code: def __init__(self, neural_lv, **kwargs):
      super().__init__(**kwargs)
      self.num_time_series = neural_lv.num_time_series  # num_ts
      self.low_rank_param = (
          neural_lv.low_rank_param
      )  # low rank parameter k
      self.is_full_matrix = neural_lv.is_full_matrix
      self.dtype = neural_lv.dtype
      self.ctx = neural_lv.ctx
      self.feat_static_cat = nd.arange(
          self.num_time_series, ctx=self.ctx, dtype=self.dtype
      )
      self.is_sym = neural_lv.is_sym
      self.neural_lv = neural_lv
  
      with self.name_scope():
          self.embedding_low_rank_mat_B = gluon.nn.Embedding(
              input_dim=self.num_time_series,
              output_dim=self.low_rank_param,
              dtype=self.dtype,
          )
          if not self.is_sym:
              self.embedding_low_rank_mat_C = gluon.nn.Embedding(
                  input_dim=self.num_time_series,
                  output_dim=self.low_rank_param,
                  dtype=self.dtype,
              )
  
file_path: gluonts/src/gluonts/nursery/auto_ode/auto_ode.py
imports: import numpy
  import matplotlib.pyplot
  import mxnet
  import mxnet.gluon.nn
  import mxnet.gluon.rnn
  from mxnet import gluon, nd, autograd
  from tqdm import tqdm_notebook
label_desc: Use image node_id 1 to create a new LowRankVectorEmbedding object from inherited base classes: gluon with example: obj = LowRankVectorEmbedding(neural_lv)