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How to use fill_ (value) in torch.tensor? aiming at this problem, this article introduces the corresponding analysis and solution in detail, hoping to help more partners who want to solve this problem to find a more simple and feasible method.

The lab code shows:

Microsoft Windows [version 10.0.18363.1256] (c) 2019 Microsoft Corporation. All rights reserved. C:\ Users\ chenxuqi > conda activate ssd4pytorch2_2_0 (ssd4pytorch2_2_0) C:\ Users\ chenxuqi > pythonPython 3.7.7 (default, May 6 2020, 11:45:54) [MSC v.1916 64 bit (AMD64)]:: Anaconda, Inc. On win32Type "help", "copyright", "credits" or "license" for more information. > import torch > > torch.manual_seed (seed=20200910) > a = torch.randn (3CM4) > > atensor ([[0.2824,-0.3715, 0.9088,-1.7601] [- 0.1806, 2.0937, 1.0406,-1.7651], [1.1216, 0.8440, 0.1783, 0.6859]) > > a.fill2020.0910 tensor ([[2020.0909, 2020.0909, 2020.0909, 2020.0909], [2020.0909, 2020.0909, 2020.0909, 2020.0909], [2020.0909, 2020.0909, 2020.0909]) > > atensor ([2020.0909, 2020.0909, 2020.0909) 2020.0909], [2020.0909, 2020.0909, 2020.0909, 2020.0909], [2020.0909, 2020.0909, 2020.0909, 2020.0909]) > > a [0memo] tensor (2020.0909) > > a [0re0] .item () 2020.0909423828125 > this is the answer to the question on how to use fill_ (value) in torch.tensor. I hope the above content can help you to a certain extent, if you still have a lot of doubts to be solved, you can follow the industry information channel to learn more related knowledge.

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