code: def generate_data(
      num_ts, ctx=mx.gpu(), dtype="float64", seed=100
  ):  # num_ts = d
      np.random.seed(seed)
      # vector of shape (num_ts, )
      r = np.random.rand(num_ts)
      # vector of shape (num_ts, )
      k = np.random.rand(num_ts)
      # matrix of shape (num_ts, num_ts)
      A = np.random.rand(num_ts, num_ts)
      # diagonal entries are 1 representing intraspecies competition
      np.fill_diagonal(A, 1)
      # initial condition vector of shape (num_ts, )
      p0 = np.random.rand(num_ts)
      return (
          nd.array(r, ctx=ctx, dtype=dtype),
          nd.array(k, ctx=ctx, dtype=dtype),
          nd.array(p0, ctx=ctx, dtype=dtype),
          nd.array(A, ctx=ctx, dtype=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 5 for calling a global function with example usage: generate_data(num_ts, ctx, dtype, seed) and returns: nd,  nd,  nd,  nd