[seq2seq] pack_dataset.py rewrites dataset in max_tokens format (#5819)
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"""Fill examples with bitext up to max_tokens without breaking up examples.
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[['I went', 'yo fui'],
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['to the store', 'a la tienda']
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]
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=> ['I went to the store', 'yo fui a la tienda']
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"""
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import argparse
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from pathlib import Path
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from tqdm import tqdm
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from transformers import AutoTokenizer
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def pack_examples(tok, src_examples, tgt_examples, max_tokens=1024):
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finished_src, finished_tgt = [], []
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new_src, new_tgt = "", ""
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sorted_examples = list(sorted(zip(src_examples, tgt_examples), key=lambda x: len(x[0])))
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def is_too_big(strang):
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return tok(strang, return_tensors="pt").input_ids.shape[1] > max_tokens
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for src, tgt in tqdm(sorted_examples):
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cand_src = new_src + " " + src
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cand_tgt = new_tgt + " " + tgt
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if is_too_big(cand_src) or is_too_big(cand_tgt): # cant fit, finalize example
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finished_src.append(new_src)
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finished_tgt.append(new_tgt)
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new_src, new_tgt = src, tgt
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else: # can fit, keep adding
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new_src, new_tgt = cand_src, cand_tgt
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return finished_src, finished_tgt
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def pack_data_dir(tok, data_dir: Path, max_tokens, save_path):
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save_path = Path(save_path)
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save_path.mkdir(exist_ok=True)
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for split in ["val", "test", "train"]:
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src_path, tgt_path = data_dir / f"{split}.source", data_dir / f"{split}.target"
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src_docs = list(Path(src_path).open().readlines())
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tgt_docs = list(Path(tgt_path).open().readlines())
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src, tgt = pack_examples(tok, src_docs, tgt_docs, max_tokens)
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print(f"packed {split} split from {len(src_docs)} examples -> {len(src)}.")
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Path(save_path / f"{split}.source").open("w").write("\n".join(src))
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Path(save_path / f"{split}.target").open("w").write("\n".join(tgt))
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def packer_cli():
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parser = argparse.ArgumentParser()
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parser.add_argument("--tok_name", type=str, help="like facebook/bart-large-cnn,t5-base, etc.")
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parser.add_argument("--max_seq_len", type=int, default=128)
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parser.add_argument("--data_dir", type=str)
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parser.add_argument("--save_path", type=str)
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args = parser.parse_args()
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tokenizer = AutoTokenizer.from_pretrained(args.tok_name)
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return pack_data_dir(tokenizer, Path(args.data_dir), args.max_seq_len, args.save_path)
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if __name__ == "__main__":
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packer_cli()
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@ -16,6 +16,7 @@ from transformers.testing_utils import require_multigpu
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from .distillation import distill_main, evaluate_checkpoint
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from .finetune import main
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from .pack_dataset import pack_data_dir
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from .run_eval import generate_summaries_or_translations, run_generate
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from .utils import SummarizationDataset, lmap, load_json
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@ -249,6 +250,16 @@ def test_finetune(model):
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assert bart.decoder.embed_tokens == bart.shared
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def test_pack_dataset():
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tokenizer = AutoTokenizer.from_pretrained("facebook/mbart-large-cc25")
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tmp_dir = Path(make_test_data_dir())
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save_dir = Path(tempfile.mkdtemp(prefix="packed_"))
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pack_data_dir(tokenizer, tmp_dir, 128, save_dir)
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orig_paths = {x.name for x in tmp_dir.iterdir()}
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new_paths = {x.name for x in save_dir.iterdir()}
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assert orig_paths == new_paths
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@pytest.mark.parametrize(
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["tok"], [pytest.param(T5_TINY), pytest.param(BART_TINY), pytest.param(MBART_TINY), pytest.param(MARIAN_TINY)]
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)
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