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"]
docstr: Check that weighted data raises a TypeError
docstr_tok: ["Check","that","weighted","data","raises","a","TypeError"]
code: def test_simple_weighted(self):
      """
      Check that weighted data raises a TypeError
      """
      estimator_list = ["fd", "scott", "rice", "sturges", "auto"]
      for estimator in estimator_list:
          assert_raises(
              TypeError,
              histogram,
              [1, 2, 3],
              estimator,
              weights=[1, 2, 3],
          )
  
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 11 for calling the TestHistogramOptimBinNums obj's underlying member method code with example usage: obj.test_simple_weighted() without return types