6 results about "Operator function" patented technology

The invention belongs to the technical field of embedded software testing, and provides a VSIPL vector library function testing method and device.The method comprises the steps that operator functions to be tested are classified and abstracted into uniform function pointers, test cases are constructed based on the function pointers, and a corresponding relation table of the test cases and VSIPL data object specifications is established; automatically generating a matched VSIPL data object according to the relation table, calling the operator function to be tested and the reference operator function corresponding to the operator function to perform calculation on the same data, outputting a test result based on a calculation result and consumed time, and releasing resources. According to the method, on-demand self-adaptive generation of test data and unified scheduling of operator functions are realized through a cooperation mechanism of a function pointer and a relation table, the automation degree, coverage integrity and cross-platform verification efficiency of VSIPL vector library test are remarkably improved, batch performance and precision evaluation is supported, and the method is suitable for popularization and application. And the correctness and the acceleration effect of the optimized version function are effectively ensured.

The embodiment of the application provides a kind of operator calling method of deep learning framework, storage medium and electronic equipment, wherein deep learning framework is the framework of artificial intelligence model, deep learning framework includes front end, back end and adaptation layer, back end maintains with the string name of operator as key, with the operator interface function pointer of adaptation layer as value's register table, front end is used to dynamically load the operator library of back end;Method includes: using the string name of the operator to be called of front end to query register table, wherein the operator to be called belongs to the target operator library of target chip;In the case where the operator interface function pointer of the operator to be called is found, the operator interface function of the operator to be called in adaptation layer is called using the operator interface function pointer of the operator to be called, to call the operator function of the operator to be called in target operator library.By the present application, the operator calling method of deep learning framework in the related art is solved Adaptation layer low universality problem.

The application provides an operator calculation method, device, equipment and system in the field of artificial intelligence. The method comprises the following steps: acquiring parameter data of a first data shape of an AI network, the first data shape being a data length in each dimension supported by the AI network for processing, the parameter data comprising combination information of at least two calculation units, the data supported by each calculation unit for processing being data with a second data shape, and the data length of each calculation unit in any dimension after combination according to the combination information being greater than or equal to the data length of the first data shape in the same dimension; and calling the at least two calculation units to perform calculation on first target data with the first data shape. Therefore, the application supports the change of the data shape in any range by combining the at least two calculation units, realizes the AI dynamic shape operator function, and improves the AI network starting speed.

The invention discloses a dynamic reconfigurable chip implementation method based on a data flow framework, which belongs to the technical field of integrated circuit design, and comprises the following steps: firstly, receiving a top-layer user program by a software programming framework, and splitting the top-layer user program into operator levels to form a program operator data flow diagram; analyzing the number of data elements and the number of program operators executed by the program in parallel; reading the configurable depth and the number of processable parallel elements of a computing unit in the reconfigurable chip; according to the parameters, determining a data flow link length, an operation updating frequency and an operation grouping mode which are executed by the program in parallel according to a corresponding formula; reading the number and the positions of idle computing units in the reconfigurable chip, and determining the computing mode and the data flow direction of the computing units; and completing operator function configuration writing and data transmission configuration writing according to the operator data flow diagram in the data flow link. According to the invention, the instruction scheduling overhead is effectively saved, the execution power consumption of the computing unit is guaranteed, and the power consumption density of the whole chip is reduced.

The present application relates to a kind of computing operator fusion method and device, readable medium, program product and electronic equipment.The method includes: the data dependency between multiple operators in received computing stream and operator is parsed;Directed acyclic graph is constructed;Multiple candidate fusion strategies are generated based on the topological structure of directed acyclic graph;According to each candidate fusion strategy, reconstruct computing stream, and same fusion mark is assigned to the node divided in same fusion group;The reconstructed computing stream is compiled, and intermediate representation code is generated in the process of compiling, and the code logic of the node with same fusion mark in intermediate representation code is merged to generate a fusion operator function;The performance of each candidate fusion strategy containing fusion operator function is evaluated, and target fusion strategy is screened out from multiple candidate fusion strategies.The technical scheme of the present application realizes the full-process automation of operator fusion, breaks through the limit of artificial experience, and ensures that the global performance is better across hardware platform.

A building security system includes processors configured to: provide one or more machine learning models, at least one of the machine learning models trained to identify abnormalities within video data, the at least one machine learning model trained using at least one of video data or image data and annotations to the at least one of the video data or image data, and provide a virtual agent configured to: receive and process one or more input videos using the at least one machine learning model to identify abnormalities based on contextual information identified from the one or more input videos, and automatically perform, by the one or more machine learning models, an operator function in response to the identified abnormalities, wherein the operator function is determined according to at least one of a set of rules defined by the building security system or an operator input.