Add script for training enhanced dependency parsing models based on IWPT'20 Shared Task data.

scripts/train_eud.py

+"""Script to train Enhanced Dependency Parsing models based on IWPT'20 Shared Task data.
+
+Might require:
+conda install -c bioconda perl-list-moreutils
+conda install -c bioconda perl-namespace-autoclean
+conda install -c bioconda perl-moose
+conda install -c dan_blanchard perl-moosex-semiaffordanceaccessor
+"""
+
+import os
+import pathlib
+import subprocess
+from typing import List
+
+from absl import app
+from absl import flags
+
+FLAGS = flags.FLAGS
+LANG2TREEBANK = {
+    "ar": ["Arabic-PADT"],
+    "bg": ["Bulgarian-BTB"],
+    "cs": ["Czech-FicTree", "Czech-CAC", "Czech-PDT", "Czech-PUD"],
+    "nl": ["Dutch-Alpino", "Dutch-LassySmall"],
+    "en": ["English-EWT", "English-PUD"],
+    "et": ["Estonian-EDT", "Estonian-EWT"],
+    "fi": ["Finnish-TDT", "Finnish-PUD"],
+    "fr": ["French-Sequoia", "French-FQB"],
+    "it": ["Italian-ISDT"],
+    "lv": ["Latvian-LVTB"],
+    "lt": ["Lithuanian-ALKSNIS"],
+    "pl": ["Polish-LFG", "Polish-PDB", "Polish-PUD"],
+    "ru": ["Russian-SynTagRus"],
+    "sk": ["Slovak-SNK"],
+    "sv": ["Swedish-Talbanken", "Swedish-PUD"],
+    "ta": ["Tamil-TTB"],
+    "uk": ["Ukrainian-IU"],
+}
+
+LANG2TRANSFORMER = {
+    "en": "bert-base-cased",
+    "pl": "allegro/herbert-base-cased",
+}
+
+flags.DEFINE_list(name="lang", default=list(LANG2TREEBANK.keys()),
+                  help=f"Language of models to train. Possible values: {LANG2TREEBANK.keys()}.")
+flags.DEFINE_string(name="data_dir", default="",
+                    help="Path to 'iwpt2020stdata' directory.")
+flags.DEFINE_string(name="serialization_dir", default="/tmp/",
+                    help="Model serialization dir.")
+flags.DEFINE_integer(name="cuda_device", default=-1,
+                     help="Cuda device id (-1 for cpu).")
+
+
+def path_to_str(path: pathlib.Path) -> str:
+    return str(path.resolve())
+
+
+def merge_files(files: List[str], output: pathlib.Path):
+    if not output.exists():
+        os.system(f"cat {' '.join(files)} > {output}")
+
+
+def execute_command(command, output_file=None):
+    command = [c for c in command.split() if c.strip()]
+    if output_file:
+        with open(output_file, "w") as f:
+            subprocess.run(command, check=True, stdout=f)
+    else:
+        subprocess.run(command, check=True)
+
+
+def collapse_nodes(data_dir: pathlib.Path, treebank_file: pathlib.Path, output: str):
+    output_path = pathlib.Path(output)
+    if not output_path.exists():
+        execute_command(f"perl {path_to_str(data_dir / 'tools' / 'enhanced_collapse_empty_nodes.pl')} "
+                        f"{path_to_str(treebank_file)}", output)
+
+
+def run(_):
+    languages = FLAGS.lang
+    for lang in languages:
+        assert lang in LANG2TREEBANK, f"'{lang}' must be one of {list(LANG2TREEBANK.keys())}."
+        data_dir = pathlib.Path(FLAGS.data_dir)
+        assert data_dir.is_dir(), f"'{data_dir}' is not a directory!"
+
+        treebanks = LANG2TREEBANK[lang]
+        train_paths = []
+        dev_paths = []
+        test_paths = []
+        for treebank in treebanks:
+            treebank_dir = data_dir / f"UD_{treebank}"
+            assert treebank_dir.exists() and treebank_dir.is_dir(), f"'{treebank_dir}' directory doesn't exists."
+            for treebank_file in treebank_dir.iterdir():
+                name = treebank_file.name
+                if "conllu" in name and "fixed" not in name:
+                    output = path_to_str(treebank_file).replace('.conllu', '.fixed.conllu')
+                    if "train" in name:
+                        collapse_nodes(data_dir, treebank_file, output)
+                        train_paths.append(output)
+                    elif "dev" in name:
+                        collapse_nodes(data_dir, treebank_file, output)
+                        dev_paths.append(output)
+                    elif "test" in name:
+                        collapse_nodes(data_dir, treebank_file, output)
+                        test_paths.append(output)
+
+        lang_data_dir = pathlib.Path(data_dir / lang)
+        lang_data_dir.mkdir(exist_ok=True)
+
+        train_path = lang_data_dir / "train.conllu"
+        dev_path = lang_data_dir / "dev.conllu"
+        test_path = lang_data_dir / "test.conllu"
+
+        merge_files(train_paths, output=train_path)
+        merge_files(dev_paths, output=dev_path)
+        merge_files(test_paths, output=test_path)
+
+        serialization_dir = pathlib.Path(FLAGS.serialization_dir) / lang
+        serialization_dir.mkdir(exist_ok=True)
+        execute_command("".join(f"""combo --mode train
+        --training_data {train_path}
+        --validation_data {dev_path}
+        --targets feats,upostag,xpostag,head,deprel,lemma,deps
+        --pretrained_transformer_name {LANG2TRANSFORMER[lang]}
+        --serialization_dir {serialization_dir}
+        --cuda_device {FLAGS.cuda_device}
+        --word_batch_size 2500
+        --config_path {pathlib.Path.cwd() / 'config.graph.template.jsonnet'}
+        --tensorboard
+        """.splitlines()))
+
+
+def main():
+    app.run(run)
+
+
+if __name__ == "__main__":
+    main()