def make_world(self, args, num_good_agents, num_adversaries): self.args = args world = World() world.args = args # set any world properties first world.dim_c = 2 num_agents = num_adversaries + num_good_agents world.collaborative = args.collaborative
时间: 2023-04-10 22:01:51 浏览: 63
这段代码定义了一个名为make_world的函数,它有三个参数:self、args、num_good_agents和num_adversaries。其中,self表示该函数是一个类的方法,args是一个参数,num_good_agents和num_adversaries分别表示好人和对手的数量。
在函数内部,首先将args参数赋值给self.args,然后创建一个名为world的World对象,并将args参数也赋值给world对象的args属性。最后,函数返回world对象。
相关问题
解释下这段代码 def make_world(self, args, num_good_agents, num_adversaries): self.args = args world = World() world.args = args
这段代码是定义了一个名为make_world的函数,该函数接受三个参数:args、num_good_agents和num_adversaries。在函数内部,将args赋值给self.args,并创建一个名为world的World对象,并将args赋值给world.args。
这段代码哪里错了 class my_BiGRU(torch.nn.Module): def __init__(self, input_size, hidden_size, num_layers, output_size, gru_dropout): super(my_BiGRU, self).__init__() self.input_size = input_size self.hidden_size = hidden_size self.num_layers = num_layers self.output_size = output_size self.gru_dropout = gru_dropout self.gru = torch.nn.GRU(input_size, hidden_size, num_layers=num_layers, batch_first=True, bidirectional=True) self.fc = torch.nn.Linear(hidden_size * 2, output_size) def _setup_BiGRU_layers(self): self.BiGRU_layers = my_BiGRU(input_size=self.args.capsule_out_dim, output_size=self.args.apsule_out_features, hidden_size=self.args.BiGRU_hiddensize, num_layers=self.args.BiGRU_layers, gru_dropout=self.args.BiGRU_dropout, )
这段代码存在两个问题:
1.函数 `_setup_BiGRU_layers` 中的代码应该是在类的构造函数 `__init__` 中进行初始化,而不是在另外一个函数中进行初始化。
2.在调用 `my_BiGRU` 类时,参数名称有误,应该将 `apsule_out_features` 改为 `capsule_out_features`。
改正后的代码如下所示:
```
class my_BiGRU(torch.nn.Module):
def __init__(self, input_size, hidden_size, num_layers, output_size, gru_dropout, capsule_out_features):
super(my_BiGRU, self).__init__()
self.input_size = input_size
self.hidden_size = hidden_size
self.num_layers = num_layers
self.output_size = output_size
self.gru_dropout = gru_dropout
self.gru = torch.nn.GRU(input_size, hidden_size, num_layers=num_layers, batch_first=True, bidirectional=True)
self.fc = torch.nn.Linear(hidden_size * 2, output_size)
self.BiGRU_layers = my_BiGRU(input_size=self.input_size,
output_size=capsule_out_features,
hidden_size=self.hidden_size,
num_layers=self.num_layers,
gru_dropout=self.gru_dropout,
)
```
注意:这里假设 `capsule_out_dim` 和 `args` 都已经在代码中被定义好了。