public/gpt-2/transformers/utils/dummy_sentencepiece_objects.py

# This file is autogenerated by the command `make fix-copies`, do not edit.
from ..file_utils import requires_backends


class AlbertTokenizer:
    def __init__(self, *args, **kwargs):
        requires_backends(self, ["sentencepiece"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["sentencepiece"])


class BarthezTokenizer:
    def __init__(self, *args, **kwargs):
        requires_backends(self, ["sentencepiece"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["sentencepiece"])


class BertGenerationTokenizer:
    def __init__(self, *args, **kwargs):
        requires_backends(self, ["sentencepiece"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["sentencepiece"])


class CamembertTokenizer:
    def __init__(self, *args, **kwargs):
        requires_backends(self, ["sentencepiece"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["sentencepiece"])


class DebertaV2Tokenizer:
    def __init__(self, *args, **kwargs):
        requires_backends(self, ["sentencepiece"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["sentencepiece"])


class M2M100Tokenizer:
    def __init__(self, *args, **kwargs):
        requires_backends(self, ["sentencepiece"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["sentencepiece"])


class MarianTokenizer:
    def __init__(self, *args, **kwargs):
        requires_backends(self, ["sentencepiece"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["sentencepiece"])


class MBart50Tokenizer:
    def __init__(self, *args, **kwargs):
        requires_backends(self, ["sentencepiece"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["sentencepiece"])


class MBartTokenizer:
    def __init__(self, *args, **kwargs):
        requires_backends(self, ["sentencepiece"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["sentencepiece"])


class MT5Tokenizer:
    def __init__(self, *args, **kwargs):
        requires_backends(self, ["sentencepiece"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["sentencepiece"])


class PegasusTokenizer:
    def __init__(self, *args, **kwargs):
        requires_backends(self, ["sentencepiece"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["sentencepiece"])


class ReformerTokenizer:
    def __init__(self, *args, **kwargs):
        requires_backends(self, ["sentencepiece"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["sentencepiece"])


class Speech2TextTokenizer:
    def __init__(self, *args, **kwargs):
        requires_backends(self, ["sentencepiece"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["sentencepiece"])


class T5Tokenizer:
    def __init__(self, *args, **kwargs):
        requires_backends(self, ["sentencepiece"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["sentencepiece"])


class XLMProphetNetTokenizer:
    def __init__(self, *args, **kwargs):
        requires_backends(self, ["sentencepiece"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["sentencepiece"])


class XLMRobertaTokenizer:
    def __init__(self, *args, **kwargs):
        requires_backends(self, ["sentencepiece"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["sentencepiece"])


class XLNetTokenizer:
    def __init__(self, *args, **kwargs):
        requires_backends(self, ["sentencepiece"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["sentencepiece"])