Operator accuracy detection method and device based on deep learning framework
A technology of precision detection and deep learning, applied in the field of deep learning, can solve problems such as poor detection effect, high cost, and low efficiency of operator precision testing, and achieve the effect of ensuring reliability and improving detection efficiency
Active Publication Date: 2022-05-13
厦门众联世纪股份有限公司
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Problems solved by technology
[0004] However, the deep learning framework has the characteristics of fast version iteration and a large number of operators. The unit test of operators usually involves multiple test samples. In related technologies, the method that requires operator accuracy testing is low in efficiency, high in cost and poor in detection effect
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[0031] Exemplary embodiments of the present application are described below in conjunction with the accompanying drawings, which include various details of the embodiments of the present application to facilitate understanding, and they should be regarded as exemplary only. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the application. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
[0032] In order to solve the technical problems of low efficiency, high cost and poor detection effect of the operator accuracy detection method based on the deep learning framework in the prior art, this application proposes an operator accuracy detection method based on the deep learning framework. Automatically detect the value, reverse calculation accuracy, etc.,...
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The application discloses an operator accuracy detection method, device, electronic equipment and storage medium based on a deep learning framework, and relates to the technical field of deep learning. The specific implementation plan is: obtain the test template corresponding to the unit test of the operator preset in the deep learning framework; analyze the test template to obtain the maximum accuracy of the unit test, and check whether the input data accuracy of at least one test sample in the unit test meets Accuracy maximum value; when the input data accuracy of at least one test sample meets the maximum accuracy value, obtain all reverse operators in the unit test according to the preset location identifier; detect each reverse operator according to the test template Whether the reverse calculation precision of all the reverse operators meets the preset conditions, and in the case that the reverse calculation precision of all reverse operators meets the preset conditions, the unit test detection success message of the operator is sent. As a result, the efficiency of operator precision detection is improved, thereby ensuring the reliability of deep learning framework operators.
Description
technical field [0001] The present application relates to the field of deep learning technology in the field of data processing technology, and in particular to an operator accuracy detection method, device, electronic device and storage medium based on a deep learning framework. Background technique [0002] Artificial intelligence is a discipline that studies the use of computers to simulate certain human thinking processes and intelligent behaviors (such as learning, reasoning, thinking, planning, etc.), both at the hardware level and at the software level. Artificial intelligence technologies generally include technologies such as sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, and big data processing; artificial intelligence software technologies mainly include computer vision technology, speech recognition technology, natural language processing technology, and machine learning / deep learning , big data processing technology, know...
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IPC IPC(8): G06N3/08G06N3/04
CPCG06N3/082G06N3/084G06N3/045
Inventor 高薇骆涛
Owner 厦门众联世纪股份有限公司