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# PyTorch torch.dstack Function * * Pytorch torch Reference Manual](#) `torch.dstack` is a function in PyTorch used to stack tensors in depth (along the third dimension). ### Function Definition torch.dstack(tensors, *, out=None) * * * ## Usage Examples ## Example import torch # 2D Tensor Depth Stacking x1 = torch.tensor([[1,2],[3,4]]) x2 = torch.tensor([[5,6],[7,8]]) result = torch.dstack([x1, x2]) print("2D Tensor Depth Stacking:") print(f" x1:n{x1}") print(f" x2:n{x2}") print(f" dstack:n{result}") # 3D Tensor Depth Stacking y1 = torch.tensor([[[1,2],[3,4]],[[5,6],[7,8]]]) y2 = torch.tensor([[[9,10],[11,12]],[[13,14],[15,16]]]) result = torch.dstack([y1, y2]) print("n3D Tensor Depth Stacking:") print(f" y1:n{y1}") print(f" y2:n{y2}") print(f" dstack:n{result}") print(f" dstack Shape: {result.shape}") # 1D Tensor Depth Stacking z1 = torch.tensor([1,2,3]) z2 = torch.tensor([4,5,6]) result = torch.dstack([z1, z2]) print("n1D Tensor Depth Stacking:") print(f" z1: {z1}") print(f" z2: {z2}") print(f" dstack:n{result}") The output result is: 2D tensor deep stacking: x1: tensor([[1, 2], [3, 4]]) x2: tensor([[5, 6], [7, 8]]) dstack: tensor([[[ 1, 5], [ 2, 6]], [[ 3, 7], [ 4, 8]]])3D tensor deep stacking: y1: tensor([[[ 1, 2], [ 3, 4]], [[ 5, 6], [ 7, 8]]]) y2: tensor([[[ 9, 10], [11, 12]], [[13, 14], [15, 16]]]) dstack: tensor([[[ 1, 2, 9, 10], [ 3, 4, 11, 12]], [[ 5, 6, 13, 14], [ 7, 8, 15, 16]]]) dstack shape: torch.Size([2, 2, 4])1D tensor deep stacking: z1: tensor([1, 2, 3]) z2: tensor([4, 5, 6]) dstack: tensor([[1, 4], [2, 5], [3, 6]]) * * Pytorch torch Reference Manual](#)