configuration_vqvae.py

from transformers import PretrainedConfig
from typing import List


class VQVAEConfig(PretrainedConfig):
    model_type = "VQVAE"

    def __init__(
        self,
        embedding_dim: int = 256,
        n_codes: int = 2048,
        n_hiddens: int = 240,
        n_res_layers: int = 4,
        downsample: List[int] = [2, 4, 4],
        **kwargs,
    ):
        self.embedding_dim = embedding_dim
        self.n_codes = n_codes
        self.n_hiddens = n_hiddens
        self.n_res_layers = n_res_layers
        self.downsample = downsample
        super().__init__(**kwargs)