PyTorch torch.concatenate Function
PyTorch torch Reference Manual
torch.concatenateis a function in PyTorch used to concatenate multiple tensors along a specified dimension. It is the same astorch.catis the same function, used to concatenate multiple tensors along a specified dimension into a larger tensor.
Function Definition
torch.concatenate(tensors, dim=0, out=None)
Parameters:
tensors(Sequence of Tensor): The sequence of tensors to be concatenated. All tensors must have the same shape in all dimensions except the concatenation dimension.dim(int, optional): The dimension along which to concatenate, defaults to 0.out(Tensor, optional): The output tensor.
Return Value:
torch.Tensor: Returns the concatenated tensor.
Usage Examples
Example
import torch
# Create multiple tensors
a = torch.tensor([1, 2])
b = torch.tensor([3, 4])
c = torch.tensor([5, 6])
# Concatenate multiple tensors
result = torch.concatenate([a, b, c])
print(result)
# Create multiple tensors
a = torch.tensor([1, 2])
b = torch.tensor([3, 4])
c = torch.tensor([5, 6])
# Concatenate multiple tensors
result = torch.concatenate([a, b, c])
print(result)
The output is:
tensor([1, 2, 3, 4, 5, 6])
Example
import torch
# Create two 2D tensors
a = torch.randn(2, 3)
b = torch.randn(2, 3)
# Concatenate along the first dimension
c = torch.concatenate([a, b], dim=0)
print("Shape of a:", a.shape)
print("Shape of b:", b.shape)
print("Shape of c:", c.shape)
# Create two 2D tensors
a = torch.randn(2, 3)
b = torch.randn(2, 3)
# Concatenate along the first dimension
c = torch.concatenate([a, b], dim=0)
print("Shape of a:", a.shape)
print("Shape of b:", b.shape)
print("Shape of c:", c.shape)
The output is:
a 的形状: torch.Size([2, 3]) b 的形状: torch.Size([2, 3]) c 的形状: torch.Size([4, 3])
Note:torch.concatenateYestorch.catan alias, and the two have exactly the same functionality. In actual code, the more commonly used istorch.cat。
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