From 213e301e589c53dd9e3667bc55687c17e629364b Mon Sep 17 00:00:00 2001 From: Chris McCarthy Date: Sat, 20 Jul 2024 15:05:56 +0100 Subject: [PATCH 1/4] retrospectively benchmarked 3.0.0 using the new benchmark process --- .azure/azure-benchmark-pipeline.yaml | 108 +++++++ benchmark/benchmark.py | 1 + benchmark/primaite_benchmark.py | 14 +- benchmark/report.py | 303 ++++++++++++------ .../PrimAITE Versions Learning Benchmark.png | Bin 92918 -> 0 bytes .../PrimAITE v3.0.0 Learning Benchmark.pdf | Bin 348917 -> 0 bytes .../PrimAITE v3.0.0 Learning Benchmark.png | Bin 302436 -> 0 bytes benchmark/utils.py | 2 +- 8 files changed, 329 insertions(+), 99 deletions(-) create mode 100644 .azure/azure-benchmark-pipeline.yaml delete mode 100644 benchmark/results/v3/PrimAITE Versions Learning Benchmark.png delete mode 100644 benchmark/results/v3/v3.0.0/PrimAITE v3.0.0 Learning Benchmark.pdf delete mode 100644 benchmark/results/v3/v3.0.0/PrimAITE v3.0.0 Learning Benchmark.png diff --git a/.azure/azure-benchmark-pipeline.yaml b/.azure/azure-benchmark-pipeline.yaml new file mode 100644 index 00000000..44010cac --- /dev/null +++ b/.azure/azure-benchmark-pipeline.yaml @@ -0,0 +1,108 @@ +trigger: +- release/* + +schedules: +- cron: "0 2 * * 1-5" # Run at 2 AM every weekday + displayName: "Weekday Schedule" + branches: + include: + - 'refs/heads/dev' +variables: + VERSION: '' + MAJOR_VERSION: '' + +jobs: +- job: PrimAITE_Benchmark + timeoutInMinutes: 360 # 6-hour maximum + pool: + name: 'Imaginary Yak Pool' + workspace: + clean: all + + steps: + - checkout: self + persistCredentials: true + + - script: | + python3.10 -m venv venv + displayName: 'Create venv' + + - script: | + VERSION=$(cat src/primaite/VERSION | tr -d '\n') + if [[ "$(Build.SourceBranch)" == "refs/heads/dev" ]]; then + DATE=$(date +%Y%m%d) + echo "${VERSION}+dev.${DATE}" > src/primaite/VERSION + fi + displayName: 'Update VERSION file for Dev Benchmark' + + - script: | + VERSION=$(cat src/primaite/VERSION | tr -d '\n') + MAJOR_VERSION=$(echo $VERSION | cut -d. -f1) + echo "##vso[task.setvariable variable=VERSION]$VERSION" + echo "##vso[task.setvariable variable=MAJOR_VERSION]$MAJOR_VERSION" + displayName: 'Set Version Variables' + + - script: | + source venv/bin/activate + pip install --upgrade pip + pip install -e .[dev,rl] + primaite setup + displayName: 'Install Dependencies' + + - script: | + set -e + source venv/bin/activate + cd benchmark + python primaite_benchmark.py + cd .. + displayName: 'Run Benchmarking Script' + + - script: | + tar czf primaite_v$(VERSION)_benchmark.tar.gz benchmark/results/v$(MAJOR_VERSION)/v$(VERSION) + displayName: 'Prepare Artifacts for Publishing' + + - task: PublishPipelineArtifact@1 + inputs: + targetPath: primaite_v$(VERSION)_benchmark.tar.gz + artifactName: 'benchmark-zip-output' + publishLocation: 'pipeline' + displayName: 'Publish Benchmark Output zip as Artifact' + + - script: | + git config --global user.email "oss@dstl.gov.uk" + git config --global user.name "Defence Science and Technology Laboratory UK" + workingDirectory: $(System.DefaultWorkingDirectory) + displayName: 'Configure Git' + condition: and(succeeded(), startsWith(variables['Build.SourceBranch'], 'refs/heads/release')) + + - script: | + echo "Fetching all branches..." + git fetch --all --prune + + echo "Stashing files..." + git stash push -u + + echo "Resolving branch name..." + # Extracting just the branch name from the full ref path + branch_name=$(echo "$(Build.SourceBranch)" | sed 's|refs/heads/||') + echo "Branch Name: $branch_name" + + echo "Checking out branch $branch_name..." + git checkout $branch_name + + echo "Popping stash..." + git stash pop + + echo "Adding benchmark results..." + git add benchmark/results/v$(MAJOR_VERSION)/v$(VERSION)/* + + echo "Committing changes..." + git commit -m "Automated benchmark output commit for version $(VERSION) [skip ci]" + + echo "Pushing to remote..." + git push origin $branch_name + displayName: 'Commit and Push Benchmark Results' + workingDirectory: $(System.DefaultWorkingDirectory) + env: + GIT_CREDENTIALS: $(System.AccessToken) + condition: and(succeeded(), startsWith(variables['Build.SourceBranch'], 'refs/heads/release')) diff --git a/benchmark/benchmark.py b/benchmark/benchmark.py index 5212b5d2..4ad398b9 100644 --- a/benchmark/benchmark.py +++ b/benchmark/benchmark.py @@ -1,3 +1,4 @@ +# © Crown-owned copyright 2024, Defence Science and Technology Laboratory UK from typing import Any, Dict, Optional, Tuple from gymnasium.core import ObsType diff --git a/benchmark/primaite_benchmark.py b/benchmark/primaite_benchmark.py index 3263867e..0e6c2acc 100644 --- a/benchmark/primaite_benchmark.py +++ b/benchmark/primaite_benchmark.py @@ -1,11 +1,11 @@ -# © Crown-owned copyright 2023, Defence Science and Technology Laboratory UK +# © Crown-owned copyright 2024, Defence Science and Technology Laboratory UK import json import shutil from datetime import datetime from pathlib import Path from typing import Any, Dict, Final, Tuple -from report import build_benchmark_latex_report +from report import build_benchmark_md_report from stable_baselines3 import PPO import primaite @@ -117,14 +117,14 @@ class BenchmarkSession: def generate_learn_metadata_dict(self) -> Dict[str, Any]: """Metadata specific to the learning session.""" total_s, s_per_step, s_per_100_steps_10_nodes = self._learn_benchmark_durations() - self.gym_env.average_reward_per_episode.pop(0) # remove episode 0 + self.gym_env.total_reward_per_episode.pop(0) # remove episode 0 return { "total_episodes": self.gym_env.episode_counter, "total_time_steps": self.gym_env.total_time_steps, "total_s": total_s, "s_per_step": s_per_step, "s_per_100_steps_10_nodes": s_per_100_steps_10_nodes, - "av_reward_per_episode": self.gym_env.average_reward_per_episode, + "total_reward_per_episode": self.gym_env.total_reward_per_episode, } @@ -151,8 +151,8 @@ def _prepare_session_directory(): def run( - number_of_sessions: int = 2, - num_episodes: int = 5, + number_of_sessions: int = 5, + num_episodes: int = 1000, episode_len: int = 128, n_steps: int = 1280, batch_size: int = 32, @@ -188,7 +188,7 @@ def run( with open(_SESSION_METADATA_ROOT / f"{i}.json", "r") as file: session_metadata_dict[i] = json.load(file) # generate report - build_benchmark_latex_report( + build_benchmark_md_report( benchmark_start_time=benchmark_start_time, session_metadata=session_metadata_dict, config_path=data_manipulation_config_path(), diff --git a/benchmark/report.py b/benchmark/report.py index 7d4c27a4..9c576562 100644 --- a/benchmark/report.py +++ b/benchmark/report.py @@ -1,4 +1,4 @@ -# © Crown-owned copyright 2023, Defence Science and Technology Laboratory UK +# © Crown-owned copyright 2024, Defence Science and Technology Laboratory UK import json import sys from datetime import datetime @@ -9,10 +9,6 @@ import plotly.graph_objects as go import polars as pl import yaml from plotly.graph_objs import Figure -from pylatex import Command, Document -from pylatex import Figure as LatexFigure -from pylatex import Section, Subsection, Tabular -from pylatex.utils import bold from utils import _get_system_info import primaite @@ -21,10 +17,20 @@ PLOT_CONFIG = { "size": {"auto_size": False, "width": 1500, "height": 