code: def __init__(self, data_num=1000, feature_dimension=10, seed=0):
      self.num_labels = feature_dimension
      self.feature_dimension = feature_dimension
      self.data_num = data_num
      self.seed = seed
  
      g = oneflow.Generator()
      g.manual_seed(1000)
      self.x = oneflow.randint(
          low=-100,
          high=100,
          size=[data_num, feature_dimension],
          generator=g,
      ).float()
      self.y = oneflow.max(self.x, dim=-1)[1]
  
file_path: fastNLP/tests/helpers/datasets/oneflow_data.py
imports: from fastNLP.envs.imports import _NEED_IMPORT_ONEFLOW
label_desc: Use image node_id 1 to create a new OneflowArgMaxDataset object from inherited base classes: Dataset with example: obj = OneflowArgMaxDataset(data_num, feature_dimension, seed)