fasttext_jp_embedding.py

from __future__ import annotations
from transformers import PretrainedConfig
from transformers import PreTrainedModel
from torch import nn
import torch


class FastTextJpConfig(PretrainedConfig):
    model_type = "fast_text_jp"

    def __init__(self, **kwargs):
        super().__init__(**kwargs)


class FastTextJpModel(PreTrainedModel):
    """FastTextのEmbeddingを行います。
    """
    config_class = FastTextJpConfig

    def __init__(self, config: FastTextJpConfig):
        super().__init__(config)
        self.word_embeddings = nn.Embedding(config.vocab_size,
                                            config.hidden_size)

    def forward(self, input_ids, **kwargs):
        return self.word_embeddings(torch.tensor([0]))


FastTextJpConfig.register_for_auto_class()
FastTextJpModel.register_for_auto_class("AutoModel")