900}, "template": "plotly_white", "range_slider": False, + "av_s_per_100_steps_10_nodes_benchmark_threshold": 5, + "benchmark_line_color": "grey", } def _build_benchmark_results_dict(start_datetime: datetime, metadata_dict: Dict, config: Dict) -> dict: + """ + Constructs a dictionary aggregating benchmark results from multiple sessions. + + :param start_datetime: The datetime when the benchmarking started. + :param metadata_dict: Dictionary containing metadata for each session. + :param config: Configuration settings used during the benchmarking. + :return: A dictionary containing aggregated data and metadata from the benchmarking sessions. + """ num_sessions = len(metadata_dict) # number of sessions averaged_data = { @@ -39,24 +45,30 @@ def _build_benchmark_results_dict(start_datetime: datetime, metadata_dict: Dict, "av_s_per_step": sum(d["s_per_step"] for d in metadata_dict.values()) / num_sessions, "av_s_per_100_steps_10_nodes": sum(d["s_per_100_steps_10_nodes"] for d in metadata_dict.values()) / num_sessions, - "combined_av_reward_per_episode": {}, - "session_av_reward_per_episode": {k: v["av_reward_per_episode"] for k, v in metadata_dict.items()}, + "combined_total_reward_per_episode": {}, + "session_total_reward_per_episode": {k: v["total_reward_per_episode"] for k, v in metadata_dict.items()}, "config": config, } # find the average of each episode across all sessions - episodes = metadata_dict[1]["av_reward_per_episode"].keys() + episodes = metadata_dict[1]["total_reward_per_episode"].keys() for episode in episodes: combined_av_reward = ( - sum(metadata_dict[k]["av_reward_per_episode"][episode] for k in metadata_dict.keys()) / num_sessions + sum(metadata_dict[k]["total_reward_per_episode"][episode] for k in metadata_dict.keys()) / num_sessions ) - averaged_data["combined_av_reward_per_episode"][episode] = combined_av_reward + averaged_data["combined_total_reward_per_episode"][episode] = combined_av_reward return averaged_data def _get_df_from_episode_av_reward_dict(data: Dict) -> pl.DataFrame: + """ + Converts a dictionary of episode average rewards into a Polars DataFrame. + + :param data: Dictionary with episodes as keys and average rewards as values. + :return: Polars DataFrame with episodes and average rewards, including a rolling average. + """ data: Dict = {"episode": data.keys(), "av_reward": data.values()} return ( @@ -71,6 +83,14 @@ def _plot_benchmark_metadata( title: Optional[str] = None, subtitle: Optional[str] = None, ) -> Figure: + """ + Plots benchmark metadata as a line graph using Plotly. + + :param benchmark_metadata_dict: Dictionary containing the total reward per episode and session. + :param title: Optional title for the graph. + :param subtitle: Optional subtitle for the graph. + :return: Plotly figure object representing the benchmark metadata plot. + """ if title: if subtitle: title = f"{title}
{subtitle}" @@ -87,7 +107,7 @@ def _plot_benchmark_metadata( fig = go.Figure(layout=layout) fig.update_layout(template=PLOT_CONFIG["template"]) - for session, av_reward_dict in benchmark_metadata_dict["session_av_reward_per_episode"].items(): + for session, av_reward_dict in benchmark_metadata_dict["session_total_reward_per_episode"].items(): df = _get_df_from_episode_av_reward_dict(av_reward_dict) fig.add_trace( go.Scatter( @@ -100,7 +120,7 @@ def _plot_benchmark_metadata( ) ) - df = _get_df_from_episode_av_reward_dict(benchmark_metadata_dict["combined_av_reward_per_episode"]) + df = _get_df_from_episode_av_reward_dict(benchmark_metadata_dict["combined_total_reward_per_episode"]) fig.add_trace( go.Scatter( x=df["episode"], y=df["av_reward"], mode="lines", name="Combined Session Av", line={"color": "#FF0000"} @@ -136,11 +156,11 @@ def _plot_all_benchmarks_combined_session_av(results_directory: Path) -> Figure: Does this by iterating over the ``benchmark/results`` directory and extracting the benchmark metadata json for each version that has been - benchmarked. The combined_av_reward_per_episode is extracted from each, + benchmarked. The combined_total_reward_per_episode is extracted from each, converted into a polars dataframe, and plotted as a scatter line in plotly. """ major_v = primaite.__version__.split(".")[0] - title = f"Learning Benchmarking of All Released Versions under Major v{major_v}.*.*" + title = f"Learning Benchmark of Minor and Bugfix Releases for Major Version {major_v}" subtitle = "Rolling Av (Combined Session Av)" if title: if subtitle: @@ -162,7 +182,7 @@ def _plot_all_benchmarks_combined_session_av(results_directory: Path) -> Figure: metadata_file = dir / f"{dir.name}_benchmark_metadata.json" with open(metadata_file, "r") as file: metadata_dict = json.load(file) - df = _get_df_from_episode_av_reward_dict(metadata_dict["combined_av_reward_per_episode"]) + df = _get_df_from_episode_av_reward_dict(metadata_dict["combined_total_reward_per_episode"]) fig.add_trace(go.Scatter(x=df["episode"], y=df["rolling_av_reward"], mode="lines", name=dir.name)) @@ -180,10 +200,118 @@ def _plot_all_benchmarks_combined_session_av(results_directory: Path) -> Figure: return fig -def build_benchmark_latex_report( +def _get_performance_benchmark_for_all_version_dict(results_directory: Path) -> Dict[str, float]: + """ + Gathers performance benchmarks for all versions of the software stored in a specified directory. + + This function iterates through each directory within the specified results directory, + extracts the av_s_per_100_steps_10_nodes from the benchmark_metadata.json files, and aggregates it into a + dictionary. + + :param results_directory: The directory containing subdirectories for each version's benchmark data. + :return: A dictionary with version numbers as keys and their corresponding average performance benchmark + (average time per 100 steps on 10 nodes) as values. + """ + performance_benchmark_dict = {} + for dir in results_directory.iterdir(): + if dir.is_dir(): + metadata_file = dir / f"{dir.name}_benchmark_metadata.json" + with open(metadata_file, "r") as file: + metadata_dict = json.load(file) + version = metadata_dict["primaite_version"] + performance_benchmark_dict[version] = metadata_dict["av_s_per_100_steps_10_nodes"] + return performance_benchmark_dict + + +def _plot_av_s_per_100_steps_10_nodes( + version_times_dict: Dict[str, float], +) -> Figure: + """ + Creates a bar chart visualising the performance of each version of PrimAITE. + + Performance is based on the average training time per 100 steps on 10 nodes. The function also includes a benchmark + line indicating the target maximum time. + + Versions that perform under this time are marked in green, and those over are marked in red. + + :param version_times_dict: A dictionary with software versions as keys and average times as values. + :return: A Plotly figure object representing the bar chart of the performance metrics. + """ + major_v = primaite.__version__.split(".")[0] + title = f"Performance of Minor and Bugfix Releases for Major Version {major_v}" + subtitle = ( + f"Average Training Time per 100 Steps on 10 Nodes " + f"(target: <= {PLOT_CONFIG['av_s_per_100_steps_10_nodes_benchmark_threshold']} seconds)" + ) + title = f"{title}
