haiku实现TemplatePairStack类

TemplatePairStack是实现蛋白质结构模版pair_act特征表示的类:
通过layer_stack.layer_stack(c.num_block)(block) 堆叠c.num_block(配置文件中为2)block 函数,每个block对输入pair_act 和 pair_mask执行计算流程:TriangleAttention ---> dropout ->TriangleAttention ---> dropout -> TriangleMultiplication ---> dropout -> TriangleMultiplication ---> dropout -> Transition

import haiku as hk


class TemplatePairStack(hk.Module):
  """Pair stack for the templates.

  Jumper et al. (2021) Suppl. Alg. 16 "TemplatePairStack"
  """

  def __init__(self, config, global_config, name='template_pair_stack'):
    super().__init__(name=name)
    self.config = config
    self.global_config = global_config

  def __call__(self, pair_act, pair_mask, is_training, safe_key=None):
    """Builds TemplatePairStack module.

    Arguments:
      pair_act: Pair activations for single template, shape [N_res, N_res, c_t].
      pair_mask: Pair mask, shape [N_res, N_res].
      is_training: Whether the module is in training mode.
      safe_key: Safe key object encapsulating the random number generation key.

    Returns:
      Updated pair_act, shape [N_res, N_res, c_t].
    """

    if safe_key is None:
      safe_key = prng.SafeKey(hk.next_rng_key())

    gc = self.global_config
    c = self.config

    if not c.num_block:
      return pair_act

    def block(x):
      """One block of the template pair stack."""
      pair_act, safe_key = x

      dropout_wrapper_fn = functools.partial(
          dropout_wrapper, is_training=is_training, global_config=gc)

      safe_key, *sub_keys = safe_key.split(6)
      sub_keys = iter(sub_keys)

      pair_act = dropout_wrapper_fn(
          TriangleAttention(c.triangle_attention_starting_node, gc,
                            name='triangle_attention_starting_node'),
          pair_act,
          pair_mask,
          next(sub_keys))
      pair_act = dropout_wrapper_fn(
          TriangleAttention(c.triangle_attention_ending_node, gc,
                            name='triangle_attention_ending_node'),
          pair_act,
          pair_mask,
          next(sub_keys))
      pair_act = dropout_wrapper_fn(
          TriangleMultiplication(c.triangle_multiplication_outgoing, gc,
                                 name='triangle_multiplication_outgoing'),
          pair_act,
          pair_mask,
          next(sub_keys))
      pair_act = dropout_wrapper_fn(
          TriangleMultiplication(c.triangle_multiplication_incoming, gc,
                                 name='triangle_multiplication_incoming'),
          pair_act,
          pair_mask,
          next(sub_keys))
      pair_act = dropout_wrapper_fn(
          Transition(c.pair_transition, gc, name='pair_transition'),
          pair_act,
          pair_mask,
          next(sub_keys))

      return pair_act, safe_key

    if gc.use_remat:
      block = hk.remat(block)

    res_stack = layer_stack.layer_stack(c.num_block)(block)
    pair_act, safe_key = res_stack((pair_act, safe_key))
    return pair_act
相关推荐
Eric.Lee20213 分钟前
数据集-目标检测系列- 螃蟹 检测数据集 crab >> DataBall
python·深度学习·算法·目标检测·计算机视觉·数据集·螃蟹检测
黑不溜秋的4 分钟前
C++ 语言特性29 - 协程介绍
开发语言·c++
一丝晨光9 分钟前
C++、Ruby和JavaScript
java·开发语言·javascript·c++·python·c·ruby
天上掉下来个程小白11 分钟前
Stream流的中间方法
java·开发语言·windows
xujinwei_gingko22 分钟前
JAVA基础面试题汇总(持续更新)
java·开发语言
sp_wxf31 分钟前
Lambda表达式
开发语言·python
DogDaoDao32 分钟前
【预备理论知识——2】深度学习:线性代数概述
人工智能·深度学习·线性代数
牛哥带你学代码33 分钟前
交叠型双重差分法
人工智能·深度学习·机器学习
学步_技术40 分钟前
自动驾驶系列—线控系统:驱动自动驾驶的核心技术解读与应用指南
人工智能·机器学习·自动驾驶·线控系统·转向系统
Fairy_sevenseven43 分钟前
【二十八】【QT开发应用】模拟WPS Tab
开发语言·qt·wps