PyTorch torch.atleast_1d 函数
Pytorch torch 参考手册torch.atleast_1d 是 PyTorch 中用于将输入张量转换为至少 1 维的函数。如果输入已经是至少 1 维的，则返回原始张量的视图；否则会添加一个新的维度。
函数定义
torch.atleast_1d(*tensors)
使用示例
实例
import torch
# 标量转换为 1 维张量
x = torch.atleast_1d(5)
print("标量转换后:", x, "形状:", x.shape)
# 已经是 1 维的张量
x = torch.tensor([1, 2, 3])
y = torch.atleast_1d(x)
print("1维张量:", y, "形状:", y.shape)
# 2 维张量保持不变
x = torch.tensor([[1, 2], [3, 4]])
y = torch.atleast_1d(x)
print("2维张量:", y, "形状:", y.shape)
# 多个输入
a = 1
b = torch.tensor([2, 3])
c = torch.tensor([[4, 5]])
result = torch.atleast_1d(a, b, c)
for i, t in enumerate(result):
print(f"输入{i}形状: {t.shape}")
# 标量转换为 1 维张量
x = torch.atleast_1d(5)
print("标量转换后:", x, "形状:", x.shape)
# 已经是 1 维的张量
x = torch.tensor([1, 2, 3])
y = torch.atleast_1d(x)
print("1维张量:", y, "形状:", y.shape)
# 2 维张量保持不变
x = torch.tensor([[1, 2], [3, 4]])
y = torch.atleast_1d(x)
print("2维张量:", y, "形状:", y.shape)
# 多个输入
a = 1
b = torch.tensor([2, 3])
c = torch.tensor([[4, 5]])
result = torch.atleast_1d(a, b, c)
for i, t in enumerate(result):
print(f"输入{i}形状: {t.shape}")