<commit_before>workers: 10
tmp: &tmp_dir tiny_test/tmp_dir
test:
    output: tiny_test/EN_ES.tgt_ann.test

datasets:
  training:
    - module: marmot.representations.wmt_representation_generator.WMTRepresentationGenerator
      args:
        - tiny_test/EN_ES.tgt_ann.train
        - tiny_test/EN_ES.source.train
        - *tmp_dir
        - False
  test:
    - module: marmot.representations.wmt_representation_generator.WMTRepresentationGenerator
      args:
        - tiny_test/EN_ES.tgt_ann.test
        - tiny_test/EN_ES.source.test
        - *tmp_dir
        - False

representations:
  - module: marmot.representations.alignment_representation_generator.AlignmentRepresentationGenerator
    args:
      - tiny_test/europarl_align_model
  - module: marmot.representations.pos_representation_generator.POSRepresentationGenerator
    args:
      - tiny_test/tree-tagger
      - tiny_test/spanish-par-linux-3.2-utf8.bin
      - 'target'
      - *tmp_dir
  - module: marmot.representations.pos_representation_generator.POSRepresentationGenerator
    args:
      - tiny_test/tree-tagger
      - tiny_test/english-utf8.par
      - 'source'
      - *tmp_dir
  - module: marmot.representations.google_translate_representation_generator.GoogleTranslateRepresentationGenerator
    args:
      - 'es'

# if 'sequential', contexts are generated as lists of lists (lists of sequences)
# if 'plain', a single list of contexts is generated
# if 'token', a separate list of contexts for every token
# TODO: change the contexts param name to 'data_type' for clarity
contexts: plain
filters:
  - min_count: 100
  - min_label_count: 30
  - proportion: 2

features:
  binarize: True
  persist: False
  persist_dir: marmot_feature_dump

feature_extractors:
  - module: marmot.features.token_count_feature_extractor.TokenCountFeatureExtractor
  - module: marmot.features.alignment_feature_extractor.AlignmentFeatureExtractor
    args:
      - ''                                               # alignment model
      - ''     # parallel corpus - source
      - ''     # parallel corpus - target
  - module: marmot.features.dictionary_feature_extractor.DictionaryFeatureExtractor
    args:
      - 'spanish'              # target language for stopwords extraction
  - module: marmot.features.lm_feature_extractor.LMFeatureExtractor
    args:
      - tiny_test/europarl.1000.es # file for LM
      - 3                                            # LM order
  - module: marmot.features.source_lm_feature_extractor.SourceLMFeatureExtractor
    args:<commit_msg>config change to fit the new LM feature<commit_after>workers: 10
tmp: &tmp_dir tiny_test/tmp_dir
test:
    output: tiny_test/EN_ES.tgt_ann.test

datasets:
  training:
    - module: marmot.representations.wmt_representation_generator.WMTRepresentationGenerator
      args:
        - tiny_test/EN_ES.tgt_ann.train
        - tiny_test/EN_ES.source.train
        - *tmp_dir
        - False
  test:
    - module: marmot.representations.wmt_representation_generator.WMTRepresentationGenerator
      args:
        - tiny_test/EN_ES.tgt_ann.test
        - tiny_test/EN_ES.source.test
        - *tmp_dir
        - False

representations:
  - module: marmot.representations.alignment_representation_generator.AlignmentRepresentationGenerator
    args:
      - tiny_test/europarl_align_model
  - module: marmot.representations.pos_representation_generator.POSRepresentationGenerator
    args:
      - tiny_test/tree-tagger
      - tiny_test/spanish-par-linux-3.2-utf8.bin
      - 'target'
      - *tmp_dir
  - module: marmot.representations.pos_representation_generator.POSRepresentationGenerator
    args:
      - tiny_test/tree-tagger
      - tiny_test/english-utf8.par
      - 'source'
      - *tmp_dir
  - module: marmot.representations.google_translate_representation_generator.GoogleTranslateRepresentationGenerator
    args:
      - 'es'

# if 'sequential', contexts are generated as lists of lists (lists of sequences)
# if 'plain', a single list of contexts is generated
# if 'token', a separate list of contexts for every token
# TODO: change the contexts param name to 'data_type' for clarity
contexts: plain
filters:
  - min_count: 100
  - min_label_count: 30
  - proportion: 2

features:
  binarize: True
  persist: False
  persist_dir: marmot_feature_dump

feature_extractors:
  - module: marmot.features.token_count_feature_extractor.TokenCountFeatureExtractor
  - module: marmot.features.alignment_feature_extractor.AlignmentFeatureExtractor
    args:
      - ''                                               # alignment model
      - ''     # parallel corpus - source
      - ''     # parallel corpus - target
  - module: marmot.features.dictionary_feature_extractor.DictionaryFeatureExtractor
    args:
      - 'spanish'              # target language for stopwords extraction
  - module: marmot.features.lm_feature_extractor.LMFeatureExtractor
    args:
      - tiny_test/europarl.1000.es # file for LM
      - 
      - 
      - 3                                            # LM order
  - module: marmot.features.source_lm_feature_extractor.SourceLMFeatureExtractor
    args:
{'fraction_non_alphanumeric': 0.07536118703631393, 'fraction_numerical': 0.006638032018742679, 'mean_word_length': 2.778023598820059, 'pattern_counts': {'":': 0, '<': 3, '<?xml version=': 0, '>': 3, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 8, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'dir': 'git-commits-cleaned', 'id': '1544379', 'n_tokens_mistral': 1593, 'n_tokens_neox': 1519, 'n_words': 288}