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[T5 and Llama Tokenizer] remove warning #29346

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merged 3 commits into from
Feb 28, 2024
Merged

[T5 and Llama Tokenizer] remove warning #29346

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fd11654
remove warning
ArthurZucker Feb 28, 2024
6e61bca
add co-author
hiaoxui Feb 28, 2024
19a4cb0
update
ArthurZucker Feb 28, 2024
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4 changes: 2 additions & 2 deletions src/transformers/models/llama/tokenization_llama.py
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Original file line number Diff line number Diff line change
Expand Up @@ -243,7 +243,7 @@ def get_vocab(self):
return vocab

# Copied from transformers.models.t5.tokenization_t5.T5Tokenizer.tokenize
def tokenize(self, text: "TextInput", add_special_tokens=False, **kwargs) -> List[str]:
def tokenize(self, text: "TextInput", **kwargs) -> List[str]:
"""
Converts a string to a list of tokens. If `self.legacy` is set to `False`, a prefix token is added unless the
first token is special.
Expand All @@ -255,7 +255,7 @@ def tokenize(self, text: "TextInput", add_special_tokens=False, **kwargs) -> Lis
if self.add_prefix_space:
text = SPIECE_UNDERLINE + text

tokens = super().tokenize(text, add_special_tokens=add_special_tokens, **kwargs)
tokens = super().tokenize(text, **kwargs)

if len(tokens) > 1 and tokens[0] == SPIECE_UNDERLINE and tokens[1] in self.all_special_tokens:
tokens = tokens[1:]
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4 changes: 2 additions & 2 deletions src/transformers/models/seamless_m4t/tokenization_seamless_m4t.py
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Expand Up @@ -447,7 +447,7 @@ def get_spm_processor(self, from_slow=False):
return tokenizer

# Copied from transformers.models.t5.tokenization_t5.T5Tokenizer.tokenize
def tokenize(self, text: "TextInput", add_special_tokens=False, **kwargs) -> List[str]:
def tokenize(self, text: "TextInput", **kwargs) -> List[str]:
"""
Converts a string to a list of tokens. If `self.legacy` is set to `False`, a prefix token is added unless the
first token is special.
Expand All @@ -459,7 +459,7 @@ def tokenize(self, text: "TextInput", add_special_tokens=False, **kwargs) -> Lis
if self.add_prefix_space:
text = SPIECE_UNDERLINE + text

tokens = super().tokenize(text, add_special_tokens=add_special_tokens, **kwargs)
tokens = super().tokenize(text, **kwargs)

if len(tokens) > 1 and tokens[0] == SPIECE_UNDERLINE and tokens[1] in self.all_special_tokens:
tokens = tokens[1:]
Expand Down
4 changes: 2 additions & 2 deletions src/transformers/models/t5/tokenization_t5.py
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Original file line number Diff line number Diff line change
Expand Up @@ -377,7 +377,7 @@ def __setstate__(self, d):
self.sp_model = spm.SentencePieceProcessor(**self.sp_model_kwargs)
self.sp_model.Load(self.vocab_file)

def tokenize(self, text: "TextInput", add_special_tokens=False, **kwargs) -> List[str]:
def tokenize(self, text: "TextInput", **kwargs) -> List[str]:
"""
Converts a string to a list of tokens. If `self.legacy` is set to `False`, a prefix token is added unless the
first token is special.
Expand All @@ -389,7 +389,7 @@ def tokenize(self, text: "TextInput", add_special_tokens=False, **kwargs) -> Lis
if self.add_prefix_space:
text = SPIECE_UNDERLINE + text

tokens = super().tokenize(text, add_special_tokens=add_special_tokens, **kwargs)
tokens = super().tokenize(text, **kwargs)

if len(tokens) > 1 and tokens[0] == SPIECE_UNDERLINE and tokens[1] in self.all_special_tokens:
tokens = tokens[1:]
Expand Down
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