code: def test_check_array_pandas_dtype_object_conversion():
      # test that data-frame like objects with dtype object
      # get converted
      X = mt.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]], dtype=mt.object)
      X_df = MockDataFrame(X)
      assert check_array(X_df).dtype.kind == "f"
      assert check_array(X_df, ensure_2d=False).dtype.kind == "f"
      # smoke-test against dataframes with column named "dtype"
      X_df.dtype = "Hans"
      assert check_array(X_df, ensure_2d=False).dtype.kind == "f"
  
imports: from itertools import product
  import numpy
  import pytest
  import scipy.sparse
  from sklearn.utils.estimator_checks import _NotAnArray
  from sklearn.utils._mocking import MockDataFrame
  from sklearn.utils._testing import assert_raise_message, assert_raises_regex
  from ....None import tensor
  from ....None import dataframe
  from ....tensor.core import Tensor
  from ..validation import check_array, check_consistent_length
label_desc: Use image node_id 3 for calling a global function with example usage: test_check_array_pandas_dtype_object_conversion() without return types