class_docstr: Implemetation of skipgram model.
  
  Args:
      config: dict, some configure parameters.
      dataset: instance of Dataset class
      place: GPU or CPU place
class_docstr_tok: ["Implemetation","of","skipgram","model",".","Args",":","config",":","dict",",","some","configure","parameters",".","dataset",":","instance","of","Dataset","class","place",":","GPU","or","CPU","place"]
code: def __init__(self, config, dataset, place):
      self.config = config
      self.dataset = dataset
      self.place = place
      self.neg_num = self.dataset.config["neg_num"]
  
      self.num_nodes = len(dataset.word2id)
  
      self.train_inputs = fl.data(
          "train_inputs", shape=[None, 1, 1], dtype="int64"
      )
  
      self.train_labels = fl.data(
          "train_labels", shape=[None, 1, 1], dtype="int64"
      )
  
      self.train_negs = fl.data(
          "train_negs", shape=[None, self.neg_num, 1], dtype="int64"
      )
  
      self.forward()
  
file_path: PGL/legacy/examples/metapath2vec/model.py
imports: import argparse
  import time
  import math
  import os
  import io
  from multiprocessing import Pool
  import logging
  import numpy
  import glob
  import pgl
  from pgl import data_loader
  from pgl.utils import op
  from pgl.utils.logger import log
  import paddle.fluid
  import paddle.fluid.layers
label_desc: Use image node_id 1 to create a new SkipgramModel object from inherited base classes: object with example: obj = SkipgramModel(config, dataset, place)