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def _check_mixed_float(df, dtype=None): # float16 are most likely to be upcasted to float32 dtypes = dict(A="float32", B="float32", C="float16", D="float64") if isinstance(dtype, str): dtypes = {k: dtype for k, v in dtypes.items()} elif isinstance(dtype, dict): dtypes.update(dtype) if dtypes.get("A"): assert df.dtypes["A"] == dtypes["A"] if dtypes.get("B"): assert df.dtypes["B"] == dtypes["B"] if dtypes.get("C"): assert df.dtypes["C"] == dtypes["C"] if dtypes.get("D"): assert df.dtypes["D"] == dtypes["D"] def _check_mixed_int(df, dtype=None): dtypes = dict(A="int32", B="uint64", C="uint8", D="int64") if isinstance(dtype, str): dtypes = {k: dtype for k, v in dtypes.items()} elif isinstance(dtype, dict): dtypes.update(dtype) if dtypes.get("A"): assert df.dtypes["A"] == dtypes["A"] if dtypes.get("B"): assert df.dtypes["B"] == dtypes["B"] if dtypes.get("C"): assert df.dtypes["C"] == dtypes["C"] if dtypes.get("D"): assert df.dtypes["D"] == dtypes["D"]
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