torch.argsort(input,dim,descending) 用法 torch.sort:对输入数据排序,返回两个值,即排序后的数据values和其在原矩阵中的坐标indices torch.argsort:同torch.sort()返回的indices 参数 input:输入矩阵 dim:排序维度,默认为dim=1,即对行排序 descending:排序方式(从小到大和从大到小),默认为从小到大排序(即descend...
torch.argsort 解释 Returns the indices that sort a tensor along a given dimension in ascending order by value. 返回沿着给定维数按值升序对张量排序的索引。 重点 是按照值的顺序排列 2. 举例说明 a = torch.randn(4,4) a = tensor([[ 0.0785, 1.5267, -0.8521, 0.4065], [ 0.1598, 0.0788, -0.07...
默认是升序排列,调用ndarray.argsort 或者 tensor.argsort 返回的是index,加负号,将index逆序即可得到降序。 import torch import numpy as np if __name__ == '__main__': b = np.array([[2,3,4,5], [5,6,7,8], [2,2,2,2]]) # increasing order by default order = b[:,3].argsort()...
🐛 Describe the bug torch.argsort() return the wrong indices. Here's the code I am using: import torch torch.manual_seed(0) x = torch.randn(5,2) print(x) print(torch.argsort(x, dim=0)) and the returns of this are tensor([[ 1.5410, -0.2934...
def order_points(pts): pts_reorder = [] for idx, pt in enumerate(pts): idx = torch.argsort(pt[:, 0]) xSorted = pt[idx, :] leftMost = xSorted[:2, :] rightMost = xSorted[2:, :] leftMost = leftMost[torch.argsort(leftMost[:, 1]), :] (tl, bl) = leftMost D = torch.cdis...
Tensors and Dynamic neural networks in Python with strong GPU acceleration - torch.argsort() outputs wrongly · pytorch/pytorch@b61032f
问相同元素情况下的Torch.sort和argsort随机排序EN可以看出，torch.Tensor()没有保留数值类型，其它三个都...
2. torch.argsort()函数解析 用法跟上面torch.sort()函数一样,不同的是torch.argsort()返回只是排序后的值所对应原输入input的下标,即torch.sort()返回的indices 3. 代码举例 dim = 1 表示对每行中的元素进行降序排序,descending=True表示降序排序,输出结果为返回排序后的值所对应原输入input的下标indices ...
问numpy.argsort与torch.argsort的区别EN与 用在网页上都能使字体加粗，二者的不同是：是物理元素 ;是...
now say we have torch.tensor object similarity (in shape batch_size * 32768), I want to extract top similarities along the last dimension. get_top = torch.argsort(similarity, dim=1) get_top = torch.argsort(similarity, dim=1, descending=True) the code gives the result of: get_top =...