Torch topk. (Bacause torch. If largest is False then the k smallest elements are returned. Jun 18, 2021 · import torch torch. import torch a = torch. The second output of torch. topk() method is used to find the top "k" elements. torch_geometric. So you will be better off calling sort() once, rather than. com Feb 21, 2022 · Learn how to use torch. equals will have shape (64, 64), try it yourself. If that's not the case then for some graphs x would be filled by 0s which would end up giving you the wrong topk result. tensor([2,3,1]) for idx, k in enumerate(K): top_k = torch. topk function to get indices of top-3 (for example) elements: >>> a = torch. Suppose I have a 3d Tensor x, and I run itorch. size()[1:] != pred. Summing only top K largest values from the result in step 1). Draws binary random numbers (0 or 1) from a Bernoulli distribution. topk() methods to get the k-th or the top “k” elements of a tensor in PyTorch. topk of the top k values, in this case 2, how could I use the long tensor indices of torch. view ( -1 )[ topk] = 1. *I understood the unpacking of top_class. The indices (empty tensor) returned by topk for k=0, leads to RuntimeError: CUDA error: device-side assert triggered when being used for selecting indexes within another tensor. topk (input, k, dim=NULL, largest=TRUE, sorted=TRUE) -> (Tensor, LongTensor) Returns the k largest elements of the given input tensor along a given dimension. self (Tensor) the input tensor. 다음의 코드는 앞서 선언한 텐서 x에 대해서 topk 함수를 수행한 결과입니다. g. scatter_(index=ind, dim=-1, value=5) print(a) Pytorch提供了一个名为topk的函数，可以用于提取张量中前k个最大（最小）值的索引。topk函数的第一个参数指定要提取的值的个数k，第二个参数确定是要提取最大值还是最小值，如果设置为True，则提取最大值，如果设置为False，则提取最小值。 Mar 27, 2020 · The stack trace points to an invalid index operation, so make sure to keep the bounds of idx:. Aug 23, 2021 · torch. In the below example we have taken a tensor X and are finding out Oct 11, 2022 · I would like to mask an input based on the top k masking values, naively doing something as in the following code. randperm((k_number - 1 ) * 64) print (a) print (torch. topk(-a, k=2) a. topk(x, 2, stable=true) #indices=[0, 2] torch. Since this is not differentiable, I wanted to ask if there’s a differentiable workaround to achieve the same thing? Thanks import torch top = 2 inp = torch. Modified today. nn. shape==[N, N_g]. If your k 's don't vary too much and you want to vectorize your code you can first take the maximum top k per row and then gather the desired results. transforms as transforms #from torch. 13. topk (logits, self. size(0) c = pred. I have tested it when top_k = 100% and the result is exactly like Apr 24, 2020 · When I use torch. shape is based on this. Screenshot 2020-04-13 at 10. See its documentation for the exact semantics of this method. COMMON. where. Example: Below I have computed the pipelined operation topk(Wx) in two ways and showed the gradients resulting from both are identical. version ): 1. Mar 25, 2020 · The indices return by torch. The input data is a tensor of size (batch, size, channel, img_features). Tensor. log_softmax(pred) n = pred. ; when distance="euclidean", topk_values are negative squared L2 distance between queries and topk closest data points. , a simple sorting and [:k] implementation would result in O(nlogn), while a quick-sort-styled partition would be O(n+k), also, when a heap is used the complexity would be O(n+klogn). Multinomial for more details) probability distribution located in the corresponding row of tensor input. autograd import Variable transform=transforms. a small test that I did. topk (input=a. 24 1074×156 9. I noticed that currently the magnitude sparsification method uses topk. 这些方法使我们能够轻松地处理张量中的最大元素 Source code for. Convert a tensor to compressed column storage (CSC) format. k (int) the k in "top-k" dim (int, optional) the dimension to torch. sort(). The first subfunction can do well , while the other will happen to this bug . What should I do to get the topk among non Sep 25, 2017 · The “sorted” parameter doesn’t affect the ordering of input samples which are the rows of pred, but it sorts the columns of pred that represent indices of the topk labels in the order [ top1 top2 top3 …topk ]. to_sparse_csc. The following snippet shows that the indices returned by topk contain invalid values. Clearly, if the first Aug 18, 2020 · I'm using the following code to find the topk matches using pytorch: def find_top(self, x, y, n_neighbors, unit_vectors=False, cuda=False): if not unit_vectors: x = __to_unit_torch__(x, Jun 7, 2023 · torch_topk: R Documentation: Topk Description. 