code: def _slot_matching_lambda(lhs_slot, rhs_slot):
      lhs_value = lhs_slot["text"]
      rhs_value = rhs_slot["rawValue"]
      if lhs_slot["entity"] != "snips/datetime":
          return lhs_value == rhs_value
      else:
          # Allow fuzzy matching when comparing datetimes
          lhs_tokens = tokenize_light(lhs_value, LANGUAGE_EN)
          rhs_tokens = tokenize_light(rhs_value, LANGUAGE_EN)
          if (
              lhs_tokens
              and lhs_tokens[0].lower() in SKIPPED_DATE_PREFIXES
          ):
              lhs_tokens = lhs_tokens[1:]
          if (
              rhs_tokens
              and rhs_tokens[0].lower() in SKIPPED_DATE_PREFIXES
          ):
              rhs_tokens = rhs_tokens[1:]
          return lhs_tokens == rhs_tokens
  
file_path: snips-nlu/snips_nlu/tests/integration_test.py
imports: from __future__ import print_function, unicode_literals
  from builtins import str
  from future.utils import iteritems
  from snips_nlu_metrics import compute_cross_val_metrics
  from snips_nlu.constants import LANGUAGE_EN
  from snips_nlu.nlu_engine.nlu_engine import SnipsNLUEngine
  from snips_nlu.preprocessing import tokenize_light
  from snips_nlu.tests.utils import PERFORMANCE_DATASET_PATH, SnipsTest
label_desc: Use image node_id 1 for calling a global function with example usage: _slot_matching_lambda(lhs_slot, rhs_slot) and returns: unknown, unknown