{subtitle}" + + layout = go.Layout( + autosize=PLOT_CONFIG["size"]["auto_size"], + width=PLOT_CONFIG["size"]["width"], + height=PLOT_CONFIG["size"]["height"], + ) + fig = go.Figure(layout=layout) + fig.update_layout(template=PLOT_CONFIG["template"]) + + versions = sorted(list(version_times_dict.keys())) + times = [version_times_dict[version] for version in versions] + av_s_per_100_steps_10_nodes_benchmark_threshold = PLOT_CONFIG["av_s_per_100_steps_10_nodes_benchmark_threshold"] + benchmark_line_color = PLOT_CONFIG["benchmark_line_color"] + + # Calculate the appropriate maximum y-axis value + max_y_axis_value = max(max(times), av_s_per_100_steps_10_nodes_benchmark_threshold) + 1 + + fig.add_trace( + go.Bar( + x=versions, + y=times, + marker_color=[ + "green" if time < av_s_per_100_steps_10_nodes_benchmark_threshold else "red" for time in times + ], + text=times, + textposition="auto", + ) + ) + + # Add a horizontal line for the benchmark + fig.add_shape( + type="line", + x0=-0.5, # start slightly before the first bar + x1=len(versions) - 0.5, # end slightly after the last bar + y0=av_s_per_100_steps_10_nodes_benchmark_threshold, + y1=av_s_per_100_steps_10_nodes_benchmark_threshold, + line=dict( + color=benchmark_line_color, + width=2, + dash="dot", + ), + ) + + fig.update_layout( + xaxis_title="PrimAITE Version", + yaxis_title="Avg Time per 100 Steps on 10 Nodes (seconds)", + yaxis=dict(range=[0, max_y_axis_value]), + title=title, + ) + + return fig + + +def build_benchmark_md_report( benchmark_start_time: datetime, session_metadata: Dict, config_path: Path, results_root_path: Path ) -> None: - """Generates a latex report of the benchmark run.""" + """ + Generates a Markdown report for a benchmarking session, documenting performance metrics and graphs. + + This function orchestrates the creation of several graphs depicting various performance benchmarks and aggregates + them into a markdown document that includes comprehensive system and benchmark information. + + :param benchmark_start_time: The datetime object representing when the benchmarking process was initiated. + :param session_metadata: A dictionary containing metadata for each benchmarking session. + :param config_path: A pathlib.Path object pointing to the configuration file used for the benchmark sessions. + :param results_root_path: A pathlib.Path object pointing to the directory where the results and graphs should be + saved. + """ # generate report folder v_str = f"v{primaite.__version__}" @@ -208,98 +336,91 @@ def build_benchmark_latex_report( fig = _plot_all_benchmarks_combined_session_av(results_directory=results_root_path) - all_version_plot_path = results_root_path / "PrimAITE Versions Learning Benchmark.png" + filename = f"PrimAITE Learning Benchmark of Minor and Bugfix Releases for Major Version {major_v}.png" + + all_version_plot_path = version_result_dir / filename fig.write_image(all_version_plot_path) - geometry_options = {"tmargin": "2.5cm", "rmargin": "2.5cm", "bmargin": "2.5cm", "lmargin": "2.5cm"} + performance_benchmark_dict = _get_performance_benchmark_for_all_version_dict(results_directory=results_root_path) + fig = _plot_av_s_per_100_steps_10_nodes(performance_benchmark_dict) + filename = f"PrimAITE Performance of Minor and Bugfix Releases for Major Version {major_v}.png" + performance_benchmark_plot_path = version_result_dir / filename + fig.write_image(performance_benchmark_plot_path) + data = benchmark_metadata_dict primaite_version = data["primaite_version"] - # Create a new document - doc = Document("report", geometry_options=geometry_options) - # Title - doc.preamble.append(Command("title", f"PrimAITE {primaite_version} Learning Benchmark")) - doc.preamble.append(Command("author", "PrimAITE Dev Team")) - doc.preamble.append(Command("date", datetime.now().date())) - doc.append(Command("maketitle")) + with open(version_result_dir / f"PrimAITE v{primaite_version} Benchmark Report.md", "w") as file: + # Title + file.write(f"# PrimAITE v{primaite_version} Learning Benchmark\n") + file.write("## PrimAITE Dev Team\n") + file.write(f"### {datetime.now().date()}\n") + file.write("\n---\n") - sessions = data["total_sessions"] - episodes = session_metadata[1]["total_episodes"] - 1 - steps = data["config"]["game"]["max_episode_length"] + sessions = data["total_sessions"] + episodes = session_metadata[1]["total_episodes"] - 1 + steps = data["config"]["game"]["max_episode_length"] - # Body - with doc.create(Section("Introduction")): - doc.append( + # Body + file.write("## 1 Introduction\n") + file.write( f"PrimAITE v{primaite_version} was benchmarked automatically upon release. Learning rate metrics " - f"were captured to be referenced during system-level testing and user acceptance testing (UAT)." + f"were captured to be referenced during system-level testing and user acceptance testing (UAT).\n" ) - doc.append( - f"\nThe benchmarking process consists of running {sessions} training session using the same " + file.write( + f"The benchmarking process consists of running {sessions} training session using the same " f"config file. Each session trains an agent for {episodes} episodes, " - f"with each episode consisting of {steps} steps." + f"with each episode consisting of {steps} steps.\n" ) - doc.append( - f"\nThe total reward per episode from each session is captured. This is then used to calculate an " + file.write( + f"The total reward per episode from each session is captured. This is then used to calculate an " f"caverage total reward per episode from the {sessions} individual sessions for smoothing. " f"Finally, a 25-widow rolling average of the average total reward per session is calculated for " - f"further smoothing." + f"further smoothing.\n" ) - with doc.create(Section("System Information")): - with doc.create(Subsection("Python")): - with doc.create(Tabular("|l|l|")) as table: - table.add_hline() - table.add_row((bold("Version"), sys.version)) - table.add_hline() + file.write("## 2 System Information\n") + i = 1 + file.write(f"### 2.{i} Python\n") + file.write(f"**Version:** {sys.version}\n") + for section, section_data in data["system_info"].items(): + i += 1 if section_data: - with doc.create(Subsection(section)): - if isinstance(section_data, dict): - with doc.create(Tabular("|l|l|")) as table: - table.add_hline() - for key, value in section_data.items(): - table.add_row((bold(key), value)) - table.add_hline() - elif isinstance(section_data, list): - headers = section_data[0].keys() - tabs_str = "|".join(["l" for _ in range(len(headers))]) - tabs_str = f"|{tabs_str}|" - with doc.create(Tabular(tabs_str)) as table: - table.add_hline() - table.add_row([bold(h) for h in headers]) - table.add_hline() - for item in section_data: - table.add_row(item.values()) - table.add_hline() + file.write(f"### 2.