How to use the awswrangler.exceptions.UnsupportedType function in awswrangler

if dtype == "int32":
        return "INTEGER"
    elif dtype == "int64":
        return "BIGINT"
    elif dtype == "float32":
        return "FLOAT4"
    elif dtype == "float64":
        return "FLOAT8"
    elif dtype == "bool":
        return "BOOLEAN"
    elif dtype == "object" and isinstance(dtype, str):
        return "VARCHAR(256)"
    elif dtype[:10] == "datetime64":
        return "TIMESTAMP"
    else:
        raise UnsupportedType("Unsupported Pandas type: " + dtype)

elif dtype == "float":
        return "FLOAT4"
    elif dtype == "double":
        return "FLOAT8"
    elif dtype in ("bool", "boolean"):
        return "BOOLEAN"
    elif dtype == "timestamp":
        return "TIMESTAMP"
    elif dtype == "date":
        return "DATE"
    elif dtype == "string":
        return "VARCHAR(256)"
    elif dtype.startswith("decimal"):
        return dtype.replace(" ", "").upper()
    else:
        raise UnsupportedType("Unsupported Spark type: " + dtype)

if dtype == "int32":
        return "int"
    elif dtype == "int64":
        return "bigint"
    elif dtype == "float32":
        return "float"
    elif dtype == "float64":
        return "double"
    elif dtype == "bool":
        return "boolean"
    elif dtype == "object" and isinstance(dtype, str):
        return "string"
    elif dtype[:10] == "datetime64":
        return "string"
    else:
        raise UnsupportedType("Unsupported Pandas type: " + dtype)

elif dtype in ("float", "double", "real"):
        return "float64"
    elif dtype == "boolean":
        return "bool"
    elif dtype in ("string", "char", "varchar"):
        return "str"
    elif dtype in ("timestamp", "timestamp with time zone"):
        return "datetime64"
    elif dtype == "date":
        return "date"
    elif dtype == "array":
        return "list"
    elif dtype == "decimal":
        return "decimal"
    else:
        raise UnsupportedType(f"Unsupported Athena type: {dtype}")

partition_cols_types = {}
        for name, dtype in pyarrow_schema:
            if (cast_columns is not None) and (name in cast_columns.keys()):
                if name in partition_cols:
                    partition_cols_types[name] = cast_columns[name]
                else:
                    schema_built.append((name, cast_columns[name]))
            else:
                try:
                    athena_type = data_types.pyarrow2athena(dtype)
                except UndetectedType:
                    raise UndetectedType(f"We can't infer the data type from an entire null object column ({name}). "
                                         f"Please consider pass the type of this column explicitly using the cast "
                                         f"columns argument")
                except UnsupportedType:
                    raise UnsupportedType(f"Unsupported Pyarrow type for column {name}: {dtype}")
                if name in partition_cols:
                    partition_cols_types[name] = athena_type
                else:
                    schema_built.append((name, athena_type))

        partition_cols_schema_built = [(name, partition_cols_types[name]) for name in partition_cols]

        logger.debug(f"schema_built:\n{schema_built}")
        logger.debug(f"partition_cols_schema_built:\n{partition_cols_schema_built}")
        return schema_built, partition_cols_schema_built

elif dtype_str in ("BIGINT", "INT8"):
        return "bigint"
    elif dtype_str in ("REAL", "FLOAT4"):
        return "float"
    elif dtype_str in ("DOUBLE PRECISION", "FLOAT8", "FLOAT"):
        return "double"
    elif dtype_str in ("BOOLEAN", "BOOL"):
        return "boolean"
    elif dtype_str in ("VARCHAR", "CHARACTER VARYING", "NVARCHAR", "TEXT"):
        return "string"
    elif dtype_str == "DATE":
        return "date"
    elif dtype_str == "TIMESTAMP":
        return "timestamp"
    else:
        raise UnsupportedType(f"Unsupported Redshift type: {dtype_str}")

elif dtype == "bigint":
        return "int64"
    elif dtype == "float":
        return "float32"
    elif dtype == "double":
        return "float64"
    elif dtype in ("boolean", "bool"):
        return "bool"
    elif dtype in ("string", "char", "varchar", "array", "row", "map"):
        return "string"
    elif dtype == "timestamp":
        return "timestamp[ns]"
    elif dtype == "date":
        return "date32"
    else:
        raise UnsupportedType(f"Unsupported Athena type: {dtype}")

if dtype == "int32":
        return "int"
    elif dtype in ("int64", "Int64"):
        return "bigint"
    elif dtype == "float32":
        return "float"
    elif dtype == "float64":
        return "double"
    elif dtype == "bool":
        return "boolean"
    elif dtype == "object":
        return "string"
    elif dtype.startswith("datetime64"):
        return "timestamp"
    else:
        raise UnsupportedType(f"Unsupported Pandas type: {dtype}")