class_docstr: Provide test coverage when using provided estimators for optimal number of
  bins
class_docstr_tok: ["Provide","test","coverage","when","using","provided","estimators","for","optimal","number","of","bins"]
code: def test_empty(self):
      estimator_list = [
          "fd",
          "scott",
          "rice",
          "sturges",
          "doane",
          "sqrt",
          "auto",
          "stone",
      ]
      # check it can deal with empty data
      for estimator in estimator_list:
          a, b = histogram([], bins=estimator)
          assert_array_equal(a, np.array([0]))
          assert_array_equal(b, np.array([0, 1]))
  
imports: import functools
  from unittest import expectedFailure, skipIf
  from pytest import raises
  from torch.testing._internal.common_utils import instantiate_parametrized_tests, parametrize, run_tests, slowTest, TEST_WITH_TORCHDYNAMO, TestCase, xpassIfTorchDynamo
label_desc: Use image node_id 1 for calling the TestHistogramOptimBinNums obj's underlying member method code with example usage: obj.test_empty() without return types