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python 3.x - Non-intersection of two n-dimentional pytorch tensors

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combined = torch.cat((t1, t2))
uniques, counts = combined.unique(return_counts=True)
difference = uniques[counts == 1]
intersection = uniques[counts > 1]

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if you don't want to leave cuda, a workaround could be:

t1 = torch.tensor([1, 9, 12, 5, 24], device = 'cuda')
t2 = torch.tensor([1, 24], device = 'cuda')
indices = torch.ones_like(t1, dtype = torch.uint8, device = 'cuda')
for elem in t2:
    indices = indices & (t1 != elem)  
intersection = t1[indices]

comparing two tensors in pytorch

python - How to find intersection of two sets of 2D tensors (points on a 2D plane) in Pytorch

pytorch - How to gather not tensor object in torch.distributed?

python - PyTorch tensor indexing produce different results after same operation

More results from stackoverflow.com

Quora

quora.com › Can-Pytorch-find-the-intersection-of-two-vectors

Can Pytorch find the intersection of two vectors? - Quora

Answer: I believe this might be in line of what you are looking for: jmichaux/pytorch-grasping Other than that, i largely found references to Matlab and custom Scripts that people have performed. If my memory serves me correctly - I do believe that Line intersection can be manually computed. ...

discuss.pytorch.org › t › intersection-between-to-vectors-tensors › 50364

Intersection between to vectors/tensors - PyTorch Forums

July 11, 2019 - Can pytorch find the intersection of two vectors? Similar to the Matlab “intersection” function: https://www.mathworks.com/help/matlab/ref/double.intersect.html;jsessionid=0f4b1f0e0ff110c50bb8a0076587 What about other…

discuss.pytorch.org › t › intersection-between-2d-tensors › 124267

Intersection between 2D tensors - PyTorch Forums

Check (a==b) *a . This should give elements where intersecting and zeros if not. Use result.nonzeor() if you don’t want zeros

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discuss.pytorch.org › t › intersection-between-to-vectors-tensors › 50364 › 3

Intersection between to vectors/tensors - #3 by WangXin93 - PyTorch Forums

November 18, 2019 - I used np.intersect1d like: >>> import torch >>> import numpy as np >>> a = torch.tensor([1, 2, 3, 6]) >>> b = torch.tensor([0, 2, 3, 7]) >>> np.intersect1d(a, b) array([2, 3]) It seems that tensorflow 2.0 has a function named tf.sets.intersection

github.com › vinija › AI-Coding › blob › main › SparseVectors.py

AI-Coding/SparseVectors.py at main · vinija/AI-Coding

common_indices = torch.intersect1d(self.indices, vec.indices) · # Compute the dot product for common indices · result = 0 · for i in common_indices: result += self.values[i] * vec.values[i] · return result ·

Author: vinija

github.com › multimodallearning › pytorch-mask-rcnn › blob › master › model.py

pytorch-mask-rcnn/model.py at master · multimodallearning/pytorch-mask-rcnn

December 23, 2021 - unique_bool = torch.cat((first_element, unique_bool),dim=0) return tensor[unique_bool.data] · def intersect1d(tensor1, tensor2): aux = torch.cat((tensor1, tensor2),dim=0) aux = aux.sort()[0] return aux[:-1][(aux[1:] == aux[:-1]).data] ·

Author: multimodallearning

Heekangpark

heekangpark.github.io › ml › shorts › pytorch-intersection-of-two-tensors

[pytorch] 두 텐서 간 교집합(Intersection) 구하기 | Reinventing the Wheel

August 21, 2020 - NumPy에서 제공하는 np.intersect1d() 메소드를 이용할 수 있다. ... import torch import numpy as np def getIntersection_Method1(a, b): a = a.detach().cpu().numpy() b = b.detach().cpu().numpy() intersection = np.intersect1d(a, b) return torch.from_numpy(intersection)

Cogdl

docs.cogdl.ai › en › 0.3.0 › _modules › cogdl › datasets › strategies_data.html

cogdl.datasets.strategies_data — CogDL 0.3.0 documentation

0 is no data # or negative, 1 is ... _, node_feature_indices, _ = np.intersect1d(allowable_features_pretrain, go_labels, return_indices=True) for idx in node_feature_indices: pretrain_go_node_feature[idx] = 1 data.go_target_downstream = torch.tensor(np.array(downstream_go_no...