{i} {section}\n") + if isinstance(section_data, dict): + for key, value in section_data.items(): + file.write(f"- **{key}:** {value}\n") - headers_map = { - "total_sessions": "Total Sessions", - "total_episodes": "Total Episodes", - "total_time_steps": "Total Steps", - "av_s_per_session": "Av Session Duration (s)", - "av_s_per_step": "Av Step Duration (s)", - "av_s_per_100_steps_10_nodes": "Av Duration per 100 Steps per 10 Nodes (s)", - } - with doc.create(Section("Stats")): - with doc.create(Subsection("Benchmark Results")): - with doc.create(Tabular("|l|l|")) as table: - table.add_hline() - for section, header in headers_map.items(): - if section.startswith("av_"): - table.add_row((bold(header), f"{data[section]:.4f}")) - else: - table.add_row((bold(header), data[section])) - table.add_hline() + headers_map = { + "total_sessions": "Total Sessions", + "total_episodes": "Total Episodes", + "total_time_steps": "Total Steps", + "av_s_per_session": "Av Session Duration (s)", + "av_s_per_step": "Av Step Duration (s)", + "av_s_per_100_steps_10_nodes": "Av Duration per 100 Steps per 10 Nodes (s)", + } - with doc.create(Section("Graphs")): - with doc.create(Subsection(f"v{primaite_version} Learning Benchmark Plot")): - with doc.create(LatexFigure(position="h!")) as pic: - pic.add_image(str(this_version_plot_path)) - pic.add_caption(f"PrimAITE {primaite_version} Learning Benchmark Plot") + file.write("## 3 Stats\n") + for section, header in headers_map.items(): + if section.startswith("av_"): + file.write(f"- **{header}:** {data[section]:.4f}\n") + else: + file.write(f"- **{header}:** {data[section]}\n") - with doc.create(Subsection(f"Learning Benchmarking of All Released Versions under Major v{major_v}.*.*")): - with doc.create(LatexFigure(position="h!")) as pic: - pic.add_image(str(all_version_plot_path)) - pic.add_caption(f"Learning Benchmarking of All Released Versions under Major v{major_v}.*.*") + file.write("## 4 Graphs\n") - doc.generate_pdf(str(this_version_plot_path).replace(".png", ""), clean_tex=True) + file.write(f"### 4.1 v{primaite_version} Learning Benchmark Plot\n") + file.write(f"![PrimAITE {primaite_version} Learning Benchmark Plot]({this_version_plot_path.name})\n") + + file.write(f"### 4.2 Learning Benchmark of Minor and Bugfix Releases for Major Version {major_v}\n") + file.write( + f"![Learning Benchmark of Minor and Bugfix Releases for Major Version {major_v}]" + f"({all_version_plot_path.name})\n" + ) + + file.write(f"### 4.3 Performance of Minor and Bugfix Releases for Major Version {major_v}\n") + file.write( + f"![Performance of Minor and Bugfix Releases for Major Version {major_v}]" + f"({performance_benchmark_plot_path.name})\n" + ) diff --git 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+ }, + "56": { + "action": "ROUTER_ACL_REMOVERULE", + "options": { + "target_router_nodename": "router_1", + "position": 4 + } + }, + "57": { + "action": "ROUTER_ACL_REMOVERULE", + "options": { + "target_router_nodename": "router_1", + "position": 5 + } + }, + "58": { + "action": "ROUTER_ACL_REMOVERULE", + "options": { + "target_router_nodename": "router_1", + "position": 6 + } + }, + "59": { + "action": "ROUTER_ACL_REMOVERULE", + "options": { + "target_router_nodename": "router_1", + "position": 7 + } + }, + "60": { + "action": "ROUTER_ACL_REMOVERULE", + "options": { + "target_router_nodename": "router_1", + "position": 8 + } + }, + "61": { + "action": "ROUTER_ACL_REMOVERULE", + "options": { + "target_router_nodename": "router_1", + "position": 9 + } + }, + "62": { + "action": "HOST_NIC_DISABLE", + "options": { + "node_id": 0, + "nic_id": 0 + } + }, + "63": { + "action": "HOST_NIC_ENABLE", + "options": { + "node_id": 0, + "nic_id": 0 + } + }, + "64": { + "action": "HOST_NIC_DISABLE", + "options": { + "node_id": 1, + "nic_id": 0 + } + }, + "65": { + "action": "HOST_NIC_ENABLE", + "options": { + "node_id": 1, + "nic_id": 0 + } + }, + "66": { + "action": "HOST_NIC_DISABLE", + "options": { + "node_id": 2, + "nic_id": 0 + } + }, + "67": { + "action": "HOST_NIC_ENABLE", + "options": { + "node_id": 2, + "nic_id": 0 + } + }, + "68": { + "action": "HOST_NIC_DISABLE", + "options": { + "node_id": 3, + "nic_id": 0 + } + }, + "69": { + "action": "HOST_NIC_ENABLE", + "options": { + "node_id": 3, + "nic_id": 0 + } + }, + "70": { + "action": "HOST_NIC_DISABLE", + "options": { + "node_id": 4, + "nic_id": 0 + } + }, + "71": { + "action": "HOST_NIC_ENABLE", + "options": { + "node_id": 4, + "nic_id": 0 + } + }, + "72": { + "action": "HOST_NIC_DISABLE", + "options": { + "node_id": 4, + "nic_id": 1 + } + }, + "73": { + "action": "HOST_NIC_ENABLE", + "options": { + "node_id": 4, + "nic_id": 1 + } + }, + "74": { + "action": "HOST_NIC_DISABLE", + "options": { + "node_id": 5, + "nic_id": 0 + } + }, + "75": { + "action": "HOST_NIC_ENABLE", + "options": { + "node_id": 5, + "nic_id": 0 + } + }, + "76": { + "action": "HOST_NIC_DISABLE", + "options": { + "node_id": 6, + "nic_id": 0 + } + }, + "77": { + "action": "HOST_NIC_ENABLE", + "options": { + "node_id": 6, + "nic_id": 0 + } + } + }, + "options": { + "nodes": [ + { + "node_name": "domain_controller" + }, + { + "node_name": "web_server", + "applications": [ + { + "application_name": "DatabaseClient" + } + ], + "services": [ + { + "service_name": "WebServer" + } + ] + }, + { + "node_name": "database_server", + "folders": [ + { + "folder_name": "database", + "files": [ + { + "file_name": "database.db" + } + ] + } + ], + "services": [ + { + "service_name": "DatabaseService" + } + ] + }, + { + "node_name": "backup_server" + }, + { + "node_name": "security_suite" + }, + { + "node_name": "client_1" + }, + { + "node_name": "client_2" + } + ], + "max_folders_per_node": 2, + "max_files_per_folder": 2, + "max_services_per_node": 2, + "max_nics_per_node": 8, + "max_acl_rules": 10, + "ip_list": [ + "192.168.1.10", + "192.168.1.12", + "192.168.1.14", + "192.168.1.16", + "192.168.1.110", + "192.168.10.21", + "192.168.10.22", + "192.168.10.110" + ] + } + }, + "reward_function": { + "reward_components": [ + { + "type": "DATABASE_FILE_INTEGRITY", + "weight": 0.4, + "options": { + "node_hostname": "database_server", + "folder_name": "database", + "file_name": "database.db" + } + }, + { + "type": "SHARED_REWARD", + "weight": 1.0, + "options": { + "agent_name": "client_1_green_user" + } + }, + { + "type": "SHARED_REWARD", + "weight": 1.0, + "options": { + "agent_name": "client_2_green_user" + } + } + ] + }, + "agent_settings": { + "flatten_obs": true + } + } + ], + "simulation": { + "network": { + "nmne_config": { + "capture_nmne": true, + "nmne_capture_keywords": [ + "DELETE" + ] + }, + "nodes": [ + { + "hostname": "router_1", + "type": "router", + "num_ports": 5, + "ports": { + "1": { + "ip_address": "192.168.1.1", + "subnet_mask": "255.255.255.0" + }, + "2": { + "ip_address": "192.168.10.1", + "subnet_mask": "255.255.255.0" + } + }, + "acl": { + "18": { + "action": "PERMIT", + "src_port": "POSTGRES_SERVER", + "dst_port": "POSTGRES_SERVER" + }, + "19": { + "action": "PERMIT", + "src_port": "DNS", + "dst_port": "DNS" + }, + "20": { + "action": "PERMIT", + "src_port": "FTP", + "dst_port": "FTP" + }, + "21": { + "action": "PERMIT", + "src_port": "HTTP", + "dst_port": "HTTP" + }, + "22": { + "action": "PERMIT", + "src_port": "ARP", + "dst_port": "ARP" + }, + "23": { + "action": "PERMIT", + "protocol": "ICMP" + } + } + }, + { + "hostname": "switch_1", + "type": "switch", + "num_ports": 8 + }, + { + "hostname": "switch_2", + "type": "switch", + "num_ports": 8 + }, + { + "hostname": "domain_controller", + "type": "server", + "ip_address": "192.168.1.10", + "subnet_mask": "255.255.255.0", + "default_gateway": "192.168.1.1", + "services": [ + { + "type": "DNSServer", + "options": { + "domain_mapping": { + "arcd.com": "192.168.1.12" + } + } + } + ] + }, + { + "hostname": "web_server", + "type": "server", + "ip_address": "192.168.1.12", + "subnet_mask": "255.255.255.0", + "default_gateway": "192.168.1.1", + "dns_server": "192.168.1.10", + "services": [ + { + "type": "WebServer" + } + ], + "applications": [ + { + "type": "DatabaseClient", + "options": { + "db_server_ip": "192.168.1.14" + } + } + ] + }, + { + "hostname": "database_server", + "type": "server", + "ip_address": "192.168.1.14", + "subnet_mask": "255.255.255.0", + "default_gateway": "192.168.1.1", + "dns_server": "192.168.1.10", + "services": [ + { + "type": "DatabaseService", + "options": { + "backup_server_ip": "192.168.1.16" + } + }, + { + "type": "FTPClient" + } + ] + }, + { + "hostname": "backup_server", + "type": "server", + "ip_address": "192.168.1.16", + "subnet_mask": "255.255.255.0", + "default_gateway": "192.168.1.1", + "dns_server": "192.168.1.10", + "services": [ + { + "type": "FTPServer" + } + ] + }, + { + "hostname": "security_suite", + "type": "server", + "ip_address": "192.168.1.110", + "subnet_mask": "255.255.255.0", + "default_gateway": "192.168.1.1", + "dns_server": "192.168.1.10", + "network_interfaces": { + "2": { + "ip_address": "192.168.10.110", + "subnet_mask": "255.255.255.0" + } + } + }, + { + "hostname": "client_1", + "type": "computer", + "ip_address": "192.168.10.21", + "subnet_mask": "255.255.255.0", + "default_gateway": "192.168.10.1", + "dns_server": "192.168.1.10", + "applications": [ + { + "type": "DataManipulationBot", + "options": { + "port_scan_p_of_success": 0.8, + "data_manipulation_p_of_success": 0.8, + "payload": "DELETE", + "server_ip": "192.168.1.14" + } + }, + { + "type": "WebBrowser", + "options": { + "target_url": "http://arcd.com/users/" + } + }, + { + "type": "DatabaseClient", + "options": { + "db_server_ip": "192.168.1.14" + } + } + ], + "services": [ + { + "type": "DNSClient" + } + ] + }, + { + "hostname": "client_2", + "type": "computer", + "ip_address": "192.168.10.22", + "subnet_mask": "255.255.255.0", + "default_gateway": "192.168.10.1", + "dns_server": "192.168.1.10", + "applications": [ + { + "type": "WebBrowser", + "options": { + "target_url": "http://arcd.com/users/" + } + }, + { + "type": "DataManipulationBot", + "options": { + "port_scan_p_of_success": 0.8, + "data_manipulation_p_of_success": 0.8, + "payload": "DELETE", + "server_ip": "192.168.1.14" + } + }, + { + "type": "DatabaseClient", + "options": { + "db_server_ip": "192.168.1.14" + } + } + ], + "services": [ + { + "type": "DNSClient" + } + ] + } + ], + "links": [ + { + "endpoint_a_hostname": "router_1", + "endpoint_a_port": 1, + "endpoint_b_hostname": "switch_1", + "endpoint_b_port": 8 + }, + { + "endpoint_a_hostname": "router_1", + "endpoint_a_port": 2, + "endpoint_b_hostname": "switch_2", + "endpoint_b_port": 8 + }, + { + "endpoint_a_hostname": "switch_1", + "endpoint_a_port": 1, + "endpoint_b_hostname": "domain_controller", + "endpoint_b_port": 1 + }, + { + "endpoint_a_hostname": "switch_1", + "endpoint_a_port": 2, + "endpoint_b_hostname": "web_server", + "endpoint_b_port": 1 + }, + { + "endpoint_a_hostname": "switch_1", + "endpoint_a_port": 3, + "endpoint_b_hostname": "database_server", + "endpoint_b_port": 1 + }, + { + "endpoint_a_hostname": "switch_1", + "endpoint_a_port": 4, + "endpoint_b_hostname": "backup_server", + "endpoint_b_port": 1 + }, + { + "endpoint_a_hostname": "switch_1", + "endpoint_a_port": 7, + "endpoint_b_hostname": "security_suite", + "endpoint_b_port": 1 + }, + { + "endpoint_a_hostname": "switch_2", + "endpoint_a_port": 1, + "endpoint_b_hostname": "client_1", + "endpoint_b_port": 1 + }, + { + "endpoint_a_hostname": "switch_2", + "endpoint_a_port": 2, + "endpoint_b_hostname": "client_2", + "endpoint_b_port": 1 + }, + { + "endpoint_a_hostname": "switch_2", + "endpoint_a_port": 7, + "endpoint_b_hostname": "security_suite", + "endpoint_b_port": 2 + } + ] + } + } + } +} \ No newline at end of file From fba85cebfdd0e76ca8451967fe0c485ac3bc620b Mon Sep 17 00:00:00 2001 From: Chris McCarthy Date: Sat, 20 Jul 2024 17:15:53 +0100 Subject: [PATCH 3/4] retrospectively benchmarked 3.1.0 using the new benchmark process --- .azure/azure-benchmark-pipeline.yaml | 108 + benchmark/primaite_benchmark.py | 8 +- benchmark/report.py | 301 +- .../PrimAITE Versions Learning Benchmark.png | Bin 92918 -> 0 bytes ...nd Bugfix Releases for Major Version 3.png | Bin 0 -> 106039 bytes ...nd Bugfix Releases for Major Version 3.png | Bin 0 -> 61092 bytes .../PrimAITE v3.0.0 Benchmark Report.md | 38 + .../PrimAITE v3.0.0 Learning Benchmark.pdf | Bin 348917 -> 0 bytes .../PrimAITE v3.0.0 Learning Benchmark.png | Bin 302436 -> 323050 bytes .../results/v3/v3.0.0/session_metadata/1.json | 1009 ++ .../results/v3/v3.0.0/session_metadata/2.json | 1009 ++ .../results/v3/v3.0.0/session_metadata/3.json | 1009 ++ .../results/v3/v3.0.0/session_metadata/4.json | 1009 ++ .../results/v3/v3.0.0/session_metadata/5.json | 1009 ++ .../v3/v3.0.0/v3.0.0_benchmark_metadata.json | 12032 ++++++++-------- 15 files changed, 11422 insertions(+), 6110 deletions(-) create mode 100644 .azure/azure-benchmark-pipeline.yaml delete mode 100644 benchmark/results/v3/PrimAITE Versions Learning Benchmark.png create mode 100644 benchmark/results/v3/v3.0.0/PrimAITE Learning Benchmark of Minor and Bugfix Releases for Major Version 3.png create mode 100644 benchmark/results/v3/v3.0.0/PrimAITE Performance of Minor and Bugfix Releases for Major Version 3.png create mode 100644 benchmark/results/v3/v3.0.0/PrimAITE v3.0.0 Benchmark Report.md delete mode 100644 benchmark/results/v3/v3.0.0/PrimAITE v3.0.0 Learning Benchmark.pdf create mode 100644 benchmark/results/v3/v3.0.0/session_metadata/1.json create mode 100644 benchmark/results/v3/v3.0.0/session_metadata/2.json create mode 100644 benchmark/results/v3/v3.0.0/session_metadata/3.json create mode 100644 benchmark/results/v3/v3.0.0/session_metadata/4.json create mode 100644 benchmark/results/v3/v3.0.0/session_metadata/5.json diff --git a/.azure/azure-benchmark-pipeline.yaml b/.azure/azure-benchmark-pipeline.yaml new file mode 100644 index 00000000..44010cac --- /dev/null +++ b/.azure/azure-benchmark-pipeline.yaml @@ -0,0 +1,108 @@ +trigger: +- release/* + +schedules: +- cron: "0 2 * * 1-5" # Run at 2 AM every weekday + displayName: "Weekday Schedule" + branches: + include: + - 'refs/heads/dev' +variables: + VERSION: '' + MAJOR_VERSION: '' + +jobs: +- job: PrimAITE_Benchmark + timeoutInMinutes: 360 # 6-hour maximum + pool: + name: 'Imaginary Yak Pool' + workspace: + clean: all + + steps: + - checkout: self + persistCredentials: true + + - script: | + python3.10 -m venv venv + displayName: 'Create venv' + + - script: | + VERSION=$(cat src/primaite/VERSION | tr -d '\n') + if [[ "$(Build.SourceBranch)" == "refs/heads/dev" ]]; then + DATE=$(date +%Y%m%d) + echo "${VERSION}+dev.${DATE}" > src/primaite/VERSION + fi + displayName: 'Update VERSION file for Dev Benchmark' + + - script: | + VERSION=$(cat src/primaite/VERSION | tr -d '\n') + MAJOR_VERSION=$(echo $VERSION | cut -d. -f1) + echo "##vso[task.setvariable variable=VERSION]$VERSION" + echo "##vso[task.setvariable variable=MAJOR_VERSION]$MAJOR_VERSION" + displayName: 'Set Version Variables' + + - script: | + source venv/bin/activate + pip install --upgrade pip + pip install -e .