openvino/samples/python/hello_query_device/README.md

Hello Query Device Python* Sample

This sample demonstrates how to show Inference Engine devices and prints their metrics and default configuration values using Query Device API feature.

The following Inference Engine Python API is used in the application:

Feature	API	Description
Basic	IECore	Common API
Query Device	IECore.get_metric, IECore.get_config	Get device properties

Options	Values
Supported devices	All
Other language realization	C++

How It Works

The sample queries all available Inference Engine devices and prints their supported metrics and plugin configuration parameters.

Running

The sample has no command-line parameters. To see the report, run the following command:

python <path_to_sample>/hello_query_device.py

Sample Output

The application prints all available devices with their supported metrics and default values for configuration parameters. (Some lines are not shown due to length.) For example:

[ INFO ] Creating Inference Engine
[ INFO ] Available devices:
[ INFO ] CPU :
[ INFO ]        SUPPORTED_METRICS:
[ INFO ]                AVAILABLE_DEVICES:
[ INFO ]                FULL_DEVICE_NAME: Intel(R) Core(TM) i5-8350U CPU @ 1.70GHz
[ INFO ]                OPTIMIZATION_CAPABILITIES: FP32, FP16, INT8, BIN
[ INFO ]                RANGE_FOR_ASYNC_INFER_REQUESTS: 1, 1, 1
[ INFO ]                RANGE_FOR_STREAMS: 1, 8
[ INFO ]
[ INFO ]        SUPPORTED_CONFIG_KEYS (default values):
[ INFO ]                CPU_BIND_THREAD: NUMA
[ INFO ]                CPU_THREADS_NUM: 0
[ INFO ]                CPU_THROUGHPUT_STREAMS: 1
[ INFO ]                DUMP_EXEC_GRAPH_AS_DOT:
[ INFO ]                DYN_BATCH_ENABLED: NO
[ INFO ]                DYN_BATCH_LIMIT: 0
[ INFO ]                ENFORCE_BF16: NO
[ INFO ]                EXCLUSIVE_ASYNC_REQUESTS: NO
[ INFO ]                PERF_COUNT: NO
[ INFO ]
[ INFO ] GNA :
[ INFO ]        SUPPORTED_METRICS:
[ INFO ]                AVAILABLE_DEVICES: GNA_SW
[ INFO ]                OPTIMAL_NUMBER_OF_INFER_REQUESTS: 1
[ INFO ]                FULL_DEVICE_NAME: GNA_SW
[ INFO ]                GNA_LIBRARY_FULL_VERSION: 2.0.0.1047
[ INFO ]
[ INFO ]        SUPPORTED_CONFIG_KEYS (default values):
[ INFO ]                EXCLUSIVE_ASYNC_REQUESTS: NO
[ INFO ]                GNA_COMPACT_MODE: NO
[ INFO ]                GNA_DEVICE_MODE: GNA_SW_EXACT
[ INFO ]                GNA_FIRMWARE_MODEL_IMAGE:
[ INFO ]                GNA_FIRMWARE_MODEL_IMAGE_GENERATION:
[ INFO ]                GNA_LIB_N_THREADS: 1
[ INFO ]                GNA_PRECISION: I16
[ INFO ]                GNA_PWL_UNIFORM_DESIGN: NO
[ INFO ]                GNA_SCALE_FACTOR: 1.000000
[ INFO ]                GNA_SCALE_FACTOR_0: 1.000000
[ INFO ]                PERF_COUNT: NO
[ INFO ]                SINGLE_THREAD: YES
[ INFO ]
[ INFO ] GPU :
[ INFO ]        SUPPORTED_METRICS:
[ INFO ]                AVAILABLE_DEVICES: 0
[ INFO ]                FULL_DEVICE_NAME: Intel(R) UHD Graphics 620 (iGPU)
[ INFO ]                OPTIMIZATION_CAPABILITIES: FP32, BIN, FP16
[ INFO ]                RANGE_FOR_ASYNC_INFER_REQUESTS: 1, 2, 1
[ INFO ]                RANGE_FOR_STREAMS: 1, 2
[ INFO ]
[ INFO ]        SUPPORTED_CONFIG_KEYS (default values):
[ INFO ]                CACHE_DIR:
[ INFO ]                CLDNN_ENABLE_FP16_FOR_QUANTIZED_MODELS: YES
[ INFO ]                CLDNN_GRAPH_DUMPS_DIR:
[ INFO ]                CLDNN_MEM_POOL: YES
[ INFO ]                CLDNN_NV12_TWO_INPUTS: NO
[ INFO ]                CLDNN_PLUGIN_PRIORITY: 0
[ INFO ]                CLDNN_PLUGIN_THROTTLE: 0
[ INFO ]                CLDNN_SOURCES_DUMPS_DIR:
[ INFO ]                CONFIG_FILE:
[ INFO ]                DEVICE_ID:
[ INFO ]                DUMP_KERNELS: NO
[ INFO ]                DYN_BATCH_ENABLED: NO
[ INFO ]                EXCLUSIVE_ASYNC_REQUESTS: NO
[ INFO ]                GPU_THROUGHPUT_STREAMS: 1
[ INFO ]                PERF_COUNT: NO
[ INFO ]                TUNING_FILE:
[ INFO ]                TUNING_MODE: TUNING_DISABLED
[ INFO ]

See Also

• Using Inference Engine Samples