code: def _is_exact_wolfe(x, f_x, df_x, f_0, df_0, delta, sigma):
      decrease_cond = f_x <= f_0 + delta * x * df_0
      curvature_cond = df_x >= sigma * df_0
      return decrease_cond & curvature_cond
  
imports: import collections
  from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.optimizer.linesearch.hager_zhang import hager_zhang
label_desc: Use image node_id 1 for calling a global function with example usage: _is_exact_wolfe(x, f_x, df_x, f_0, df_0, delta, sigma) and returns: unknown