[dev,rl] + primaite setup + displayName: 'Install Dependencies' + + - script: | + set -e + source venv/bin/activate + cd benchmark + python primaite_benchmark.py + cd .. + displayName: 'Run Benchmarking Script' + + - script: | + tar czf primaite_v$(VERSION)_benchmark.tar.gz benchmark/results/v$(MAJOR_VERSION)/v$(VERSION) + displayName: 'Prepare Artifacts for Publishing' + + - task: PublishPipelineArtifact@1 + inputs: + targetPath: primaite_v$(VERSION)_benchmark.tar.gz + artifactName: 'benchmark-zip-output' + publishLocation: 'pipeline' + displayName: 'Publish Benchmark Output zip as Artifact' + + - script: | + git config --global user.email "oss@dstl.gov.uk" + git config --global user.name "Defence Science and Technology Laboratory UK" + workingDirectory: $(System.DefaultWorkingDirectory) + displayName: 'Configure Git' + condition: and(succeeded(), startsWith(variables['Build.SourceBranch'], 'refs/heads/release')) + + - script: | + echo "Fetching all branches..." + git fetch --all --prune + + echo "Stashing files..." + git stash push -u + + echo "Resolving branch name..." + # Extracting just the branch name from the full ref path + branch_name=$(echo "$(Build.SourceBranch)" | sed 's|refs/heads/||') + echo "Branch Name: $branch_name" + + echo "Checking out branch $branch_name..." + git checkout $branch_name + + echo "Popping stash..." + git stash pop + + echo "Adding benchmark results..." + git add benchmark/results/v$(MAJOR_VERSION)/v$(VERSION)/* + + echo "Committing changes..." + git commit -m "Automated benchmark output commit for version $(VERSION) [skip ci]" + + echo "Pushing to remote..." + git push origin $branch_name + displayName: 'Commit and Push Benchmark Results' + workingDirectory: $(System.DefaultWorkingDirectory) + env: + GIT_CREDENTIALS: $(System.AccessToken) + condition: and(succeeded(), startsWith(variables['Build.SourceBranch'], 'refs/heads/release')) diff --git a/benchmark/primaite_benchmark.py b/benchmark/primaite_benchmark.py index b19dbb16..0e6c2acc 100644 --- a/benchmark/primaite_benchmark.py +++ b/benchmark/primaite_benchmark.py @@ -5,7 +5,7 @@ from datetime import datetime from pathlib import Path from typing import Any, Dict, Final, Tuple -from report import build_benchmark_latex_report +from report import build_benchmark_md_report from stable_baselines3 import PPO import primaite @@ -117,14 +117,14 @@ class BenchmarkSession: def generate_learn_metadata_dict(self) -> Dict[str, Any]: """Metadata specific to the learning session.""" total_s, s_per_step, s_per_100_steps_10_nodes = self._learn_benchmark_durations() - self.gym_env.average_reward_per_episode.pop(0) # remove episode 0 + self.gym_env.total_reward_per_episode.pop(0) # remove episode 0 return { "total_episodes": self.gym_env.episode_counter, "total_time_steps": self.gym_env.total_time_steps, "total_s": total_s, "s_per_step": s_per_step, "s_per_100_steps_10_nodes": s_per_100_steps_10_nodes, - "av_reward_per_episode": self.gym_env.average_reward_per_episode, + "total_reward_per_episode": self.gym_env.total_reward_per_episode, } @@ -188,7 +188,7 @@ def run( with open(_SESSION_METADATA_ROOT / f"{i}.json", "r") as file: session_metadata_dict[i] = json.load(file) # generate report - build_benchmark_latex_report( + build_benchmark_md_report( benchmark_start_time=benchmark_start_time, session_metadata=session_metadata_dict, config_path=data_manipulation_config_path(), diff --git a/benchmark/report.py b/benchmark/report.py index ca3d03a3..9c576562 100644 --- a/benchmark/report.py +++ b/benchmark/report.py @@ -9,10 +9,6 @@ import plotly.graph_objects as go import polars as pl import yaml from plotly.graph_objs import Figure -from pylatex import Command, Document -from pylatex import Figure as LatexFigure -from pylatex import Section, Subsection, Tabular -from pylatex.utils import bold from utils import _get_system_info import primaite @@ -21,10 +17,20 @@ PLOT_CONFIG = { "size": {"auto_size": False, "width": 1500, "height": 900}, "template": "plotly_white", "range_slider": False, + "av_s_per_100_steps_10_nodes_benchmark_threshold": 5, + "benchmark_line_color": "grey", } def _build_benchmark_results_dict(start_datetime: datetime, metadata_dict: Dict, config: Dict) -> dict: + """ + Constructs a dictionary aggregating benchmark results from multiple sessions. + + :param start_datetime: The datetime when the benchmarking started. + :param metadata_dict: Dictionary containing metadata for each session. + :param config: Configuration settings used during the benchmarking. + :return: A dictionary containing aggregated data and metadata from the benchmarking sessions. + """ num_sessions = len(metadata_dict) # number of sessions averaged_data = { @@ -39,24 +45,30 @@ def _build_benchmark_results_dict(start_datetime: datetime, metadata_dict: Dict, "av_s_per_step": sum(d["s_per_step"] for d in metadata_dict.values()) / num_sessions, "av_s_per_100_steps_10_nodes": sum(d["s_per_100_steps_10_nodes"] for d in metadata_dict.values()) / num_sessions, - "combined_av_reward_per_episode": {}, - "session_av_reward_per_episode": {k: v["av_reward_per_episode"] for k, v in metadata_dict.items()}, + "combined_total_reward_per_episode": {}, + "session_total_reward_per_episode": {k: v["total_reward_per_episode"] for k, v in metadata_dict.items()}, "config": config, } # find the average of each episode across all sessions - episodes = metadata_dict[1]["av_reward_per_episode"].keys() + episodes = metadata_dict[1]["total_reward_per_episode"].keys() for episode in episodes: combined_av_reward = ( - sum(metadata_dict[k]["av_reward_per_episode"][episode] for k in metadata_dict.keys()) / num_sessions + sum(metadata_dict[k]["total_reward_per_episode"][episode] for k in metadata_dict.keys()) / num_sessions ) - averaged_data["combined_av_reward_per_episode"][episode] = combined_av_reward + averaged_data["combined_total_reward_per_episode"][episode] = combined_av_reward return averaged_data def _get_df_from_episode_av_reward_dict(data: Dict) -> pl.DataFrame: + """ + Converts a dictionary of episode average rewards into a Polars DataFrame. + + :param data: Dictionary with episodes as keys and average rewards as values. + :return: Polars DataFrame with episodes and average rewards, including a rolling average. + """ data: Dict = {"episode": data.keys(), "av_reward": data.values()} return ( @@ -71,6 +83,14 @@ def _plot_benchmark_metadata( title: Optional[str] = None, subtitle: Optional[str] = None, ) -> Figure: + """ + Plots benchmark metadata as a line graph using Plotly. + + :param benchmark_metadata_dict: Dictionary containing the total reward per episode and session. + :param title: Optional title for the graph. + :param subtitle: Optional subtitle for the graph. + :return: Plotly figure object representing the benchmark metadata plot. + """ if title: if subtitle: title = f"{title}