이번에는 argmax의 상위호환 버전인 topk를 소개합니다. Tensor. 函数作用： 该函数的作用即按字面意思理解，topk:取数组的前k个元素进行排序。. rand(5, 5, requires_grad=True) mask = torch. If dim is not given, the last dimension of the input is chosen. See full list on zhuanlan. topk (input=a Differentiable Top-k Classification Learning. topk函数，我们获取了排名前5的概率最高的类别和对应的概率，并将其输出到控制台。 总结 通过本文，我们学习了如何使用PyTorch获取预测概率。 Jul 15, 2020 · Hi, I’m looking to get the topk gradients of all rows, not topk of each row. Currently I do this: torch. 我们可以使用argmax函数来获取最大元素的索引，使用max函数来同时获取最大元素的值和索引，以及使用topk函数来获取前k个最大元素的索引。. to_sparse_csr. " The straightforward interpretation of that sentence is that indices is a collection containing n-tuples where n is the number of dimensions in the original tensor input. topk() and use some other algorithms with better smoother gradient behaviour that outputs some inclusion probabilities, such as the work by this paper, “Differentiable Top-k Operator with Optimal Transport”, then how can I translate the inclusion probabilities Jul 15, 2020 · Aayush-Ankit (Aayush Ankit) July 15, 2020, 2:59pm 1. from typing import Callable, Optional, Tuple, Union import torch from torch import Tensor from torch_geometric. ages_by_class = [[ 99, 24 ], [ 99, 13 ], [ 55, 33 ], #<--- ages not necessarily sorted in any order apriori. zhihu. topk(input, k, dim=None, largest=True, sorted=True, out=None) ``` 参数说明： - input: 输入的张量。 - k: 需要获取的最大值的个数。 Jul 24, 2023 · The goal is to calculate the new “topk multiplication” function, where entry (i,j) in the output is calculated as follows: Perform element-wise multiplication between the i-th row of A and the j-th column of B. randn(5,4) >>> a. topk function that computes the top k values along a dimension. Nov 16, 2017 · Having seen a paper talking about mining top 70% gradient for Backpropagation, I am wondering if this strategy can real help improve performance. The following my code. [Answer 1] You need the first k largest of all the elements irrespective of the dimension. Value tensor of shape $ (a_1, a_2, , a_n, k)$ which contains the values of the top k elements along the last dimension 2. Index tensor of shape $ (a_1, a_2, , a_n, k)$ which contains the indices of the top k elements (original indices from the input tensor). The resulting tensor shape should then be: torch. kthvalue() and torch. This version of the operator has been available since version 11. So I typed in like this: import torch b = torch. topk and torch. topk. import torch. Aug 15, 2023 · LongTensor, shape: Tuple [int,],)-> torch. With this arg, you can save a std::sort (if k * 64 > n) so it's more efficient. rand(6, requires_grad = True) Aug 5, 2022 · module: cuda Related to torch. topk(2) topk_indices = linear_indices % stacked. Aggregation just outputs the s…. Returns up to three outputs: 1. 0000, 0. view(-1), k) But this also considers the zero elements in variable tensor and returns the top largest among them. argpartition is also not stable, so we cannot define the expected behavior based on np. 0) and can be a maximum of N elements (similarities is NxN matrix with the diagonal elements as 1 How could I go this? x = torch. def TopKLoss(pred, target, top_k=0. e, not to count zero elements in the counting process). Normalize((0. top-k accuracyというのは、モデルが予測した分類のうち、確率の高いもの上位k位までに The existing answers are correct, but I wanted to expand on them to provide a self-contained function that behaves exactly like torch. Convert a tensor to compressed row storage format (CSR). It seems that if we take the result from this function it is ending the search at index 2. size(1) out_size = (n,) + pred. 42 values, indices = torch. argsort ( w, descending=True )[: k ] mask. topk() in two subfunctions of my program . topkは、PyTorchのテンソル（Tensor）に対して、指定した次元ごとにk個の最大値または最小値を見つけるための関数です。この関数は、指定した次元で最大値または最小値のk個の要素と、それらの要素のインデックスを返します。 