class_docstr: Helper class containing various parameters of fixed-point precision
  tensors.
class_docstr_tok: ["Helper","class","containing","various","parameters","of","fixed-point","precision","tensors","."]
code: def __init__(
      self,
      scaling_base: int,
      nbits: int,
      precision_integral: int,
      precision_fractional: int,
      matmul_threshold: int,
      truncation_gap: int,
      use_noninteractive_truncation: bool,
  ) -> None:
      self.scaling_base = scaling_base
      self.nbits = nbits
      self.precision_integral = precision_integral
      self.precision_fractional = precision_fractional
      self.matmul_threshold = matmul_threshold
      self.truncation_gap = truncation_gap
      self.use_noninteractive_truncation = use_noninteractive_truncation
  
file_path: tf-encrypted/tf_encrypted/tensor/fixed.py
imports: from __future__ import absolute_import
  from math import ceil
  from math import log2
  from .factory import AbstractFactory
label_desc: Use image node_id 1 to create a new FixedpointConfig object  with example: obj = FixedpointConfig(scaling_base, nbits, precision_integral, precision_fractional, matmul_threshold, truncation_gap, use_noninteractive_truncation)