/Zephyr-latest/include/zephyr/net/prometheus/ |
D | collector.h | 54 sys_slist_t metrics; member 79 .metrics = SYS_SLIST_STATIC_INIT(&_name.metrics), \
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/Zephyr-latest/scripts/footprint/ |
D | compare_footprint | 230 metrics = {} 233 metrics[type] = {} 239 if not row["test"] in metrics[type]: 240 metrics[type][row["test"]] = {} 241 metrics[type][row["test"]][row["platform"]] = d 243 for test, platforms in metrics['current'].items(): 244 if not test in metrics['base']: 249 if not platform in metrics['base'][test]: 251 golden_metric = metrics['base'][test][platform]
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/Zephyr-latest/samples/net/prometheus/ |
D | README.rst | 12 By integrating this library into your code, you can expose internal metrics 14 scrape and collect the metrics. 37 - Using a browser: ``http://192.0.2.1/metrics`` 82 ``'your_server_port'`` with the port number where your server exposes Prometheus metrics. 87 Once restarted, Prometheus will start scraping metrics from your server according 88 to the defined scrape configuration. You can verify that your server's metrics are 90 metrics from your server.
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/Zephyr-latest/subsys/net/lib/prometheus/ |
D | collector.c | 39 (void)sys_slist_find_and_remove(&collector->metrics, &metric->node); in prometheus_collector_register_metric() 41 sys_slist_prepend(&collector->metrics, &metric->node); in prometheus_collector_register_metric() 126 SYS_SLIST_FOR_EACH_CONTAINER_SAFE(&collector->metrics, metric, tmp, node) { in prometheus_collector_get_metric() 182 &ctx->collector->metrics, in prometheus_collector_walk_metrics()
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D | formatter.c | 258 SYS_SLIST_FOR_EACH_CONTAINER_SAFE(&collector->metrics, metric, tmp, node) { in prometheus_format_exposition()
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/Zephyr-latest/subsys/bluetooth/host/shell/ |
D | l2cap.c | 61 static bool metrics; variable 102 if (metrics) { in l2cap_recv() 156 if (!metrics) { in l2cap_alloc_buf() 483 metrics = true; in cmd_metrics() 485 metrics = false; in cmd_metrics() 537 SHELL_CMD_ARG(metrics, NULL, "<value on, off>", cmd_metrics, 2, 0),
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D | gatt.c | 1322 SHELL_CMD_ARG(metrics, NULL, "[value: on, off]", cmd_metrics, 1, 1),
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/Zephyr-latest/scripts/pylib/twister/twisterlib/ |
D | reports.py | 336 handler_time = instance.metrics.get('handler_time', 0) 337 used_ram = instance.metrics.get ("used_ram", 0) 338 used_rom = instance.metrics.get("used_rom",0) 339 available_ram = instance.metrics.get("available_ram", 0) 340 available_rom = instance.metrics.get("available_rom", 0) 514 if metric not in instance.metrics: 518 delta = instance.metrics.get(metric, 0) - mtype(sm[metric]) 521 results.append((instance, metric, instance.metrics.get(metric, 0), delta, 632 elif not ignore_unrecognized_sections and instance.metrics.get("unrecognized"): 641 handler_time = instance.metrics.get('handler_time', 0)
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D | runner.py | 1732 instance.metrics["used_ram"] = 0 1733 instance.metrics["used_rom"] = 0 1734 instance.metrics["available_rom"] = 0 1735 instance.metrics["available_ram"] = 0 1736 instance.metrics["unrecognized"] = [] 1748 instance.metrics["used_ram"] = size_calc.get_used_ram() 1749 instance.metrics["used_rom"] = size_calc.get_used_rom() 1750 instance.metrics["available_rom"] = size_calc.get_available_rom() 1751 instance.metrics["available_ram"] = size_calc.get_available_ram() 1752 instance.metrics["unrecognized"] = size_calc.unrecognized_sections() [all …]
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D | testplan.py | 717 instance.metrics['handler_time'] = ts.get('execution_time', 0) 718 instance.metrics['used_ram'] = ts.get("used_ram", 0) 719 instance.metrics['used_rom'] = ts.get("used_rom",0) 720 instance.metrics['available_ram'] = ts.get('available_ram', 0) 721 instance.metrics['available_rom'] = ts.get('available_rom', 0)
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D | testinstance.py | 59 self.metrics = dict()
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/Zephyr-latest/cmake/sca/eclair/ECL/ |
D | analysis_HIS.ecl | 9 # Enable the desired metrics.
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/Zephyr-latest/scripts/tests/twister/ |
D | test_runner.py | 2386 instance_mock.metrics = {} 2401 assert instance_mock.metrics['used_ram'] == 0 2402 assert instance_mock.metrics['used_rom'] == 0 2403 assert instance_mock.metrics['available_rom'] == 0 2404 assert instance_mock.metrics['available_ram'] == 0 2405 assert instance_mock.metrics['unrecognized'] == [] 2436 instance_mock.metrics = {} 2449 assert instance_mock.metrics['used_ram'] == \ 2451 assert instance_mock.metrics['used_rom'] == \ 2453 assert instance_mock.metrics['available_rom'] == \ [all …]
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D | test_testplan.py | 1706 assert expected_instances[n]['metrics'] == i.metrics
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/Zephyr-latest/samples/modules/tflite-micro/magic_wand/train/ |
D | train.py | 127 metrics=["accuracy"])
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D | train_magic_wand_model.ipynb | 193 …ss. Training will take around 5 minutes on a GPU runtime. You'll see the metrics in TensorBoard af…
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/Zephyr-latest/cmake/sca/eclair/ |
D | sca.cmake | 67 list(APPEND ECLAIR_REPORT_ADDITIONAL_OPTIONS "-metrics_tab=${ECLAIR_OUTPUT_DIR}/metrics")
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/Zephyr-latest/doc/develop/sca/ |
D | eclair.rst | 10 computation of software metrics, to the checking of independence and
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/Zephyr-latest/doc/safety/ |
D | safety_overview.rst | 171 requirements apply to safety for test coverage, and various metrics must be considered, which are
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/Zephyr-latest/doc/develop/test/ |
D | twister.rst | 624 regex: "RECORD:(?P<type>.*):DATA:(?P<metrics>.*)" 625 as_json: [metrics] 640 "metrics":{
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/Zephyr-latest/scripts/kconfig/ |
D | guiconfig.py | 383 .metrics("linespace") + 2
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/Zephyr-latest/doc/releases/ |
D | release-notes-4.0.rst | 43 A `Prometheus`_ metrics library has been added to the networking stack. It provides a way to 44 expose metrics to Prometheus clients over HTTP, facilitating the consolidated remote monitoring of
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D | release-notes-3.1.rst | 316 (e.g. fairness or interactivity metrics, budget tracking) that are
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/Zephyr-latest/doc/security/ |
D | security-overview.rst | 401 process and metrics such as cyclomatic complexity shall be
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/Zephyr-latest/samples/modules/tflite-micro/hello_world/train/ |
D | train_hello_world_model.ipynb | 404 "model_1.compile(optimizer='adam', loss='mse', metrics=['mae'])" 1740 "model.compile(optimizer='adam', loss=\"mse\", metrics=[\"mae\"])" 2897 …e metrics for validation are better than those for training is that validation metrics are calcula… 2957 …"Much better! The evaluation metrics we printed show that the model has a low loss and MAE on the …
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