def __init__(self, num_vertices: int, embed_dim: int):
        """
        Initialize embedder, set random embeddings

        Args:
            num_vertices (int): number of vertices to embed
            embed_dim (int): number of dimensions in the embedding space
        """
        super(VertexDirectEmbedder, self).__init__()
        self.embeddings = nn.Parameter(torch.Tensor(num_vertices, embed_dim))
        self.reset_parameters()

        Initialize embedder, set random embeddings

        Args:
            num_vertices (int): number of vertices to embed
            embed_dim (int): number of dimensions in the embedding space
        
EVA-02/det/projects/DensePose/densepose/modeling/cse/vertex_direct_embedder.py