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Add XLMR and RoBERTa transforms as factory functions #2102

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Mar 9, 2023
Merged

Add XLMR and RoBERTa transforms as factory functions #2102

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f4a7a87
Add XLMR and RoBERTa transforms as classes
joecummings Mar 8, 2023
498036c
Remove unused import
joecummings Mar 8, 2023
e35cb8e
Add roberta transform and xlmr transform as factory methods
joecummings Mar 9, 2023
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72 changes: 29 additions & 43 deletions torchtext/models/roberta/bundler.py
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Original file line number Diff line number Diff line change
Expand Up @@ -160,16 +160,35 @@ def encoderConf(self) -> RobertaEncoderConf:
return self._encoder_conf


XLMR_BASE_ENCODER = RobertaBundle(
_path=urljoin(_TEXT_BUCKET, "xlmr.base.encoder.pt"),
_encoder_conf=RobertaEncoderConf(vocab_size=250002),
transform=lambda: T.Sequential(
def xlmr_transform(truncate_length: int) -> Module:
"""Standard transform for XLMR models."""
return T.Sequential(
T.SentencePieceTokenizer(urljoin(_TEXT_BUCKET, "xlmr.sentencepiece.bpe.model")),
T.VocabTransform(load_state_dict_from_url(urljoin(_TEXT_BUCKET, "xlmr.vocab.pt"))),
T.Truncate(254),
T.Truncate(truncate_length),
T.AddToken(token=0, begin=True),
T.AddToken(token=2, begin=False),
),
)


def roberta_transform(truncate_length: int) -> Module:
"""Standard transform for RoBERTa models."""
return T.Sequential(
T.GPT2BPETokenizer(
encoder_json_path=urljoin(_TEXT_BUCKET, "gpt2_bpe_encoder.json"),
vocab_bpe_path=urljoin(_TEXT_BUCKET, "gpt2_bpe_vocab.bpe"),
),
T.VocabTransform(load_state_dict_from_url(urljoin(_TEXT_BUCKET, "roberta.vocab.pt"))),
T.Truncate(truncate_length),
T.AddToken(token=0, begin=True),
T.AddToken(token=2, begin=False),
)


XLMR_BASE_ENCODER = RobertaBundle(
_path=urljoin(_TEXT_BUCKET, "xlmr.base.encoder.pt"),
_encoder_conf=RobertaEncoderConf(vocab_size=250002),
transform=lambda: xlmr_transform(254),
)

XLMR_BASE_ENCODER.__doc__ = """
Expand All @@ -193,13 +212,7 @@ def encoderConf(self) -> RobertaEncoderConf:
_encoder_conf=RobertaEncoderConf(
vocab_size=250002, embedding_dim=1024, ffn_dimension=4096, num_attention_heads=16, num_encoder_layers=24
),
transform=lambda: T.Sequential(
T.SentencePieceTokenizer(urljoin(_TEXT_BUCKET, "xlmr.sentencepiece.bpe.model")),
T.VocabTransform(load_state_dict_from_url(urljoin(_TEXT_BUCKET, "xlmr.vocab.pt"))),
T.Truncate(510),
T.AddToken(token=0, begin=True),
T.AddToken(token=2, begin=False),
),
transform=lambda: xlmr_transform(510),
)

XLMR_LARGE_ENCODER.__doc__ = """
Expand All @@ -221,16 +234,7 @@ def encoderConf(self) -> RobertaEncoderConf:
ROBERTA_BASE_ENCODER = RobertaBundle(
_path=urljoin(_TEXT_BUCKET, "roberta.base.encoder.pt"),
_encoder_conf=RobertaEncoderConf(vocab_size=50265),
transform=lambda: T.Sequential(
T.GPT2BPETokenizer(
encoder_json_path=urljoin(_TEXT_BUCKET, "gpt2_bpe_encoder.json"),
vocab_bpe_path=urljoin(_TEXT_BUCKET, "gpt2_bpe_vocab.bpe"),
),
T.VocabTransform(load_state_dict_from_url(urljoin(_TEXT_BUCKET, "roberta.vocab.pt"))),
T.Truncate(254),
T.AddToken(token=0, begin=True),
T.AddToken(token=2, begin=False),
),
transform=lambda: roberta_transform(254),
)

ROBERTA_BASE_ENCODER.__doc__ = """
Expand Down Expand Up @@ -263,16 +267,7 @@ def encoderConf(self) -> RobertaEncoderConf:
num_attention_heads=16,
num_encoder_layers=24,
),
transform=lambda: T.Sequential(
T.GPT2BPETokenizer(
encoder_json_path=urljoin(_TEXT_BUCKET, "gpt2_bpe_encoder.json"),
vocab_bpe_path=urljoin(_TEXT_BUCKET, "gpt2_bpe_vocab.bpe"),
),
T.VocabTransform(load_state_dict_from_url(urljoin(_TEXT_BUCKET, "roberta.vocab.pt"))),
T.Truncate(510),
T.AddToken(token=0, begin=True),
T.AddToken(token=2, begin=False),
),
transform=lambda: roberta_transform(510),
)

ROBERTA_LARGE_ENCODER.__doc__ = """
Expand Down Expand Up @@ -302,16 +297,7 @@ def encoderConf(self) -> RobertaEncoderConf:
num_encoder_layers=6,
padding_idx=1,
),
transform=lambda: T.Sequential(
T.GPT2BPETokenizer(
encoder_json_path=urljoin(_TEXT_BUCKET, "gpt2_bpe_encoder.json"),
vocab_bpe_path=urljoin(_TEXT_BUCKET, "gpt2_bpe_vocab.bpe"),
),
T.VocabTransform(load_state_dict_from_url(urljoin(_TEXT_BUCKET, "roberta.vocab.pt"))),
T.Truncate(510),
T.AddToken(token=0, begin=True),
T.AddToken(token=2, begin=False),
),
transform=lambda: roberta_transform(510),
)

ROBERTA_DISTILLED_ENCODER.__doc__ = """
Expand Down