docstr: Initializing the trainer with the input arguments
docstr_tok: ["Initializing","the","trainer","with","the","input","arguments"]
code: def __init__(self, args):
      """Initializing the trainer with the input arguments"""
      self.args = args
      self.dataset = DeepwalkDataset(
          net_file=args.data_file,
          map_file=args.map_file,
          walk_length=args.walk_length,
          window_size=args.window_size,
          num_walks=args.num_walks,
          batch_size=args.batch_size,
          negative=args.negative,
          gpus=args.gpus,
          fast_neg=args.fast_neg,
          ogbl_name=args.ogbl_name,
          load_from_ogbl=args.load_from_ogbl,
      )
      self.emb_size = self.dataset.G.num_nodes()
      self.emb_model = None
  
file_path: dgl/examples/pytorch/ogb/deepwalk/deepwalk.py
imports: import argparse
  import os
  import random
  import time
  import dgl
  import numpy
  import torch
  import torch.multiprocessing
  from model import SkipGramModel
  from reading_data import DeepwalkDataset
  from torch.utils.data import DataLoader
  from utils import shuffle_walks, sum_up_params
label_desc: Use image node_id 1 to create a new DeepwalkTrainer object  with example: obj = DeepwalkTrainer(args)