code: def generate_data(input_shape):
      shape = (5000, *input_shape)
      d = np.random.normal(0, 2, shape)
      modify_entries = np.random.randint(0, 1, shape) < 0.05
      d[modify_entries] = d[modify_entries] * 5 + 10
      return np.clip(d, -32, 31)
  
file_path: hls4ml/test/pytest/test_softmax.py
imports: from pathlib import Path
  import numpy
  import pytest
  import tensorflow
  from sklearn.metrics import accuracy_score
  import hls4ml
label_desc: Use image node_id 1 for calling a global function with example usage: generate_data(input_shape) and returns: np