def __getitem__(self, index): if self.mode == 'training': user_id, book_id, label = self.Xs[index] return user_id, book_id, label elif self.mode == 'validation': user_id, book_id = self.Xs[index] negs = list(random.sample( list(set(range(self.book_nums)) - set(self.user_book_map[user_id])), k=99 )) return user_id, book_id, torch.LongTensor(negs)
时间: 2023-12-05 07:03:23 浏览: 51
这段代码是一个 PyTorch Dataset 类的 __getitem__ 方法的实现。其中,该 Dataset 用于训练或验证推荐系统模型,包含三个变量:user_id、book_id 和 label。当 mode 为 'training' 时,返回 user_id、book_id 和 label;当 mode 为 'validation' 时,返回 user_id、book_id 和 99 个负样本。其中,负样本是在所有未被该用户购买的图书中随机采样得到的。这种采样方法被称为负采样(Negative Sampling),用于训练推荐系统模型的负样本。返回的负样本被封装成一个 LongTensor 类型的 Tensor。
相关问题
def __getitem__(self, index): if not self.is_train: index = self.train_index + index
这段代码是一个类的方法,用于获取数据集中某个索引位置的数据。`self`表示当前对象,`index`表示需要获取的数据的索引位置。`is_train`是一个布尔值,表示当前是否在训练模式下。如果不是训练模式,那么就需要加上`train_index`,因为在非训练模式下,`index`是相对于`train_index`的偏移量。具体来说,如果当前是测试模式,那么`index`就是测试数据集中的索引位置,但是在代码中实际需要获取的是训练数据集中的`train_index + index`位置的数据。
def __getitem__(self, index):
As an AI language model, I don't have access to the full context of your code. However, based on the method name "__getitem__", it is likely that this method is being used to implement the indexing behavior for a custom object or data structure.
In Python, the "__getitem__" method is a special method that allows objects to be indexed using square brackets. For example, if you have a custom list-like object, you could implement "__getitem__" to allow indexing like this:
my_list = MyCustomList([1, 2, 3])
print(my_list[0]) # prints 1
The "__getitem__" method takes an index as its argument and should return the value at that index. If the index is invalid, such as being out of range, the method should raise an IndexError.
Here is an example implementation of "__getitem__" for a custom list-like object:
class MyCustomList:
def __init__(self, items):
self.items = items
def __getitem__(self, index):
if index < 0 or index >= len(self.items):
raise IndexError("Index out of range")
return self.items[index]
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