{subtitle}" @@ -87,7 +107,7 @@ def _plot_benchmark_metadata( fig = go.Figure(layout=layout) fig.update_layout(template=PLOT_CONFIG["template"]) - for session, av_reward_dict in benchmark_metadata_dict["session_av_reward_per_episode"].items(): + for session, av_reward_dict in benchmark_metadata_dict["session_total_reward_per_episode"].items(): df = _get_df_from_episode_av_reward_dict(av_reward_dict) fig.add_trace( go.Scatter( @@ -100,7 +120,7 @@ def _plot_benchmark_metadata( ) ) - df = _get_df_from_episode_av_reward_dict(benchmark_metadata_dict["combined_av_reward_per_episode"]) + df = _get_df_from_episode_av_reward_dict(benchmark_metadata_dict["combined_total_reward_per_episode"]) fig.add_trace( go.Scatter( x=df["episode"], y=df["av_reward"], mode="lines", name="Combined Session Av", line={"color": "#FF0000"} @@ -136,11 +156,11 @@ def _plot_all_benchmarks_combined_session_av(results_directory: Path) -> Figure: Does this by iterating over the ``benchmark/results`` directory and extracting the benchmark metadata json for each version that has been - benchmarked. The combined_av_reward_per_episode is extracted from each, + benchmarked. The combined_total_reward_per_episode is extracted from each, converted into a polars dataframe, and plotted as a scatter line in plotly. """ major_v = primaite.__version__.split(".")[0] - title = f"Learning Benchmarking of All Released Versions under Major v{major_v}.*.*" + title = f"Learning Benchmark of Minor and Bugfix Releases for Major Version {major_v}" subtitle = "Rolling Av (Combined Session Av)" if title: if subtitle: @@ -162,7 +182,7 @@ def _plot_all_benchmarks_combined_session_av(results_directory: Path) -> Figure: metadata_file = dir / f"{dir.name}_benchmark_metadata.json" with open(metadata_file, "r") as file: metadata_dict = json.load(file) - df = _get_df_from_episode_av_reward_dict(metadata_dict["combined_av_reward_per_episode"]) + df = _get_df_from_episode_av_reward_dict(metadata_dict["combined_total_reward_per_episode"]) fig.add_trace(go.Scatter(x=df["episode"], y=df["rolling_av_reward"], mode="lines", name=dir.name)) @@ -180,10 +200,118 @@ def _plot_all_benchmarks_combined_session_av(results_directory: Path) -> Figure: return fig -def build_benchmark_latex_report( +def _get_performance_benchmark_for_all_version_dict(results_directory: Path) -> Dict[str, float]: + """ + Gathers performance benchmarks for all versions of the software stored in a specified directory. + + This function iterates through each directory within the specified results directory, + extracts the av_s_per_100_steps_10_nodes from the benchmark_metadata.json files, and aggregates it into a + dictionary. + + :param results_directory: The directory containing subdirectories for each version's benchmark data. + :return: A dictionary with version numbers as keys and their corresponding average performance benchmark + (average time per 100 steps on 10 nodes) as values. + """ + performance_benchmark_dict = {} + for dir in results_directory.iterdir(): + if dir.is_dir(): + metadata_file = dir / f"{dir.name}_benchmark_metadata.json" + with open(metadata_file, "r") as file: + metadata_dict = json.load(file) + version = metadata_dict["primaite_version"] + performance_benchmark_dict[version] = metadata_dict["av_s_per_100_steps_10_nodes"] + return performance_benchmark_dict + + +def _plot_av_s_per_100_steps_10_nodes( + version_times_dict: Dict[str, float], +) -> Figure: + """ + Creates a bar chart visualising the performance of each version of PrimAITE. + + Performance is based on the average training time per 100 steps on 10 nodes. The function also includes a benchmark + line indicating the target maximum time. + + Versions that perform under this time are marked in green, and those over are marked in red. + + :param version_times_dict: A dictionary with software versions as keys and average times as values. + :return: A Plotly figure object representing the bar chart of the performance metrics. + """ + major_v = primaite.__version__.split(".")[0] + title = f"Performance of Minor and Bugfix Releases for Major Version {major_v}" + subtitle = ( + f"Average Training Time per 100 Steps on 10 Nodes " + f"(target: <= {PLOT_CONFIG['av_s_per_100_steps_10_nodes_benchmark_threshold']} seconds)" + ) + title = f"{title}
{subtitle}" + + layout = go.Layout( + autosize=PLOT_CONFIG["size"]["auto_size"], + width=PLOT_CONFIG["size"]["width"], + height=PLOT_CONFIG["size"]["height"], + ) + fig = go.Figure(layout=layout) + fig.update_layout(template=PLOT_CONFIG["template"]) + + versions = sorted(list(version_times_dict.keys())) + times = [version_times_dict[version] for version in versions] + av_s_per_100_steps_10_nodes_benchmark_threshold = PLOT_CONFIG["av_s_per_100_steps_10_nodes_benchmark_threshold"] + benchmark_line_color = PLOT_CONFIG["benchmark_line_color"] + + # Calculate the appropriate maximum y-axis value + max_y_axis_value = max(max(times), av_s_per_100_steps_10_nodes_benchmark_threshold) + 1 + + fig.add_trace( + go.Bar( + x=versions, + y=times, + marker_color=[ + "green" if time < av_s_per_100_steps_10_nodes_benchmark_threshold else "red" for time in times + ], + text=times, + textposition="auto", + ) + ) + + # Add a horizontal line for the benchmark + fig.add_shape( + type="line", + x0=-0.5, # start slightly before the first bar + x1=len(versions) - 0.5, # end slightly after the last bar + y0=av_s_per_100_steps_10_nodes_benchmark_threshold, + y1=av_s_per_100_steps_10_nodes_benchmark_threshold, + line=dict( + color=benchmark_line_color, + width=2, + dash="dot", + ), + ) + + fig.update_layout( + xaxis_title="PrimAITE Version", + yaxis_title="Avg Time per 100 Steps on 10 Nodes (seconds)", + yaxis=dict(range=[0, max_y_axis_value]), + title=title, + ) + + return fig + + +def build_benchmark_md_report( benchmark_start_time: datetime, session_metadata: Dict, config_path: Path, results_root_path: Path ) -> None: - """Generates a latex report of the benchmark run.""" + """ + Generates a Markdown report for a benchmarking session, documenting performance metrics and graphs. + + This function orchestrates the creation of several graphs depicting various performance benchmarks and aggregates + them into a markdown document that includes comprehensive system and benchmark information. + + :param benchmark_start_time: The datetime object representing when the benchmarking process was initiated. + :param session_metadata: A dictionary containing metadata for each benchmarking session. + :param config_path: A pathlib.Path object pointing to the configuration file used for the benchmark sessions. + :param results_root_path: A pathlib.Path object pointing to the directory where the results and graphs should be + saved. + """ # generate report folder v_str = f"v{primaite.