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51CTO

blog.51cto.com › u_16175524 › 6877394

PyTorch Intersection()的实现 - 51CTO博客

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51CTO

blog.51cto.com › u_16213321 › 12489392

pytorch筛选两个tensor的交集 - 51CTO博客

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discuss.pytorch.org › t › intersection-between-to-vectors-tensors › 50364 › 8

Intersection between to vectors/tensors - #8 by Deeply - PyTorch Forums

February 17, 2021 - Not sure if this would help, as the code hoovers over all t2 elements in a for-loop. Hence, would not benefit from the GPU. In fact, numpy intersect is much faster. def tensor_intersect(t1, t2): t1=t1.cuda() t2=t2.cuda() indices = torch.zeros_like(t1, dtype = torch.bool, device = 'cuda') for elem in t2: indices = indices | (t1 == elem) intersection = t1[indices] return intersection t1= np.random.randint( 1,1e9, 10000) t2= np.random.randint( 1,1e9, 10000...

Stack Overflow

stackoverflow.com › questions › 75807477 › intersection-of-two-pytorch-tensors-without-loops-ideally-multidimensional

python - Intersection of two pytorch tensors without loops; ideally multidimensional - Stack Overflow

docs.scvi-tools.org › en › 1.1.4 › tutorials › notebooks › spatial › DestVI_tutorial.html

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If t_2 and t_1 are already sorted like in the example you can use torch.searchsorted.

torch.searchsorted(t_1, t_2)

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I do not know how efficient this solution is, but it might help:

eq_matrix = torch.eq(t_1[:, None], t_2)
output = torch.nonzero(eq_matrix)[:, 0]

Python

Multi-resolution deconvolution of spatial transcriptomics — scvi-tools

# filter genes to be the same on the spatial data intersect = np.intersect1d(sc_adata.var_names, st_adata.var_names) st_adata = st_adata[:, intersect].copy() sc_adata = sc_adata[:, intersect].copy() G = len(intersect)

Pygod

docs.pygod.org › en › latest › _modules › pygod › detector › scan.html

pygod.detector.scan - PyGOD 1.1.0 documentation

[docs] def fit(self, data, label=None): ... return self def _similarity(self, u, v): u_set = torch.unique(self._neighbors(u)) v_set = torch.unique(self._neighbors(v)) inter = np.intersect1d(v_set, u_set) if len(inter) == 0: return 0 # need to account for vertex itself, add 2(1 for ...

Hugging Face

huggingface.co › spaces › Doubiiu › DynamiCrafter › resolve › 8631f1e082952f8838b89332ea615a27342c1b3b › lvdm › models › ddpm3d.py

Huggingface

as_cumprod, t, x.shape) * noise ... noise = torch.randn_like(x_start) x_noisy = self.q_sample(x_start=x_start, t=t, noise=noise) diffusion_row.append(x_noisy) log["diffusion_row"] = self._get_rows_from_list(diffusion_row) if sample: # get denoise row with self.ema_scope("Plotting"): samples, denoise_row = self.sample(batch_size=N, return_intermediates=True) log["samples"] = samples log["denoise_row"] = self._get_rows_from_list(denoise_row) if return_keys: if np.intersect1d(list(log.keys()), ...

Stack Overflow

stackoverflow.com › questions › 61108901 › pytorch-element-intersection

python - pytorch element intersection - Stack Overflow

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Perhaps you could convert to numpy and then use its set operations.

import torch
import numpy as np

target = torch.tensor([[14, 13, 8, 11, 18, 12, 5, 1, 0, 10], [ 8, 10, 2, 10, 7, 17, 6, 12, 13, 14]])
pred_idx = torch.tensor([[14, 11, 8, 19, 4], [ 6, 9, 8, 13, 18]])

Find elements of p@5 in target:

[np.intersect1d(t,p) for t,p in zip(target.cpu().numpy(),pred_idx.cpu().numpy())]

Find number of elements in p@5 also in target:

[len(np.intersect1d(t,p)) for t,p in zip(target.cpu().numpy(),pred_idx.cpu().numpy())]

github.com › aliutkus › torchinterp1d

GitHub - aliutkus/torchinterp1d: 1D interpolation for pytorch · GitHub

This repository implements an interp1d function that overrides torch.autograd.Function, enabling linear 1D interpolation on the GPU for Pytorch.

Author: aliutkus