Feb 21, 2023 · The usage of sorted=False is when you are interested in only the top- k values instead of their order. So for the above, the boolean mask would look Mar 21, 2023 · Let's say we have an Op like topk, which has multiple outputs. topk(input, k, dim=None, largest=True, sorted=True, *, out=None) -> (Tensor, LongTensor) Returns the k largest elements of the given input tensor along a given dimension. ToTensor(), transforms. topk when the input contains +nan and -nan, the result is not sure; sometimes -nan is treated greater than normal number, sometimes -nan is the least; Versions torch 1. When is the fix expected? print (torch. rand(5,10) topk_list = [2,3,1,2,0] # means top2 for 1st row, top3 for 2nd row, top1 for 3rd row,. May 28, 2020 · 1. Size([3, 4, 3]) I know how to do topk for a single tensor, but how do I do this for several batches at once? Apr 13, 2020 · I am trying to implement a customized loss function in pytorch based on the formula below. This is a `torch` implementation of `numpy. Aug 1, 2022 · Hi, really appreciate your brilliant work. You switched accounts on another tab or window. Softmax() first and set the values I don’t want to 0, the calculation procedure is : Nov 12, 2023 · ultralytics. to_sparse. argpartition. topk(mask, top, dim=0 Nov 10, 2023 · torch. typing import OptTensor. (iii) The desired output would be a tensor x_top5 Feb 9, 2021 · ValueError: Using a target size (torch. In this specific use case you want, at the end, all 100 elements split up. sort(i, dim=1). Summary# Retrieve the top-K largest or smallest elements along a specified axis. Apr 1, 2021 · torch. Jul 18, 2022 · You can use the torch. Here, if K = n, then this operation reduces to the standard matrix Apr 25, 2021 · I’m not sure someone asked it before… Says we have a one-hot segmentation mask with BxNxHxW, where B=batch, N=class-categories, H=height, W=width of the mask. Return a tensor of elements selected from either input or other, depending on condition. The corresponding issue is MPS: Add support for TopK (k>16) on M1 GPU · Issue #78915 · pytorch/pytorch · GitHub. shape[-1] Oct 21, 2020 · 画像分類モデルの性能評価の計算 (top-k accuracy) 画像分類の性能評価にはILSVRC 2012の検証データが使って計算したtop-1, top-5 accuracyという量が使われることが多いようです。. Using argsort [:k] seems to actually both use less memory and actually be faster (which ig is expected for a 1D tensor). 3. TaskAlignedAssigner. Mar 10, 2020 · 1. multinomial. Does anyone have a link to the code implementation for this function? Thank you in advance. topk【按维度求前k个最值以及其索引】以及top1和top5 - 代码先锋网 Oct 31, 2022 · I want to apply the function torch. In [2]: x1 = torch. But I want to know more elegant code to realize this. when distance="inner", topk_values are inner product of queries and topk closest data points. sqrt() to compute their lengths, resulting in x_len. I am trying to implement k best selection, that consist of two parts: 1) aggregation / attention, 2) topk selection. Maximilian Gangloff. manual_seed(0) k_number = 20 a = torch. . NumPy関数を使って多次元配列のTopKを求める方法を検証します。. block: [197,0,0], thread: [32,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && "index out of bounds"` failed Oct 27, 2021 · Note the below approach would only work if all the graphs have the same number of nodes. Mar 25, 2018 · I used the torch. max ()、torch. Dec 31, 2019 · Top_p, top_class = ps. topk【按维度求前k个最值以及其索引】以及top1和top5，代码先锋网，一个为软件开发程序员提供代码片段和技术文章聚合的网站。 torch. We can use -1*all_num for getting min_top_k) val, ind = torch. Example: torch. A namedtuple of (values, indices) is returned, where the indices are the indices Jun 13, 2017 · Given a float tensor, and indices from torch. Improve this question. topk(x, 3, stable=true) #indices=[3, 0, 2] Note that np. If stable is True then the sorting routine becomes stable torch. max() Ask Question Asked 4 months ago. 5498]), but if I apply nn. topk with sorted=True doesn't return a result that is consistent across different values of k when dealing with duplicates values. I am thinking of getting the max, removing it, and then get the max again. eq(1) answered Jul 18, 2022 at 15:30. It is like a keepdim version of the torch Oct 23, 2022 · RuntimeError: Currently topk on mps works only for k<=16. However, in the following example, t2 has something wrong: 2144, 20, 104, 118, 123, 136, 137, 144, 171. topk_values, linear_indices = stacked. answered Aug 31, 2023 at 16:29. Oct 30, 2020 · Now I am trying to get the coordinates of vectors of top 5 length in each group. LongTensor : r"""Converts flat indices into unraveled coordinates in a target shape. pytorch; Share. Sep 6, 2023 · I'm trying to use topk to extract individual rankings of two tensors, with which I can compute the label y in torch. 