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| import glob |
| import os |
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| from tensorboard.backend.event_processing import event_accumulator |
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| from isaacsim.benchmark.services import BaseIsaacBenchmark |
| from isaacsim.benchmark.services.metrics.measurements import DictMeasurement, ListMeasurement, SingleMeasurement |
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| def parse_tf_logs(log_dir: str): |
| """Search for the latest tfevents file in log_dir folder and returns |
| the tensorboard logs in a dictionary. |
| |
| Args: |
| log_dir: directory used to search for tfevents files |
| """ |
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| |
| list_of_files = glob.glob(f"{log_dir}/events*") |
| latest_file = max(list_of_files, key=os.path.getctime) |
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| log_data = {} |
| ea = event_accumulator.EventAccumulator(latest_file) |
| ea.Reload() |
| tags = ea.Tags()["scalars"] |
| for tag in tags: |
| log_data[tag] = [] |
| for event in ea.Scalars(tag): |
| log_data[tag].append(event.value) |
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| return log_data |
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| def log_min_max_mean_stats(benchmark: BaseIsaacBenchmark, values: dict): |
| for k, v in values.items(): |
| measurement = SingleMeasurement(name=f"Min {k}", value=min(v), unit="ms") |
| benchmark.store_custom_measurement("runtime", measurement) |
| measurement = SingleMeasurement(name=f"Max {k}", value=max(v), unit="ms") |
| benchmark.store_custom_measurement("runtime", measurement) |
| measurement = SingleMeasurement(name=f"Mean {k}", value=sum(v) / len(v), unit="ms") |
| benchmark.store_custom_measurement("runtime", measurement) |
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| def log_app_start_time(benchmark: BaseIsaacBenchmark, value: float): |
| measurement = SingleMeasurement(name="App Launch Time", value=value, unit="ms") |
| benchmark.store_custom_measurement("startup", measurement) |
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| def log_python_imports_time(benchmark: BaseIsaacBenchmark, value: float): |
| measurement = SingleMeasurement(name="Python Imports Time", value=value, unit="ms") |
| benchmark.store_custom_measurement("startup", measurement) |
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| def log_task_start_time(benchmark: BaseIsaacBenchmark, value: float): |
| measurement = SingleMeasurement(name="Task Creation and Start Time", value=value, unit="ms") |
| benchmark.store_custom_measurement("startup", measurement) |
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| def log_scene_creation_time(benchmark: BaseIsaacBenchmark, value: float): |
| measurement = SingleMeasurement(name="Scene Creation Time", value=value, unit="ms") |
| benchmark.store_custom_measurement("startup", measurement) |
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| def log_simulation_start_time(benchmark: BaseIsaacBenchmark, value: float): |
| measurement = SingleMeasurement(name="Simulation Start Time", value=value, unit="ms") |
| benchmark.store_custom_measurement("startup", measurement) |
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| def log_total_start_time(benchmark: BaseIsaacBenchmark, value: float): |
| measurement = SingleMeasurement(name="Total Start Time (Launch to Train)", value=value, unit="ms") |
| benchmark.store_custom_measurement("startup", measurement) |
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| def log_runtime_step_times(benchmark: BaseIsaacBenchmark, value: dict, compute_stats=True): |
| measurement = DictMeasurement(name="Step Frametimes", value=value) |
| benchmark.store_custom_measurement("runtime", measurement) |
| if compute_stats: |
| log_min_max_mean_stats(benchmark, value) |
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| def log_rl_policy_rewards(benchmark: BaseIsaacBenchmark, value: list): |
| measurement = ListMeasurement(name="Rewards", value=value) |
| benchmark.store_custom_measurement("train", measurement) |
| |
| measurement = SingleMeasurement(name="Max Rewards", value=max(value), unit="float") |
| benchmark.store_custom_measurement("train", measurement) |
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| def log_rl_policy_episode_lengths(benchmark: BaseIsaacBenchmark, value: list): |
| measurement = ListMeasurement(name="Episode Lengths", value=value) |
| benchmark.store_custom_measurement("train", measurement) |
| |
| measurement = SingleMeasurement(name="Max Episode Lengths", value=max(value), unit="float") |
| benchmark.store_custom_measurement("train", measurement) |
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