Deep Learning Assignment Processing via Web UI and CLI
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Solution Overview
Problem
Current deep learning frameworks require users to program and run deep learning assignments manually, making the submission process complex and inefficient.
Innovation Solution
A deep learning assignment processing method and apparatus that allows users to submit assignments through web UI, CLI, or Notebook Style interfaces, with parameter parsing and management features, enabling the deep learning system to run assignments without manual programming and providing management options like stopping, deleting, and viewing states.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If users program and run deep learning assignments manually using programming languages, then the deep learning framework can execute the assignments, but the submission process becomes complex and processing efficiency decreases
Solution Approach 1:
The patent introduces an assignment management system that acts as an intermediary between users and the deep learning framework. This system provides automated assignment submission, parameter parsing, and execution management, eliminating the need for users to manually program and run assignments. The intermediary handles the complex coordination between user intent and framework execution, thereby improving both ease of operation and processing efficiency.
Solution Approach 2:
The assignment management system enables self-service by automatically parsing assignment parameters, managing submission workflows, and coordinating execution without requiring manual programming intervention from users. The system serves itself by handling the entire assignment lifecycle from submission to execution management, reducing operational complexity while maintaining productivity.
2Ease of operation
If users manually program deep learning assignments, then the assignments can be executed by the deep learning framework, but the user operations become complex and time-consuming
Solution Approach 1:
The system performs preliminary actions by pre-defining assignment templates, parameters, and execution configurations. Users can submit assignments using standardized formats without needing to program from scratch. The system prepares the execution environment and parses parameters in advance, significantly reducing the time and complexity of user operations while ensuring proper framework execution.
3Adaptability or versatility
If the system provides multiple submission interfaces (web UI, CLI, Notebook), then user accessibility improves, but system complexity increases
Solution Approach 1:
The assignment management system implements multi-functionality by providing multiple submission interfaces (web UI, CLI, Notebook) that all converge on a unified assignment processing backend. Each interface serves different user preferences and scenarios, but they all utilize the same core assignment management logic, parameter parsing, and execution control mechanisms. This universal approach enhances adaptability while managing system complexity through shared underlying infrastructure.
Data Source
AI summary
The present disclosure provides a deep learning assignment processing method and apparatus, a device and a storage medium. It is feasible to obtain the deep learning assignment submitted by the user in a predetermined manner, the predetermined manner comprising the web UI manner, then submit the deep learning assignment to the deep learning system so that the deep learning system runs the submitted deep learning assignment. As compared with the prior art, processing such as programming is not needed upon submitting the deep learning assignment in the solutions of the present disclosure, thereby simplifying the user's operations, improving the processing efficiency of the deep learning assignment, and accelerating the user's speed of developing deep learning.