"""
This module supplies `transformers`-compatible wrappers for
`GPTXTokenizer`s.

The tokenizers in this do not conform to the `PreTrainedTokenizer` API,
but allow for better practical usage.
"""

from typing import List

try:
    from gptxdata.tokenization.hf_wrappers import (
        HFTokenizer as _HFTokenizer,
        SPTokenizer as _SPTokenizer,
)
except ImportError:
    from gptx_tokenizer.hf_wrappers import (
        HFTokenizer as _HFTokenizer,
        SPTokenizer as _SPTokenizer,
)

class HFTokenizer(_HFTokenizer):
    # The tokenizer is ridiculously slow without this; however, this
    # doesn't implement all APIs of `PreTrainedTokenizer`.
    def encode(self, text: str, **kwargs) -> List[int]:
        return_tokens = kwargs.pop('return_tokens', False)
        return self._tok.encode(text, return_tokens=return_tokens)


class SPTokenizer(_SPTokenizer):
    # `is_continuation` does not work without this, but it doesn't
    # implement all APIs of `PreTrainedTokenizer`.
    def encode(self, text: str, **kwargs) -> List[int]:
        return_tokens = kwargs.pop('return_tokens', False)
        is_continuation = kwargs.pop('is_continuation', False)
        return self._tok.encode(
            text,
            return_tokens=return_tokens,
            is_continuation=is_continuation,
        )