一. torch.repeat()函数解析
1. 说明
官网：torch.tensor.repeat()，函数说明如下图所示：
2. 函数功能
torch.tensor.repeat()函数可以对张量进行重复扩充
1) 当参数只有两个时：（行的重复倍数，列的重复倍数），1表示不重复。
2) 当参数有三个时：（通道数的重复倍数，行的重复倍数，列的重复倍数），1表示不重复。
3. 代码例子如下：
3.1 输入一维张量，参数为一个，即表示在列上面进行重复n次
a = torch.randn(3)a,a.repeat(4)结果如下所示：(tensor([ 0.81, -0.57, 0.10]), tensor([ 0.81, -0.57, 0.10, 0.81, -0.57, 0.10, 0.81, -0.57, 0.10, 0.81, -0.57, 0.10]))3.2 输入一维张量，参数为两个(m,n)，即表示先在列上面进行重复n次，再在行上面重复m次，输出张量为二维
a = torch.randn(3)a,a.repeat(4,2)(tensor([ 0.06, -0.76, -0.59]), tensor([[ 0.06, -0.76, -0.59, 0.06, -0.76, -0.59], [ 0.06, -0.76, -0.59, 0.06, -0.76, -0.59], [ 0.06, -0.76, -0.59, 0.06, -0.76, -0.59], [ 0.06, -0.76, -0.59, 0.06, -0.76, -0.59]]))3.3 输入一维张量，参数为三个(b,m,n)，即表示先在列上面进行重复n次，再在行上面重复m次，最后在通道上面重复b次，输出张量为三维
a = torch.randn(3)a,a.repeat(3,4,2)输出结果如下：(tensor([2.25, 0.49, 1.47]), tensor([[[2.25, 0.49, 1.47, 2.25, 0.49, 1.47], [2.25, 0.49, 1.47, 2.25, 0.49, 1.47], [2.25, 0.49, 1.47, 2.25, 0.49, 1.47], [2.25, 0.49, 1.47, 2.25, 0.49, 1.47]], [[2.25, 0.49, 1.47, 2.25, 0.49, 1.47], [2.25, 0.49, 1.47, 2.25, 0.49, 1.47], [2.25, 0.49, 1.47, 2.25, 0.49, 1.47], [2.25, 0.49, 1.47, 2.25, 0.49, 1.47]], [[2.25, 0.49, 1.47, 2.25, 0.49, 1.47], [2.25, 0.49, 1.47, 2.25, 0.49, 1.47], [2.25, 0.49, 1.47, 2.25, 0.49, 1.47], [2.25, 0.49, 1.47, 2.25, 0.49, 1.47]]]))3.4 输入二维张量，参数为两个(m,n)，即表示先在列上面进行重复n次，再在行上面重复m次，输出张量为两维（注意参数个数必须大于等于输入张量维度个数）
a = torch.randn(3,2)a,a.repeat(4,2)输出结果如下：(tensor([[-0.58, -1.21], [-0.35, 0.68], [ 0.33, 0.70]]), tensor([[-0.58, -1.21, -0.58, -1.21], [-0.35, 0.68, -0.35, 0.68], [ 0.33, 0.70, 0.33, 0.70], [-0.58, -1.21, -0.58, -1.21], [-0.35, 0.68, -0.35, 0.68], [ 0.33, 0.70, 0.33, 0.70], [-0.58, -1.21, -0.58, -1.21], [-0.35, 0.68, -0.35, 0.68], [ 0.33, 0.70, 0.33, 0.70], [-0.58, -1.21, -0.58, -1.21], [-0.35, 0.68, -0.35, 0.68], [ 0.33, 0.70, 0.33, 0.70]]))3.5 输入二维张量，参数为三个(b,m,n)，即表示先在列上面进行重复n次，再在行上面重复m次，最后在通道上面重复b次，输出张量为三维。（注意输出张量维度个数为参数个数）
a = torch.randn(3,2)a,a.repeat(3,4,2)输出结果如下：(tensor([[-0.75, 1.20], [-1.50, 1.75], [-0.05, 0.40]]), tensor([[[-0.75, 1.20, -0.75, 1.20], [-1.50, 1.75, -1.50, 1.75], [-0.05, 0.40, -0.05, 0.40], [-0.75, 1.20, -0.75, 1.20], [-1.50, 1.75, -1.50, 1.75], [-0.05, 0.40, -0.05, 0.40], [-0.75, 1.20, -0.75, 1.20], [-1.50, 1.75, -1.50, 1.75], [-0.05, 0.40, -0.05, 0.40], [-0.75, 1.20, -0.75, 1.20], [-1.50, 1.75, -1.50, 1.75], [-0.05, 0.40, -0.05, 0.40]], [[-0.75, 1.20, -0.75, 1.20], [-1.50, 1.75, -1.50, 1.75], [-0.05, 0.40, -0.05, 0.40], [-0.75, 1.20, -0.75, 1.20], [-1.50, 1.75, -1.50, 1.75], [-0.05, 0.40, -0.05, 0.40], [-0.75, 1.20, -0.75, 1.20], [-1.50, 1.75, -1.50, 1.75], [-0.05, 0.40, -0.05, 0.40], [-0.75, 1.20, -0.75, 1.20], [-1.50, 1.75, -1.50, 1.75], [-0.05, 0.40, -0.05, 0.40]], [[-0.75, 1.20, -0.75, 1.20], [-1.50, 1.75, -1.50, 1.75], [-0.05, 0.40, -0.05, 0.40], [-0.75, 1.20, -0.75, 1.20], [-1.50, 1.75, -1.50, 1.75], [-0.05, 0.40, -0.05, 0.40], [-0.75, 1.20, -0.75, 1.20], [-1.50, 1.75, -1.50, 1.75], [-0.05, 0.40, -0.05, 0.40], [-0.75, 1.20, -0.75, 1.20], [-1.50, 1.75, -1.50, 1.75], [-0.05, 0.40, -0.05, 0.40]]]))