PATH=${PREFIX}/lib/libmxnet.so
+
+$PYTHON -m pip install -e ./python
+
diff --git a/recipes/mxnet/meta.yaml b/recipes/mxnet/meta.yaml
@@ -0,0 +1,133 @@
+{% set name = "mxnet" %}
+{% set version = "v2.0.0.beta0.rc1" %}
+{% set sha256 = "dfb741a07971b2607474b299ac880ba07e9fdaf217404c7d20bd5a4762324f26" %}
+{% set build_number = "0" %}
+{% set proc_type = "cuda" if cuda_compiler_version != "None" else "cpu" %}
+
+
+package:
+  name: mxnet
+  version: {{ version }}
+
+source:
+  - url: https://github.com/apache/incubator-{{ name }}/archive/refs/tags/{{ version }}.tar.gz
+    sha256: {{ sha256 }}
+  # build as provided upstream:
+  # see some discussion here:
+  # https://github.com/apache/incubator-mxnet/issues/19610
+  - url: https://github.com/dmlc/dmlc-core/archive/5df8305.tar.gz
+    sha256: a8046f752f36005564d2924b4b6f73e1aea3cce7ff10f9e19d99ad6a22a045b2
+    folder: 3rdparty/dmlc-core
+  - url: https://github.com/dmlc/ps-lite/archive/34fd45c.tar.gz
+    sha256: ec5d5baab8bbf0c3983ad5f18d7f963f15ae7cd4d154ec204b03c1dceccf209b
+    folder: 3rdparty/ps-lite
+  - url: https://github.com/dmlc/dlpack/archive/3efc489.tar.gz
+    sha256: b59586ce69bcf3efdbf3cf4803fadfeaae4948044e2b8d89cf912194cf28f233
+    folder: 3rdparty/dlpack
+  - url: https://github.com/google/googletest/archive/eb9225c.tar.gz
+    sha256: a4cb4b0c3ebb191b798594aca674ad47eee255dcb4c26885cf7f49777703484f
+    folder: 3rdparty/googletest
+  - url: https://github.com/apache/incubator-tvm/archive/efdac94.tar.gz
+    sha256: 656c38d66baeab885b0212602148bb55ad3cf7d22f52ded8ece53f88e103a2f5
+    folder: 3rdparty/tvm
+  - url: https://github.com/onnx/onnx-tensorrt/archive/2eb74d9.tar.gz
+    sha256: df99819727445c247fb5c21c2fd825ded3269376867457ae84fa6d6f1c0ae331
+    folder: 3rdparty/onnx-tensorrt
+  - url: https://github.com/NVlabs/cub/archive/0158fa1.tar.gz
+    sha256: 43424c4c17a997d1d730c89ec14688671245de7941e02b388d7d3df6ea53777a
+    folder: 3rdparty/nvidia_cub
+  - url: https://github.com/nih-at/libzip/releases/download/v1.8.0/libzip-1.8.0.tar.gz
+    sha256: 30ee55868c0a698d3c600492f2bea4eb62c53849bcf696d21af5eb65f3f3839e
+    folder: 3rdparty/libzip
+  - url: https://github.com/kpu/intgemm/archive/8f28282.tar.gz
+    sha256: bc8bd8015613a13747eb769876385ec53e8c1ea7ae3f8414521dc53b8fcdfc65
+    folder: 3rdparty/intgemm
+  - url: https://github.com/oneapi-src/oneDNN/archive/f40443c.tar.gz
+    sha256: da1dd1bb68ce3318db11e57971f975653e84adcb7d65cd879e558f2245e6de9a
+    folder: 3rdparty/onednn
+
+build:
+  number: {{ build_number }}
+  skip: True  # [win]
+  string: py{{ CONDA_PY }}h{{ PKG_HASH }}_{{ PKG_BUILDNUM }}_{{ proc_type }}  # [cuda_compiler_version == "None"]
+  string: py{{ CONDA_PY }}cuda{{ cuda_compiler_version|replace('.', '') }}h{{ PKG_HASH }}_{{ PKG_BUILDNUM }}_{{ proc_type }}  # [cuda_compiler_version != "None"]
+  run_exports:
+    # ensure matching proc-type
+    - mxnet =*=*_{{ proc_type }}
+
+requirements:
+  build:
+    - {{ compiler('c') }}
+    - {{ compiler('cxx') }}
+    - {{ compiler('fortran') }}
+    - {{ compiler('cuda') }}  # [cuda_compiler_version != "None"]
+    # is this only needed locally???
+    # - sysroot_linux-64 2.17 # [linux64 and cuda_compiler_version != "None"]
+    - openblas
+    - make
+    - cmake
+    - ccache
+    - llvm-openmp  # [osx]
+    - libgomp  # [linux]
+    - python
+    - pip
+    - setuptools
+
+  host:
+    # need to better expose these deps
+    - libgomp  # [linux]
+    - llvm-openmp  # [osx]
+    - mkl
+    - opencv
+    - onednn
+    - numpy >=1.17
+    - requests >=2.20.0,<3
+    - python-graphviz >=0.8.1,<0.9.0
+    - python_version <3.7
+    - python
+    - pip
+  run:
+    # ?
+    - libgomp  # [linux]
+    - llvm-openmp  # [osx]
+    - mkl
+    - opencv
+    - onednn
+    - numpy >=1.17
+    - requests >=2.20.0,<3
+    - python-graphviz >=0.8.1,<0.9.0
+    - python_version
+    - python
+    - pip
+test:
+  imports:
+    - mxnet
+  requires:
+    - pip
+  commands:
+    - pip check
+
+about:
+  home: http://mxnet.io
+  license: Apache-2.0
+  license_family: Apache
+  license_file: LICENSE
+  summary: MXNet is a deep learning framework designed for both efficiency and flexibility
+  description: |
+    Apache MXNet (incubating) is a deep learning framework designed for both
+    efficiency and flexibility. It allows you to mix symbolic and imperative
+    programming to maximize efficiency and productivity. At its core, MXNet
+    contains a dynamic dependency scheduler that automatically parallelizes both
+    symbolic and imperative operations on the fly. A graph optimization layer on
+    top of that makes symbolic execution fast and memory efficient. MXNet is
+    portable and lightweight, scaling effectively to multiple GPUs and multiple
+    machines. MXNet is also more than a deep learning project. It is also a
+    collection of blue prints and guidelines for building deep learning systems,
+    and interesting insights of DL systems for hackers.
+  doc_url: https://mxnet.incubator.apache.org/
+  dev_url: https://github.com/apache/incubator-mxnet
+
+extra:
+  recipe-maintainers:
+    - barry-jin  
+    - ngam