5. It returns the value of the k-th element of tensor sorted in ascending order, and the index of the element in the original tensor. on the other word, I want to get a funtion foo_slice as following: top_tensor, indices = torch. Jan 17, 2024 · 🐛 Describe the bug torch. 16 KB. randn(8, 1, 64, 64) # [batch_size, 1, H, W] batch Nov 10, 2023 · torch. topk(), it returns the k largest elements of the given input tensor along a given dimension. scatter_. topk to get the index, I find that the program will stop quickly after several training iters because of Pyorch-CUDA error: device-side assert triggered, THCTensorScatterGather, Assertion indexValue failed. Topk Usage torch_topk(self, k, dim = -1L, largest = TRUE, sorted = TRUE) Arguments. index_list = [] # record the topk index in Nov 25, 2022 · basically, How can i use the indeces of these max k elements (return of the topk() torch function) to zero(set their values to 0) the original values in these positions out? preferred would be a suggestion of a torch method that does what im asking. topk and I would like to find information about how top k selection is implemented in a differentiable way (with respect to the top k values). The rankings in the inputs in my case are based on the magnitude of individual elements' values. A task-aligned assigner for object detection. topk is the "arg top k": the k indices of the top values. utils. 14. 这时候，我们想要看看这每张图片的1000个预测值中哪个值最大，最大值对应的下标是多少 Apr 24, 2020 · zhoulukuan commented on Apr 24, 2020. sum(dim=2). to('cuda:0') Jun 22, 2023 · Saved searches Use saved searches to filter your results more quickly Feb 13, 2021 · Note they are of different sizes. where(condition) is identical to torch. 94 6. Reload to refresh your session. Logits of other tokens remain − ∞ 通过使用torch. 则输出的是一个64*1000的tensor。. out ( Tensor, optional) – the output tensor. 举个栗子： 该函数功能经常用来获取张量或者 torch. 7000]), if I only want the top 2 softmax result for this tensor, the result should be tensor([0. May 17, 2021 · Since this is a W @ X or matrix-vector multiplication kind of operation, this is also differentiable. select import SelectTopK from torch_geometric. Jun 28, 2023 · torch. Nov 30, 2023 · torch. kthvalue() to find the k-th element of a tensor. elements = torch. I’m trying to find the top 3 maximize results from each one-hot element-wise vector of the map, and let other unselected elements be 0 (which means we want the dimension not to change). The difftopk library provides different differentiable sorting and ranking methods as well as a wrapper for using them in a TopKCrossEntropyLoss. Returns a tensor where each row contains num_samples indices sampled from the multinomial (a stricter definition would be multivariate, refer to torch. Here's how this can be used in the context of semantic segmentation: Suppose you have the ground truth prediction tensor y of shape b-h-w (dtype=torch. bernoulli. Jun 14, 2022 · The result I’m looking for is something like: For each index i , get all the values which are closer than 0. I can realize this without batch of tensor and batch also can be implemented with a for loop. 通常该函数返回2个值，第一个值为排序的数组，第二个值为该数组中获取到的元素在原数组中的位置标号。. Official implementation for our ICML 2022 Paper "Differentiable Top-k Classification Learning". Jan 20, 2022 · Pytorch provide torch. topk函数是PyTorch中的一个函数，用于获取张量（Tensor）中的前k个最大值。它的使用方式如下： ```python torch. a2mps = torch. unravel_index`. [ 55, 43 ], [ 55, 36 ], I’m trying to get the indexes or boolean mask or values corresponding to the topk ages within each group. topk(-x, 3) But wondering if this mink operation already exist. Here's the function (I've included the instructions inline): Aug 6, 2022 · You can use a combination of torch. distributions. topk(k) I’m wondering what’s the time complexity of that operation. 5,&hellip; Oct 30, 2020 · Now I am trying to get the coordinates of vectors of top 5 length in each group. Type. topk is strange. (iii) The desired output would be a tensor x_top5 torch. Size([16])) that is different to the input size (torch. argsort(input, dim=-1, descending=False, stable=False) → Tensor. See torch. In my option, if sorted=False, then the returned indices should be sorted, that is the elements in the indices are ascending. This class assigns ground-truth (gt) objects to anchors based on the task-aligned metric, which combines both classification and localization information. topk to set the values of x that aren’t in the topk to zero either in-place, or as a new object? Jun 25, 2023 · Since I supposed that the problem is that I use indices sort in using topk_sort, _ = torch. int64). indices) for selecting indexes to the another tensor works fine. Hi Maria! I want to get the two highest values from a number. rand(size=[10, 212, 500000]). randn(8, 256, 64, 64) # [batch_size, C, H, W] score_map = torch. should it be. However, when using an empty tensor (not from topk. Size([13456, 1])) is deprecated Hot Network Questions Can you tile a 25 x 25 square with a mixture of 2 x 2 squares and 3 x 3 squares? 