code: def __init__(self, width, oscillate):
      super(_NeuralF, self).__init__()
      self.linears = torch.nn.Sequential(
          torch.nn.Linear(2, width),
          torch.nn.Tanh(),
          torch.nn.Linear(width, 2),
          torch.nn.Tanh(),
      )
      self.nfe = 0
      self.oscillate = oscillate
  
imports: from functools import partial
  import unittest
  import warnings
  import torch
  import torchdiffeq
  from problems import construct_problem, PROBLEMS, DTYPES, DEVICES, METHODS, ADAPTIVE_METHODS, FIXED_METHODS, SCIPY_METHODS
label_desc: Use image node_id 1 to create a new _NeuralF object from inherited base classes: torch.nn with example: obj = _NeuralF(width, oscillate)