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公开(公告)号:US20230119229A1
公开(公告)日:2023-04-20
申请号:US17972492
申请日:2022-10-24
Applicant: Google LLC
Inventor: Sherry Moore , Jeremiah Harmsen , Noah Fiedel
IPC: G06N3/10 , G06F8/34 , G06N3/08 , G06F18/214 , G06F18/2137 , G06F18/21 , G06N3/044 , G06N3/047
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for augmenting a neural network with additional operations. One of the methods includes maintaining, by a computational graph system that manages execution of computational graphs representing neural network operations for users of the computational graph system, data specifying a plurality of pre-trained neural networks, wherein each of the pre-trained neural networks is a neural network that has been trained on training data to determine trained values of the respective parameters of the neural network; obtaining data specifying a user computational graph representing neural network operations, the user computational graph comprising a plurality of nodes connected by edges; identifying (i) an insertion point after a first node in the user computational graph and (ii) a particular pre-trained neural network from the plurality of pre-trained neural networks; and inserting a remote call node into the user computational graph.
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公开(公告)号:US11481638B2
公开(公告)日:2022-10-25
申请号:US16645441
申请日:2018-09-12
Applicant: GOOGLE LLC
Inventor: Sherry Moore , Jeremiah Harmsen , Noah Fiedel
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for augmenting a neural network with additional operations. One of the methods includes maintaining, by a computational graph system that manages execution of computational graphs representing neural network operations for users of the computational graph system, data specifying a plurality of pre-trained neural networks, wherein each of the pre-trained neural networks is a neural network that has been trained on training data to determine trained values of the respective parameters of the neural network; obtaining data specifying a user computational graph representing neural network operations, the user computational graph comprising a plurality of nodes connected by edges; identifying (i) an insertion point after a first node in the user computational graph and (ii) a particular pre-trained neural network from the plurality of pre-trained neural networks; and inserting a remote call node into the user computational graph.
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公开(公告)号:US11900263B2
公开(公告)日:2024-02-13
申请号:US17972492
申请日:2022-10-24
Applicant: Google LLC
Inventor: Sherry Moore , Jeremiah Harmsen , Noah Fiedel
IPC: G06N3/10 , G06F8/34 , G06N3/08 , G06F18/214 , G06F18/2137 , G06F18/21 , G06N3/044 , G06N3/047
CPC classification number: G06N3/105 , G06F8/34 , G06F18/214 , G06F18/2137 , G06F18/2178 , G06N3/044 , G06N3/047 , G06N3/08
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for augmenting a neural network with additional operations. One of the methods includes maintaining, by a computational graph system that manages execution of computational graphs representing neural network operations for users of the computational graph system, data specifying a plurality of pre-trained neural networks, wherein each of the pre-trained neural networks is a neural network that has been trained on training data to determine trained values of the respective parameters of the neural network; obtaining data specifying a user computational graph representing neural network operations, the user computational graph comprising a plurality of nodes connected by edges; identifying (i) an insertion point after a first node in the user computational graph and (ii) a particular pre-trained neural network from the plurality of pre-trained neural networks; and inserting a remote call node into the user computational graph.
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公开(公告)号:US20200210851A1
公开(公告)日:2020-07-02
申请号:US16645441
申请日:2018-09-12
Applicant: GOOGLE LLC
Inventor: Sherry Moore , Jeremiah Harmsen , Noah Fiedel
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for augmenting a neural network with additional operations. One of the methods includes maintaining, by a computational graph system that manages execution of computational graphs representing neural network operations for users of the computational graph system, data specifying a plurality of pre-trained neural networks, wherein each of the pre-trained neural networks is a neural network that has been trained on training data to determine trained values of the respective parameters of the neural network; obtaining data specifying a user computational graph representing neural network operations, the user computational graph comprising a plurality of nodes connected by edges; identifying (i) an insertion point after a first node in the user computational graph and (ii) a particular pre-trained neural network from the plurality of pre-trained neural networks; and inserting a remote call node into the user computational graph.
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