🐛 Describe the bug I found a problem in my code which lead to discovering this issue. I am trying to use DINO to train my own dataset with 2 classes. Returns the indices that sort a tensor along a given dimension in ascending order by value. difftopk builds on PyTorch. pool. topk (1, dim=1) Pls scroll towards 1/3 down from this page. 1 cc @albanD Mar 11, 2021 · In this case, I don't know the real values of b, so I can't use topk to b. So I tried the following: (i) First I used x_len = (x**2). Attributes: Name. See also torch Jun 24, 2019 · import torch import torchvision import torchvision. For example, if I have a conv layer of shape [64, 64, 3, 3] and k=2, I only want 2 top values and their corresponding indices returned. connect import FilterEdges from torch_geometric. topk () 在用卷积神经网络对结果进行预测时，输出的是一个Batchsize*n的向量。. topk will get a very large number such as tensor (9223372034707292159 Jan 9, 2021 · torch. topk return max_top_k and you want min_top_k. shape inference: True. because the former has a shape of (64,64) based on the explanation of. Apr 9, 2024 · w = w. k, dim =-1) Set the values of the top-k selected indices to actual logits. a1mps = torch. Currently, we treat the whole output as an unit, and the graph trying to use each of the output element to different nodes is not supported. 13 & torch 2. size()[2:] if target. topk(a, k=k_number, sorted=False)) print (torch. topk(x, k=2, dim=1) So making PyG's topk visible is a good idea. function: False. 2,148 4 4 gold Dec 21, 2021 · 🐛 Describe the bug The function 'torch. I modified num_classes=3 and dn_labelbook_size = 3 (I think it is necessary), then start t Dec 30, 2020 · You signed in with another tab or window. nonzero(condition, as_tuple=True). rather than. topk () When we use torch. size()[2:]: raise ValueError('Expected Nov 21, 2019 · I believe this is what you want. Does torch. topk () do what you want? Oct 31, 2019 · Yes, top-k operation is differentiable, but I was asking if I don’t use torch. PyTorchの関数を使えば簡単にできますが、NumPyだけで行う場合は工夫が必要です。. 在本文中，我们介绍了在PyTorch中索引多维张量中最大元素的方法。. 比如batchsize=64，在ImageNet是1000分类的任务。. topk(tensor. if not it would be best for the solution to be as efficient as possible. rand(5, 5, requires_grad=True) top_mask_indices = torch. to_dense. So, flatten the tensor and use the torch. The ages are in column 1. k Nov 1, 2022 · torch. scatter_(0, top_k. tensor. topk_pool. topk(input, k, dim=None, largest=True, sorted=True) function to calculate k largest elements of the given input tensor along a given dimension dim. 앞서 argmax는 가장 큰 한 개의 값의 인덱스를 반환하는 것이었다면, 이 topk 함수는 가장 큰 k개의 값과 인덱스 모두 반환합니다. topk() Tensor. By clicking or navigating, you agree to allow our usage of cookies. to (“mps”), k=15) # working fine. Jul 4, 2022 · Hi Fried! fried-chicken: the first [32,50] contains the top-50-largest elements in each rows and the second [32,50] contains the top-50-smallest. topk(a, 2, dim=1) # top_tensor == foo_slice(a, indices) Is there any approach to achieve this using pytorch? Thanks! Nov 6, 2021 · PyTorch provides a method torch. topk' will return different results when the input tensor is on cpu and cuda. feature_map = torch. Attached below is my custom Cross_Entropy implementation for calculating top k percentage gradient for binary classification. multinomial. The remaining two issues are: that topk on CUDA is not consistent with CPU (or with sort() on any device). support_level: SupportType. The behavior varies between CPU and CUDA, and it's inconsistent both between and within the two backends. AFAIK, the returned order with sorted=False should be unpredictable, depending on the underlying std::nth_element algorithm. I have a tensor of shape (64, 128, 512) and I am using torch. topk(a, k=k_number, sorted=True)) I do not agree with the suggestion about "deprecating the argument", as the sorted=True does do something to sort the output values. topk documentation says that the function returns a tuple (values, indices), where indices is "the indices of the elements in the original input tensor. Any information (also just a description in words or pseudoc&hellip; Aug 11, 2022 · I want to do the feature selection based on the score map with two dimensional index. Penguin Penguin Apr 12, 2021 · The following code finds the top-k elements of a tensor. Compose([transforms. dev20221022. flatten(). 