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US 2025/0156679 A1Published application
Compilation method, data processing method and apparatus thereof
AssigneeMediatek Inc.
InventorsPING-YUAN TSENG, Jen-Chieh Tsai, Sheng-Je Hung, Chia-Wei Hsu, PO-YEN LIN, YEN-HAO CHEN
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Abstract
The application discloses a compilation method, a data processing method and an apparatus thereof. Data representing a first graph characterizing the operations of a first neural network is obtained. The data representing the first graph is processed to transform the first graph into a second graph. A set of instructions for characterizing the second graph is generated. The set of instructions is provided to one or more hardware platforms.
Claims16
A compilation method, comprising:
- obtaining data representing a first graph characterizing the operations of a first neural network;
- processing the data representing the first graph to transform the first graph into a second graph;
- generating a set of instructions for characterizing the second graph;
- and
- providing the set of instructions to one or more hardware platforms,
- wherein the second graph includes a first partial transformed graph and a second partial transformed graph,
- the first partial transformed graph includes a plurality of convolution layers serially connected to generate a first partial output data based on a first part of an input data,
- the second partial transformed graph includes a plurality of convolution layers and a plurality of concatenation layers, the concatenation layer of the second partial transformed graph receiving convolution results from a corresponding convolution layer of the first partial transformed graph and a previous corresponding convolution layer of the second partial transformed graph for generating a concatenation result to a next corresponding convolution layer of the second partial transformed graph or as a second partial output data, the convolution layer of the second partial transformed graph receiving a second part of the input data or a concatenation result from a previous corresponding concatenation layer of the second partial transformed graph for generating a convolution result to a next corresponding concatenation layer of the second partial transformed graph.
5 more elements
A data processing method, comprising:
- receiving a set of instructions for characterizing a graph;
- obtaining input data;
- and
- performing the set of instructions on the input data for generating output data;
- wherein the graph includes a first partial transformed graph and a second partial transformed graph,
- the first partial transformed graph includes a plurality of convolution layers serially connected to generate a first partial output based on a first part of an input data,
- the second partial transformed graph includes a plurality of convolution layers and a plurality of concatenation layers, the concatenation layer of the second partial transformed graph receiving convolution results from a corresponding convolution layer of the first partial transformed graph and a previous corresponding convolution layer of the second partial transformed graph for generating a concatenation result to a next corresponding convolution layer of the second partial transformed graph or as a second partial output, the convolution layer of the second partial transformed graph receiving a second part of the input data or a concatenation result from a previous corresponding concatenation layer of the second partial transformed graph for generating a convolution result to a next corresponding concatenation layer of the second partial transformed graph.
4 more elements
A data processing apparatus, comprising:
- a processor, and
- a memory coupled to the processor,
- the processor being configured for:
- receiving a set of instructions for characterizing a graph;
- obtaining input data;
- and
- performing the set of instructions on the input data for generating output data;
- wherein the graph includes a first partial transformed graph and a second partial transformed graph,
- the first partial transformed graph includes a plurality of convolution layers serially connected to generate a first partial output based on a first part of an input data,
- the second partial transformed graph includes a plurality of convolution layers and a plurality of concatenation layers, the concatenation layer of the second partial transformed graph receiving convolution results from a corresponding convolution layer of the first partial transformed graph and a previous corresponding convolution layer of the second partial transformed graph for generating a concatenation result to a next corresponding convolution layer of the second partial transformed graph or as a second partial output, the convolution layer of the second partial transformed graph receiving a second part of the input data or a concatenation result from a previous corresponding concatenation layer of the second partial transformed graph for generating a convolution result to a next corresponding concatenation layer of the second partial transformed graph;
- wherein the concatenation result for the next corresponding convolution layer is stored in the memory, and the next corresponding convolution layer reads the concatenation result from the memory, the convolution result for the next corresponding concatenation layer is stored in the memory, and the next corresponding concatenation layer reads the convolution result from the memory.
8 more elements
Dependencies are inferred from the claim text.