ExecuteGraphWithStreamAsync

Applicability

Product

Supported or Not

Atlas A3 training products / Atlas A3 inference products

Atlas A2 training products / Atlas A2 inference products

Atlas 200I/500 A2 inference products

x

Atlas inference products

Atlas training products

Header File/Library File

  • Header file: #include <ge/ge_api.h>
  • Library file: libge_runner.so

Function Usage

Runs the graph of a specified ID and returns the execution result. This API is asynchronous.

Both this function and RunGraphWithStreamAsync are used to run the graph of a specified ID and output the result. However, this function features the following:

  • The CompileGraph and LoadGraph processes (asynchronous graph execution) must be completed before this API call.
  • The data type of inputs and outputs is gert::Tensor. For details, see Constructor.

Prototype

1
Status ExecuteGraphWithStreamAsync(uint32_t graph_id, void *stream,const std::vector<gert::Tensor> &inputs,std::vector<gert::Tensor> &outputs)

Parameters

Parameter

Input/Output

Description

graph_id

Input

Subgraph ID.

stream

Input

Stream on which a graph is run.

inputs

Input

Input data of the current subgraph, which is the memory on the device.

If the value of ge.exec.hostInputIndexes parameter is specified using options, Tensor of the corresponding index specifies the memory space on the host.

outputs

Output

Output data of the current subgraph, which is the memory on the device.

Returns

Parameter

Type

Description

-

Status

SUCCESS: The graph is successfully run by using the asynchronous API.

FAILED: The graph fails to be run by using the asynchronous API.

Restrictions

  • The memory required by Tensor must be allocated before this API call.
  • The CompileGraph and LoadGraph processes must be completed before this API call.
  • A stream must be created using aclrtCreateStream provided by acl before this API call.
  • Before the graph running result is output, the tasks on the stream are complete by using aclrtSynchronizeStream provided by acl.

    For details about the APIs, see "Stream Management" .

Example

For details, see Running a Graph Asynchronously.