返回k个 input中的最大元素 Param： input：输入张量 k： 前k个最值 dim：若不指定，则默认dim为最后一个维度 largest：若为True，则返回k个最大元素；反之，为最小元素 sorted：控制是否按排序顺序返回元素 out：（Tensor，LongTensor）的输出元组，可以选择将其 torch. Paper @ ArXiv , Video @ Youtube. 7): pred = F. x, mask = to_dense_batch(x, batch) torch. topk(input, k, dim=None, largest=True, sorted=True, out=None) -> (Tensor, LongTensor) Returns the k largest elements of the given input tensor along a given dimension. 0. When I use torch. topk in the following manner-reduce = input. topk(x[idx], k) x[idx]. See answers, examples, and explanations from experts and users on Stack Overflow. >>> import torch. It returns the top "k" or largest "k" elements in the tensor. The position of duplicated values in the returned sorted indices varies with k. cuda, and CUDA support in general triaged This issue has been looked at a team member, and triaged and prioritized into an appropriate module Comments Copy link NumPy関数だけでTopKを求め、多次元のインデックスをスライスするための方法. Mar 30, 2022 · I’m using torch. Follow asked Nov 10, 2023 at 15:13. You signed out in another tab or window. Ultimately, I want a new tensor with a shape matching the dimensions of the original weight, with all elements zeroed out except the top k gradients. randn((905 TopK# TopK - 11# Version# name: TopK (GitHub) domain: main. Here is what I have now, which torch_topk(self, k, dim = -1L, largest = TRUE, sorted = TRUE) Arguments. randn(n) b = a. torch. MarginRankingLoss(input1, input2, y). float () topk = torch. indices, 1) mask = x. since_version: 11. To analyze traffic and optimize your experience, we serve cookies on this site. Sep 9, 2019 · To my understanding, I think these two methods are different. topk with pure numpy. (ii) Then I used tk = x_len. This is the second value returned by torch. In [1]: import torch. topk vs torch. ra Feb 5, 2019 · This also seems to be the desired default behaviour because it's consistent with numpy, as per #15886. topk, but only on the non-zero elements of the tensor (i. topk torch. topk - PyTorch Forums. Jun 4, 2018 · Advanced indexing with torch. Obviously for each index i, there’ll be a minimum 1 element (self similarity is 1. Size([3, 8, 3]) and I would like to find the topk(k=4) elements across dim1, where the value to sort by is dim2 (the negative values). いつも忘れるので自分用忘備録に. scatter_ methods for this: K = torch. Nov 9, 2018 · Learn how to retrieve the indices of maximum values in a Torch tensor using torch. 1 Like. Returns a sparse copy of the tensor. Penguin Penguin. topk(5) to get the top 5 lengths in each group. topk(k, dim=1). First you would find the topk elements in the flattened list, then convert those indices back to the row-relative format. topk ()函数快速理解. import torch n, k = 100, 5 a = torch. The operation is defined as: The tensors condition, input, other must be broadcastable. topk() function. 4502, 0. calling topk() one or more times: >>> import torch. I printed the index and found sometimes torch. Viewed 94 times 0 Has anyone tried comparing the values output by the above 2 Dec 25, 2019 · You are looking for torch. Creates a strided copy of self if self is not a strided tensor, otherwise returns self. I want to get the two highest values from a number. Nov 27, 2019 · vision. I am trying to calculate the top-k accuracy for each row in a matrix. topk will get a very large number such torch. Bases: Module. topk(x, k=2, dim=0)[1] to retrieve the indices of the first two max values over the 0th dimension. for. Somebody call this Online Hard Example Mining (OHEM). Resize(256),transforms. See syntax, parameters, and examples of these functions. # Code from OP. tal. AreTor June 4, 2018, 12:22pm 1. If largest is FALSE then the k smallest elements are returned. For example, we have a tensor a = tensor([0. values May 29, 2021 · Great! So you need the first k largest elements of a tensor. a certain way. E. 5000, 0. oo hv eh wv qi pj dw fv jg oi