pytorch常用函数之torch.randn()解读
土豆豆豆豆豆 人气:0pytorch常用函数torch.randn()
torch.randn(*sizes, out=None) → Tensor
功能:从标准正态分布(均值为0,方差为1)中抽取的一组随机数。返回一个张量
sizes (int…)
- 整数序列,定义输出张量的形状out (Tensor, optinal)
- 结果张量
eg:
random = torch.randn(2, 3) out: 0.5419 0.1594 -0.0413 -2.7937 0.9534 0.4561
pytorch torch.chunk(tensor, chunks, dim)
说明:在给定的维度上讲张量进行分块。
参数:
tensor(Tensor)
-- 待分块的输入张量chunks(int)
-- 分块的个数dim(int)
-- 维度,沿着此维度进行分块
>>> x = torch.randn(3, 3) >>> x tensor([[ 1.0103, 2.3358, -1.9236], [-0.3890, 0.6594, 0.6664], [ 0.5240, -1.4193, 0.1681]]) >>> torch.chunk(x, 3, dim=0) (tensor([[ 1.0103, 2.3358, -1.9236]]), tensor([[-0.3890, 0.6594, 0.6664]]), tensor([[ 0.5240, -1.4193, 0.1681]])) >>> torch.chunk(x, 3, dim=1) (tensor([[ 1.0103], [-0.3890], [ 0.5240]]), tensor([[ 2.3358], [ 0.6594], [-1.4193]]), tensor([[-1.9236], [ 0.6664], [ 0.1681]])) >>> torch.chunk(x, 2, dim=1) (tensor([[ 1.0103, 2.3358], [-0.3890, 0.6594], [ 0.5240, -1.4193]]), tensor([[-1.9236], [ 0.6664], [ 0.1681]]))
总结
以上为个人经验,希望能给大家一个参考,也希望大家多多支持。
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