# This file created by conda-build 3.22.0
# meta.yaml template originally from:
# /work/aggregate/sentencepiece-feedstock/recipe, last modified Mon Feb 13 19:13:27 2023
# ------------------------------------------------

package:
  name: sentencepiece
  version: 0.1.95
source:
  sha256: 1c0bd83e03f71a10fc934b7ce996e327488b838587f03159fd392c77c7701389
  url: https://github.com/google/sentencepiece/archive/v0.1.95.tar.gz
build:
  missing_dso_whitelist:
    - '*/libc.so.*'
    - '*/libm.so.*'
    - '*/libpthread.so.*'
    - /lib64/ld-linux-x86-64.so.*
  number: '0'
  string: py311hdb19cb5_0
requirements:
  host:
    - _libgcc_mutex 0.1 main
    - _openmp_mutex 5.1 1_gnu
    - _sysroot_linux-64_curr_repodata_hack 3 haa98f57_10
    - binutils_impl_linux-64 2.38 h2a08ee3_1
    - binutils_linux-64 2.38.0 hc2dff05_0
    - bzip2 1.0.8 h7b6447c_0
    - c-ares 1.18.1 h7f8727e_0
    - ca-certificates 2023.01.10 h06a4308_0
    - certifi 2022.12.7 py311h06a4308_0
    - cmake 3.22.1 h1fce559_0
    - expat 2.4.9 h6a678d5_0
    - gcc_impl_linux-64 11.2.0 h1234567_1
    - gcc_linux-64 11.2.0 h5c386dc_0
    - gxx_impl_linux-64 11.2.0 h1234567_1
    - gxx_linux-64 11.2.0 hc2dff05_0
    - kernel-headers_linux-64 3.10.0 h57e8cba_10
    - krb5 1.19.4 h568e23c_0
    - ld_impl_linux-64 2.38 h1181459_1
    - libcurl 7.87.0 h91b91d3_0
    - libedit 3.1.20221030 h5eee18b_0
    - libev 4.33 h7f8727e_1
    - libffi 3.4.2 h6a678d5_6
    - libgcc-devel_linux-64 11.2.0 h1234567_1
    - libgcc-ng 11.2.0 h1234567_1
    - libgomp 11.2.0 h1234567_1
    - libnghttp2 1.46.0 hce63b2e_0
    - libssh2 1.10.0 h8f2d780_0
    - libstdcxx-devel_linux-64 11.2.0 h1234567_1
    - libstdcxx-ng 11.2.0 h1234567_1
    - libuuid 1.41.5 h5eee18b_0
    - libuv 1.40.0 h7b6447c_0
    - lz4-c 1.9.4 h6a678d5_0
    - make 4.2.1 h1bed415_1
    - ncurses 6.4 h6a678d5_0
    - openssl 1.1.1t h7f8727e_0
    - pip 22.3.1 py311h06a4308_0
    - pkg-config 0.29.2 h1bed415_8
    - python 3.11.0 h7a1cb2a_2
    - readline 8.2 h5eee18b_0
    - rhash 1.4.1 h3c74f83_1
    - setuptools 65.5.0 py311h06a4308_0
    - sqlite 3.40.1 h5082296_0
    - sysroot_linux-64 2.17 h57e8cba_10
    - tk 8.6.12 h1ccaba5_0
    - tzdata 2022g h04d1e81_0
    - wheel 0.37.1 pyhd3eb1b0_0
    - xz 5.2.10 h5eee18b_1
    - zlib 1.2.13 h5eee18b_0
    - zstd 1.5.2 ha4553b6_0
  run:
    - libgcc-ng >=11.2.0
    - libstdcxx-ng >=11.2.0
    - python >=3.11,<3.12.0a0
test:
  commands:
    - pip check
    - spm_export_vocab --help
    - spm_normalize --help
    - cd python && pytest test
  imports:
    - sentencepiece
  requires:
    - pip
    - pytest
  source_files:
    - data
    - python/test
about:
  description: SentencePiece implements subword units (e.g., byte-pair-encoding (BPE)
    [Sennrich et al.]) and unigram language model [Kudo.]) with the extension of direct
    training from raw sentences. SentencePiece allows us to make a purely end-to-end
    system that does not depend on language-specific pre/postprocessing.
  dev_url: https://github.com/google/sentencepiece/
  doc_url: https://github.com/google/sentencepiece/blob/master/doc/api.md
  home: https://github.com/google/sentencepiece/
  license: Apache-2.0
  license_family: Apache
  license_file: LICENSE
  summary: SentencePiece is an unsupervised text tokenizer and detokenizer mainly
    for Neural Network-based text generation systems where the vocabulary size is
    predetermined prior to the neural model training.
extra:
  copy_test_source_files: true
  final: true
  recipe-maintainers:
    - ndmaxar
    - oblute
    - rluria14
    - setu4993
