torch.stack#
- torch.stack(tensors, dim=0, *, out=None) Tensor#
沿新維度連線一系列張量。
所有張量需要大小相同。
另請參閱
torch.cat()在現有維度上連線給定的序列。- 引數
tensors (sequence of Tensors) – 要連線的張量序列
dim (int, optional) – 要插入的維度。必須介於 0 和連線的張量的維度數(含)之間。預設為:0
- 關鍵字引數
out (Tensor, optional) – 輸出張量。
示例
>>> x = torch.randn(2, 3) >>> x tensor([[ 0.3367, 0.1288, 0.2345], [ 0.2303, -1.1229, -0.1863]]) >>> torch.stack((x, x)) # same as torch.stack((x, x), dim=0) tensor([[[ 0.3367, 0.1288, 0.2345], [ 0.2303, -1.1229, -0.1863]], [[ 0.3367, 0.1288, 0.2345], [ 0.2303, -1.1229, -0.1863]]]) >>> torch.stack((x, x)).size() torch.Size([2, 2, 3]) >>> torch.stack((x, x), dim=1) tensor([[[ 0.3367, 0.1288, 0.2345], [ 0.3367, 0.1288, 0.2345]], [[ 0.2303, -1.1229, -0.1863], [ 0.2303, -1.1229, -0.1863]]]) >>> torch.stack((x, x), dim=2) tensor([[[ 0.3367, 0.3367], [ 0.1288, 0.1288], [ 0.2345, 0.2345]], [[ 0.2303, 0.2303], [-1.1229, -1.1229], [-0.1863, -0.1863]]]) >>> torch.stack((x, x), dim=-1) tensor([[[ 0.3367, 0.3367], [ 0.1288, 0.1288], [ 0.2345, 0.2345]], [[ 0.2303, 0.2303], [-1.1229, -1.1229], [-0.1863, -0.1863]]])