Single-threading, Multistreaming Scenario
After APIs are called, add an exception handling branch, and record error logs and warning logs. The sample code of key steps is as follows, which is for reference only. Do not directly copy and run the code.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 | import acl # ...... device_id = 0 model_id_1 = 0 model_id_2 = 1 stream1, ret = acl.rt.create_stream() # Call the task execution API. For example, the asynchronous model inference task is delivered to stream1. ret = acl.mdl.execute_async(model_id_1, dataset_in_1, dataset_out_1, stream1) stream2, ret = acl.rt.create_stream() # Call the task execution API. For example, the asynchronous model inference task is delivered to stream2. ret = acl.mdl.execute_async(model_id_2, dataset_in_2, dataset_out_2, stream2) # Synchronize streams. ret = acl.rt.synchronize_stream(stream1) ret = acl.rt.synchronize_stream(stream2) # Destroy allocations. ret = acl.rt.destroy_stream(stream2) ret = acl.rt.destroy_stream(stream1) # .... |
Parent topic: Stream Management