class node: def __init__(self,layer,next_layer=None): self.layer = layer self.next_layer = next_layer self.value = np.zeros((self.layer,1)) #当前节点的值,如X1,y1 if self.next_layer!=None: self.w = np.random.randn(self.next_layer,self.layer) #当前节点到下一节点的权值 randn为标准差为1的正态分布 self.b = np.random.randn( self.next_layer,1)
时间: 2024-02-23 09:56:33 浏览: 24
这段代码是定义了一个名为"node"的类,这个类包含了一些属性和方法。在这个类中,初始化函数"__init__"中包含了两个参数"layer"和"next_layer",分别表示当前节点的层数和下一层的节点数。在初始化函数中,首先将"layer"和"next_layer"赋值给了对应的属性"self.layer"和"self.next_layer"。然后,初始化了一个值为0的矩阵"self.value",它的大小是(layer,1),用于表示该节点的值,如X1,y1。最后,如果"next_layer"不为None,则初始化了一个权重矩阵"self.w"和一个偏置矩阵"self.b",用于连接当前节点和下一层的节点。其中,权重矩阵的大小为(next_layer,layer),偏置矩阵的大小为(next_layer,1),并且它们的值都是从标准差为1的正态分布中随机生成的。
相关问题
改写代码风格并保持变量名不变class LinkedList: class Node: def __init__(self, val, prior=None, next=None): self.val = val self.prior = prior self.next = next def __init__(self): self.head = LinkedList.Node(None) # sentinel node (never to be removed) self.head.prior = self.head.next = self.head # set up "circular" topology self.length = 0
下面是改写后的代码风格:
```
class LinkedList:
class Node:
def __init__(self, val, prior=None, next=None):
self.val = val
self.prior = prior
self.next = next
def __init__(self):
self.head = LinkedList.Node(None) # Sentinel node (never to be removed)
self.head.prior = self.head.next = self.head # Set up "circular" topology
self.length = 0
```
注意,变量名没有改变,只是对代码进行了一些格式化和注释。
class ListNode: def __init__(self, val, next=None): self.val = val self.next = next
class Solution:
def reverseList(self, head: ListNode) -> ListNode:
"""
:type head: ListNode
:rtype: ListNode
"""
prev = None
curr = head
while curr:
next_node = curr.next
curr.next = prev
prev = curr
curr = next_node
return prev
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