feldman_verifiable_sum_param¶
feldman_verifiable_sum_param
¶
Classes¶
FeldmanVerifiableSumParam (BaseParam)
¶
Define how to transfer the cols
Parameters:
Name | Type | Description | Default |
---|---|---|---|
sum_cols |
list of column index, default: None |
Specify which columns need to be sum. If column index is None, each of columns will be sum. |
None |
q_n |
int, positive integer less than or equal to 16, default: 6 |
q_n is the number of significant decimal digit, If the data type is a float, the maximum significant digit is 16. The sum of integer and significant decimal digits should be less than or equal to 16. |
6 |
Source code in federatedml/param/feldman_verifiable_sum_param.py
class FeldmanVerifiableSumParam(BaseParam):
"""
Define how to transfer the cols
Parameters
----------
sum_cols : list of column index, default: None
Specify which columns need to be sum. If column index is None, each of columns will be sum.
q_n : int, positive integer less than or equal to 16, default: 6
q_n is the number of significant decimal digit, If the data type is a float,
the maximum significant digit is 16. The sum of integer and significant decimal digits should
be less than or equal to 16.
"""
def __init__(self, sum_cols=None, q_n=6):
self.sum_cols = sum_cols
if sum_cols is None:
self.sum_cols = []
self.q_n = q_n
def check(self):
if isinstance(self.sum_cols, list):
for idx in self.sum_cols:
if not isinstance(idx, int):
raise ValueError(f"type mismatch, column_indexes with element {idx}(type is {type(idx)})")
if not isinstance(self.q_n, int):
raise ValueError(f"Init param's q_n {self.q_n} not supported, should be int type", type is {type(self.q_n)})
if self.q_n < 0:
raise ValueError(f"param's q_n {self.q_n} not supported, should be non-negative int value")
elif self.q_n > 16:
raise ValueError(f"param's q_n {self.q_n} not supported, should be less than or equal to 16")
__init__(self, sum_cols=None, q_n=6)
special
¶
Source code in federatedml/param/feldman_verifiable_sum_param.py
def __init__(self, sum_cols=None, q_n=6):
self.sum_cols = sum_cols
if sum_cols is None:
self.sum_cols = []
self.q_n = q_n
check(self)
¶
Source code in federatedml/param/feldman_verifiable_sum_param.py
def check(self):
if isinstance(self.sum_cols, list):
for idx in self.sum_cols:
if not isinstance(idx, int):
raise ValueError(f"type mismatch, column_indexes with element {idx}(type is {type(idx)})")
if not isinstance(self.q_n, int):
raise ValueError(f"Init param's q_n {self.q_n} not supported, should be int type", type is {type(self.q_n)})
if self.q_n < 0:
raise ValueError(f"param's q_n {self.q_n} not supported, should be non-negative int value")
elif self.q_n > 16:
raise ValueError(f"param's q_n {self.q_n} not supported, should be less than or equal to 16")
Last update: 2021-11-24