diff --git a/docs/training.md b/docs/training.md
index 7d7b0a8256e0c7896bf1372f817ab4e263b4f45e..2cdf75d0803e6ea12e5ce6343d8471579e90bf8c 100644
--- a/docs/training.md
+++ b/docs/training.md
@@ -51,6 +51,8 @@ Enhanced Dependencies are described [here](https://universaldependencies.org/u/o
### Data pre-processing
The organisers of [IWPT20 shared task](https://universaldependencies.org/iwpt20/data.html) distributed the data sets and a data pre-processing script `enhanced_collapse_empty_nodes.pl`. If you wish to train a model on IWPT20 data, apply this script to the training and validation data sets, before training the COMBO EUD model.
+The script is part of the [UD tools repository](https://github.com/UniversalDependencies/tools/).
+
```bash
perl enhanced_collapse_empty_nodes.pl training.conllu > training.fixed.conllu
```
diff --git a/scripts/train_iwpt21.py b/scripts/train_iwpt21.py
new file mode 100644
index 0000000000000000000000000000000000000000..5082f9dc7709bb8a2b3565c077e0f24279d27f0e
--- /dev/null
+++ b/scripts/train_iwpt21.py
@@ -0,0 +1,134 @@
+"""Script to train Enhanced Dependency Parsing models based on IWPT'21 Shared Task data.
+
+For possible requirements, see train_eud.py comments.
+"""
+
+import os
+import pathlib
+from typing import List
+
+from absl import app
+from absl import flags
+
+from scripts import utils
+
+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", "UD_English-GUM"],
+ "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"],
+}
+
+FLAGS = flags.FLAGS
+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 collapse_nodes(data_dir: pathlib.Path, treebank_file: pathlib.Path, output: str):
+ output_path = pathlib.Path(output)
+ if not output_path.exists():
+ utils.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())}."
+ assert lang in utils.LANG2TRANSFORMER, f"Transformer for '{lang}' isn't defined. See 'LANG2TRANSFORMER' dict."
+ 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 = []
+
+ # TODO Uncomment when IWPT'21 Shared Task ends.
+ # During shared task duration test data is not available.
+ 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"
+ # TODO Uncomment
+ # test_path = lang_data_dir / "test.conllu"
+
+ merge_files(train_paths, output=train_path)
+ merge_files(dev_paths, output=dev_path)
+ # TODO Uncomment
+ # merge_files(test_paths, output=test_path)
+
+ serialization_dir = pathlib.Path(FLAGS.serialization_dir) / lang
+ serialization_dir.mkdir(exist_ok=True, parents=True)
+
+ command = f"""combo --mode train
+ --training_data {train_path}
+ --validation_data {dev_path}
+ --targets feats,upostag,xpostag,head,deprel,lemma,deps
+ --pretrained_transformer_name {utils.LANG2TRANSFORMER[lang]}
+ --serialization_dir {serialization_dir}
+ --cuda_device {FLAGS.cuda_device}
+ --word_batch_size 2500
+ --config_path {pathlib.Path.cwd() / 'config.graph.template.jsonnet'}
+ --notensorboard
+ """
+
+ # Datasets without XPOS
+ if lang in {"fr"}:
+ command = command + " --targets deprel,head,upostag,lemma,feats"
+
+ utils.execute_command("".join(command.splitlines()))
+
+
+def main():
+ app.run(run)
+
+
+if __name__ == "__main__":
+ main()