code: def __init__(self, model_path):
      self.model = load_model(model_path)
      input_matrix = self.model.get_input_matrix()
      input_matrix_shape = input_matrix.shape
      super().__init__(input_matrix_shape[0], input_matrix_shape[1])
      self.weight.data.copy_(torch.FloatTensor(input_matrix))
  
file_path: fastText/python/doc/examples/FastTextEmbeddingBag.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from __future__ import unicode_literals
  from torch.nn.modules.sparse import EmbeddingBag
  import numpy
  import torch
  import random
  import string
  import time
  from fasttext import load_model
  from torch.autograd import Variable
label_desc: Use image node_id 1 to create a new FastTextEmbeddingBag object from inherited base classes: EmbeddingBag with example: obj = FastTextEmbeddingBag(model_path)