PyTorch torch.concat Function
Pytorch torch Reference Manual
torch.concatis a function in PyTorch used to concatenate multiple tensors along a specified dimension. Ittorch.catis the same function, used to concatenate multiple tensors along a specified dimension into a larger tensor.
Function Definition
torch.concat(tensors, dim=0, out=None)
Parameters:
tensors(Sequence of Tensor): The sequence of tensors to concatenate. All tensors must have the same shape in all dimensions except the concatenation dimension.dim(int, optional): The dimension along which to concatenate, default is 0.out(Tensor, optional): The output tensor.
Return Value:
torch.Tensor: Returns the concatenated tensor.
Usage Examples
Example
import torch
# Create two tensors
a = torch.tensor([1, 2, 3])
b = torch.tensor([4, 5, 6])
# Concatenate two tensors
result = torch.concat([a, b])
print(result)
# Create two tensors
a = torch.tensor([1, 2, 3])
b = torch.tensor([4, 5, 6])
# Concatenate two tensors
result = torch.concat([a, b])
print(result)
The output result is:
tensor([1, 2, 3, 4, 5, 6])
Example
import torch
# Create two 2D tensors
a = torch.tensor([[1, 2], [3, 4]])
b = torch.tensor([[5, 6], [7, 8]])
# Concatenate along the first dimension
c = torch.concat([a, b], dim=0)
# Concatenate along the second dimension
d = torch.concat([a, b], dim=1)
print("Concatenation along dim=0:")
print(c)
print("nConcatenation along dim=1:")
print(d)
# Create two 2D tensors
a = torch.tensor([[1, 2], [3, 4]])
b = torch.tensor([[5, 6], [7, 8]])
# Concatenate along the first dimension
c = torch.concat([a, b], dim=0)
# Concatenate along the second dimension
d = torch.concat([a, b], dim=1)
print("Concatenation along dim=0:")
print(c)
print("nConcatenation along dim=1:")
print(d)
The output result is:
沿 dim=0 连接:
tensor([[1, 2],
[3, 4],
[5, 6],
[7, 8]])
沿 dim=1 连接:
tensor([[1, 2, 5, 6],
[3, 4, 7, 8]])
Note:torch.concatYestorch.catis an alias, and the functionality of the two is exactly the same.
Other Extensions