公开(公告)号：US20240370237A1

公开(公告)日：2024-11-07

申请号：US18774696

申请日：2024-07-16

Applicant: Microsoft Technology Licensing, LLC

Inventor： Haoxiang Lin ,  Mao Yang ,  Shuguang Liu ,  Cheng Chen

IPC: G06F8/34 ,  G06F3/0486 ,  G06N3/082

Abstract: Implementations of the present disclosure relate to visual programming for deep learning. A computer-implemented method comprises presenting a visual representation of an artificial neural network, the visual representation comprising graphical elements representing layers of the artificial neural network; in response to receiving a drag-and-drop operation on the graphical elements, modifying an intermediate representation of the artificial neural network, wherein the intermediate representation is independent of a deep learning framework and the drag-and-drop operation is configured to modify connections between the graphical elements; and modifying, based on the intermediate representation of the artificial neural network, code of the artificial neural network for a target deep learning framework.

公开(公告)号：US12079600B2

公开(公告)日：2024-09-03

申请号：US17615080

申请日：2020-05-06

Applicant: Microsoft Technology Licensing, LLC

Inventor： Haoxiang Lin ,  Mao Yang ,  Shuguang Liu ,  Cheng Chen

IPC: G06F8/34 ,  G06F3/0486 ,  G06N3/082

CPC classification number: G06F8/34 ,  G06F3/0486 ,  G06N3/082

Abstract: Implementations of the present disclosure relate to visual programming for deep learning. A computer-implemented method comprises presenting a visual representation of an artificial neural network, the visual representation comprising graphical elements representing layers of the artificial neural network; in response to receiving a drag-and-drop operation on the graphical elements, modifying an intermediate representation of the artificial neural network, wherein the intermediate representation is independent of a deep learning framework and the drag-and-drop operation is configured to modify connections between the graphical elements; and modifying, based on the intermediate representation of the artificial neural network, code of the artificial neural network for a target deep learning framework.

公开(公告)号：US20220222049A1

公开(公告)日：2022-07-14

申请号：US17615080

申请日：2020-05-06

Applicant: Microsoft Technology Licensing, LLC

Inventor： Haoxiang Lin ,  Mao Yang ,  Shuguang Liu ,  Cheng Chen

IPC: G06F8/34 ,  G06N3/08 ,  G06F3/0486

Abstract: Implementations of the present disclosure relate to visual programming for deep learning. A computer-implemented method comprises presenting a visual representation of an artificial neural network, the visual representation comprising graphical elements representing layers of the artificial neural network; in response to receiving a drag-and-drop operation on the graphical elements, modifying an intermediate representation of the artificial neural network, wherein the intermediate representation is independent of a deep learning framework and the drag-and-drop operation is configured to modify connections between the graphical elements; and modifying, based on the intermediate representation of the artificial neural network, code of the artificial neural network for a target deep learning framework.