code: def test_backofff_ngram_lm():
      from speechbrain.lm.ngram import BackoffNgramLM
      import math
  
      HALF = math.log(0.5)
      ngrams = {
          1: {tuple(): {"a": HALF, "b": HALF}},
          2: {("a",): {"a": HALF, "b": HALF}, ("b",): {"a": HALF}},
      }
      backoffs = {1: {("b",): 0.0}}
      lm = BackoffNgramLM(ngrams, backoffs)
      # The basic cases covered by the ngrams and backoffs:
      assert lm.logprob("a", ()) == HALF
      assert lm.logprob("b", ()) == HALF
      assert lm.logprob("a", ("a",)) == HALF
      assert lm.logprob("a", ("b",)) == HALF
      assert lm.logprob("b", ("a",)) == HALF
      assert lm.logprob("b", ("b",)) == HALF
      # Edge cases
      # Too large context:
      assert lm.logprob("a", ("a", "a")) == HALF
      assert lm.logprob("b", ("a", "b")) == HALF
      # OOV:
      assert lm.logprob("c", ()) == float("-inf")
      # OOV in context:
      assert lm.logprob("a", ("c",)) == HALF
  
label_desc: Use image node_id 1 for calling a global function with example usage: test_backofff_ngram_lm() without return types