* Doc Migration from Gitlab (#1289) * doc migration * fix * Update FakeQuantize_1.md * Update performance_benchmarks.md * Updates graphs for FPGA * Update performance_benchmarks.md * Change DL Workbench structure (#1) * Changed DL Workbench structure * Fixed tags * fixes * Update ie_docs.xml * Update performance_benchmarks_faq.md * Fixes in DL Workbench layout * Fixes for CVS-31290 * [DL Workbench] Minor correction * Fix for CVS-30955 * Added nGraph deprecation notice as requested by Zoe * fix broken links in api doxy layouts * CVS-31131 fixes * Additional fixes * Fixed POT TOC * Update PAC_Configure.md PAC DCP 1.2.1 install guide. * Update inference_engine_intro.md * fix broken link * Update opset.md * fix * added opset4 to layout * added new opsets to layout, set labels for them * Update VisionAcceleratorFPGA_Configure.md Updated from 2020.3 to 2020.4 Co-authored-by: domi2000 <domi2000@users.noreply.github.com>
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Hello Query Device C++ Sample
This topic demonstrates how to run the Hello Query Device sample application, which queries Inference Engine devices and prints their metrics and default configuration values. The sample shows how to use Query Device API feature.
NOTE: This topic describes usage of C++ implementation of the Query Device Sample. For the Python* implementation, refer to Hello Query Device Python* Sample
Running
To see quired information, run the following:
./hello_query_device
Sample Output
The application prints all available devices with their supported metrics and default values for configuration parameters:
Available devices:
Device: CPU
Metrics:
AVAILABLE_DEVICES : [ 0 ]
SUPPORTED_METRICS : [ AVAILABLE_DEVICES SUPPORTED_METRICS FULL_DEVICE_NAME OPTIMIZATION_CAPABILITIES SUPPORTED_CONFIG_KEYS RANGE_FOR_ASYNC_INFER_REQUESTS RANGE_FOR_STREAMS ]
FULL_DEVICE_NAME : Intel(R) Core(TM) i7-8700 CPU @ 3.20GHz
OPTIMIZATION_CAPABILITIES : [ WINOGRAD FP32 INT8 BIN ]
SUPPORTED_CONFIG_KEYS : [ CPU_BIND_THREAD CPU_THREADS_NUM CPU_THROUGHPUT_STREAMS DUMP_EXEC_GRAPH_AS_DOT DYN_BATCH_ENABLED DYN_BATCH_LIMIT EXCLUSIVE_ASYNC_REQUESTS PERF_COUNT ]
...
Default values for device configuration keys:
CPU_BIND_THREAD : YES
CPU_THREADS_NUM : 0
CPU_THROUGHPUT_STREAMS : 1
DUMP_EXEC_GRAPH_AS_DOT : ""
DYN_BATCH_ENABLED : NO
DYN_BATCH_LIMIT : 0
EXCLUSIVE_ASYNC_REQUESTS : NO
PERF_COUNT : NO
Device: FPGA
Metrics:
AVAILABLE_DEVICES : [ 0 ]
SUPPORTED_METRICS : [ AVAILABLE_DEVICES SUPPORTED_METRICS SUPPORTED_CONFIG_KEYS FULL_DEVICE_NAME OPTIMIZATION_CAPABILITIES RANGE_FOR_ASYNC_INFER_REQUESTS ]
SUPPORTED_CONFIG_KEYS : [ DEVICE_ID PERF_COUNT EXCLUSIVE_ASYNC_REQUESTS DLIA_IO_TRANSFORMATIONS_NATIVE DLIA_ARCH_ROOT_DIR DLIA_PERF_ESTIMATION ]
FULL_DEVICE_NAME : a10gx_2ddr : Intel Vision Accelerator Design with Intel Arria 10 FPGA (acla10_1150_sg10)
OPTIMIZATION_CAPABILITIES : [ FP16 ]
RANGE_FOR_ASYNC_INFER_REQUESTS : { 2, 5, 1 }
Default values for device configuration keys:
DEVICE_ID : [ 0 ]
PERF_COUNT : true
EXCLUSIVE_ASYNC_REQUESTS : false
DLIA_IO_TRANSFORMATIONS_NATIVE : false
DLIA_PERF_ESTIMATION : true
See Also
- Using Inference Engine Samples
- [Model Downloader](@ref omz_tools_downloader_README)
- Model Optimizer