Python MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING.update 예제들

예제 #1

from transformers import CONFIG_MAPPING, MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING, MODEL_NAMES_MAPPING, TOKENIZER_MAPPING
from transformers.convert_slow_tokenizer import SLOW_TO_FAST_CONVERTERS, BertConverter
from transformers.models.auto.modeling_auto import auto_class_factory

from .modeling.layoutlmv2 import (
    LayoutLMv2Config,
    LayoutLMv2ForTokenClassification,
    LayoutLMv2Tokenizer,
    LayoutLMv2TokenizerFast,
)

CONFIG_MAPPING.update([("layoutlmv2", LayoutLMv2Config)])
MODEL_NAMES_MAPPING.update([("layoutlmv2", "LayoutLMv2")])
TOKENIZER_MAPPING.update([(LayoutLMv2Config, (LayoutLMv2Tokenizer,
                                              LayoutLMv2TokenizerFast))])
SLOW_TO_FAST_CONVERTERS.update({"LayoutLMv2Tokenizer": BertConverter})
MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING.update([
    (LayoutLMv2Config, LayoutLMv2ForTokenClassification)
])
AutoModelForTokenClassification = auto_class_factory(
    "AutoModelForTokenClassification",
    MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING,
    head_doc="token classification")

예제 #2

    MarkupLMTokenizer,
    MarkupLMForQuestionAnswering,
    MarkupLMForTokenClassification,
    MarkupLMTokenizerFast,
)

CONFIG_MAPPING.update(
    [
        ("markuplm", MarkupLMConfig),
    ]
)
MODEL_NAMES_MAPPING.update([("markuplm", "MarkupLM")])

TOKENIZER_MAPPING.update(
    [
        (MarkupLMConfig, (MarkupLMTokenizer, MarkupLMTokenizerFast)),
    ]
)

SLOW_TO_FAST_CONVERTERS.update(
    {"MarkupLMTokenizer": RobertaConverter}
)

MODEL_FOR_QUESTION_ANSWERING_MAPPING.update(
    [(MarkupLMConfig, MarkupLMForQuestionAnswering)]
)

MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING.update(
    [(MarkupLMConfig, MarkupLMForTokenClassification)]
)