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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def get_field(self, field_name):
 """Get property from the Dataset. Parameters field_name : string The field name of the information. Returns ------- info : numpy array A numpy array with information from the Dataset. """

        if self.handle is None:
            raise Exception("Cannot get %s before construct Dataset" % field_name)
        tmp_out_len = ctypes.c_int()
        out_type = ctypes.c_int()
        ret = ctypes.POINTER(ctypes.c_void_p)()
        _safe_call(_LIB.LGBM_DatasetGetField(
            self.handle,
            c_str(field_name),
            ctypes.byref(tmp_out_len),
            ctypes.byref(ret),
            ctypes.byref(out_type)))
        if out_type.value != FIELD_TYPE_MAPPER[field_name]:
            raise TypeError("Return type error for get_field")
        if tmp_out_len.value == 0:
            return None
        if out_type.value == C_API_DTYPE_INT32:
            return cint32_array_to_numpy(ctypes.cast(ret, ctypes.POINTER(ctypes.c_int32)), tmp_out_len.value)
        elif out_type.value == C_API_DTYPE_FLOAT32:
            return cfloat32_array_to_numpy(ctypes.cast(ret, ctypes.POINTER(ctypes.c_float)), tmp_out_len.value)
        elif out_type.value == C_API_DTYPE_FLOAT64:
            return cfloat64_array_to_numpy(ctypes.cast(ret, ctypes.POINTER(ctypes.c_double)), tmp_out_len.value)
        elif out_type.value == C_API_DTYPE_INT8:
            return cint8_array_to_numpy(ctypes.cast(ret, ctypes.POINTER(ctypes.c_int8)), tmp_out_len.value)
        else:
            raise TypeError("Unknown type")