__version__}" @@ -208,98 +336,91 @@ def build_benchmark_latex_report( fig = _plot_all_benchmarks_combined_session_av(results_directory=results_root_path) - all_version_plot_path = results_root_path / "PrimAITE Versions Learning Benchmark.png" + filename = f"PrimAITE Learning Benchmark of Minor and Bugfix Releases for Major Version {major_v}.png" + + all_version_plot_path = version_result_dir / filename fig.write_image(all_version_plot_path) - geometry_options = {"tmargin": "2.5cm", "rmargin": "2.5cm", "bmargin": "2.5cm", "lmargin": "2.5cm"} + performance_benchmark_dict = _get_performance_benchmark_for_all_version_dict(results_directory=results_root_path) + fig = _plot_av_s_per_100_steps_10_nodes(performance_benchmark_dict) + filename = f"PrimAITE Performance of Minor and Bugfix Releases for Major Version {major_v}.png" + performance_benchmark_plot_path = version_result_dir / filename + fig.write_image(performance_benchmark_plot_path) + data = benchmark_metadata_dict primaite_version = data["primaite_version"] - # Create a new document - doc = Document("report", geometry_options=geometry_options) - # Title - doc.preamble.append(Command("title", f"PrimAITE {primaite_version} Learning Benchmark")) - doc.preamble.append(Command("author", "PrimAITE Dev Team")) - doc.preamble.append(Command("date", datetime.now().date())) - doc.append(Command("maketitle")) + with open(version_result_dir / f"PrimAITE v{primaite_version} Benchmark Report.md", "w") as file: + # Title + file.write(f"# PrimAITE v{primaite_version} Learning Benchmark\n") + file.write("## PrimAITE Dev Team\n") + file.write(f"### {datetime.now().date()}\n") + file.write("\n---\n") - sessions = data["total_sessions"] - episodes = session_metadata[1]["total_episodes"] - 1 - steps = data["config"]["game"]["max_episode_length"] + sessions = data["total_sessions"] + episodes = session_metadata[1]["total_episodes"] - 1 + steps = data["config"]["game"]["max_episode_length"] - # Body - with doc.create(Section("Introduction")): - doc.append( + # Body + file.write("## 1 Introduction\n") + file.write( f"PrimAITE v{primaite_version} was benchmarked automatically upon release. Learning rate metrics " - f"were captured to be referenced during system-level testing and user acceptance testing (UAT)." + f"were captured to be referenced during system-level testing and user acceptance testing (UAT).\n" ) - doc.append( - f"\nThe benchmarking process consists of running {sessions} training session using the same " + file.write( + f"The benchmarking process consists of running {sessions} training session using the same " f"config file. Each session trains an agent for {episodes} episodes, " - f"with each episode consisting of {steps} steps." + f"with each episode consisting of {steps} steps.\n" ) - doc.append( - f"\nThe total reward per episode from each session is captured. This is then used to calculate an " + file.write( + f"The total reward per episode from each session is captured. This is then used to calculate an " f"caverage total reward per episode from the {sessions} individual sessions for smoothing. " f"Finally, a 25-widow rolling average of the average total reward per session is calculated for " - f"further smoothing." + f"further smoothing.\n" ) - with doc.create(Section("System Information")): - with doc.create(Subsection("Python")): - with doc.create(Tabular("|l|l|")) as table: - table.add_hline() - table.add_row((bold("Version"), sys.version)) - table.add_hline() + file.write("## 2 System Information\n") + i = 1 + file.write(f"### 2.{i} Python\n") + file.write(f"**Version:** {sys.version}\n") + for section, section_data in data["system_info"].items(): + i += 1 if section_data: - with doc.create(Subsection(section)): - if isinstance(section_data, dict): - with doc.create(Tabular("|l|l|")) as table: - table.add_hline() - for key, value in section_data.items(): - table.add_row((bold(key), value)) - table.add_hline() - elif isinstance(section_data, list): - headers = section_data[0].keys() - tabs_str = "|".join(["l" for _ in range(len(headers))]) - tabs_str = f"|{tabs_str}|" - with doc.create(Tabular(tabs_str)) as table: - table.add_hline() - table.add_row([bold(h) for h in headers]) - table.add_hline() - for item in section_data: - table.add_row(item.values()) - table.add_hline() + file.write(f"### 2.{i} {section}\n") + if isinstance(section_data, dict): + for key, value in section_data.items(): + file.write(f"- **{key}:** {value}\n") - headers_map = { - "total_sessions": "Total Sessions", - "total_episodes": "Total Episodes", - "total_time_steps": "Total Steps", - "av_s_per_session": "Av Session Duration (s)", - "av_s_per_step": "Av Step Duration (s)", - "av_s_per_100_steps_10_nodes": "Av Duration per 100 Steps per 10 Nodes (s)", - } - with doc.create(Section("Stats")): - with doc.create(Subsection("Benchmark Results")): - with doc.create(Tabular("|l|l|")) as table: - table.add_hline() - for section, header in headers_map.items(): - if section.startswith("av_"): - table.add_row((bold(header), f"{data[section]:.4f}")) - else: - table.add_row((bold(header), data[section])) - table.add_hline() + headers_map = { + "total_sessions": "Total Sessions", + "total_episodes": "Total Episodes", + "total_time_steps": "Total Steps", + "av_s_per_session": "Av Session Duration (s)", + "av_s_per_step": "Av Step Duration (s)", + "av_s_per_100_steps_10_nodes": "Av Duration per 100 Steps per 10 Nodes (s)", + } - with doc.create(Section("Graphs")): - with doc.create(Subsection(f"v{primaite_version} Learning Benchmark Plot")): - with doc.create(LatexFigure(position="h!")) as pic: - pic.add_image(str(this_version_plot_path)) - pic.add_caption(f"PrimAITE {primaite_version} Learning Benchmark Plot") + file.write("## 3 Stats\n") + for section, header in headers_map.items(): + if section.startswith("av_"): + file.write(f"- **{header}:** {data[section]:.4f}\n") + else: + file.write(f"- **{header}:** {data[section]}\n") - with doc.create(Subsection(f"Learning Benchmarking of All Released Versions under Major v{major_v}.*.*")): - with doc.create(LatexFigure(position="h!")) as pic: - pic.add_image(str(all_version_plot_path)) - pic.add_caption(f"Learning Benchmarking of All Released Versions under Major v{major_v}.*.*") + file.write("## 4 Graphs\n") - doc.generate_pdf(str(this_version_plot_path).replace(".png", ""), clean_tex=True) + file.write(f"### 4.1 v{primaite_version} Learning Benchmark Plot\n") + file.write(f"![PrimAITE {primaite_version} Learning Benchmark Plot]({this_version_plot_path.name})\n") + + file.write(f"### 4.2 Learning Benchmark of Minor and Bugfix Releases for Major Version {major_v}\n") + file.write( + f"![Learning Benchmark of Minor and Bugfix Releases for Major Version {major_v}]" + f"({all_version_plot_path.name})\n" + ) + + file.write(f"### 4.3 Performance of Minor and Bugfix Releases for Major Version {major_v}\n") + file.write( + f"![Performance of Minor and Bugfix Releases for Major Version {major_v}]" + f"({performance_benchmark_plot_path.name})\n" + ) diff --git 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"hostname": "security_suite" + }, + { + "hostname": "client_1" + }, + { + "hostname": "client_2" + } + ], + "num_services": 1, + "num_applications": 0, + "num_folders": 1, + "num_files": 1, + "num_nics": 2, + "include_num_access": false, + "include_nmne": true, + "monitored_traffic": { + "icmp": [ + "NONE" + ], + "tcp": [ + "DNS" + ] + }, + "routers": [ + { + "hostname": "router_1" + } + ], + "num_ports": 0, + "ip_list": [ + "192.168.1.10", + "192.168.1.12", + "192.168.1.14", + "192.168.1.16", + "192.168.1.110", + "192.168.10.21", + "192.168.10.22", + "192.168.10.110" + ], + "wildcard_list": [ + "0.0.0.1" + ], + "port_list": [ + 80, + 5432 + ], + "protocol_list": [ + "ICMP", + "TCP", + "UDP" + ], + "num_rules": 10 + } + }, + { + "type": "LINKS", + "label": "LINKS", + "options": { + "link_references": [ + "router_1:eth-1<->switch_1:eth-8", + "router_1:eth-2<->switch_2:eth-8", + "switch_1:eth-1<->domain_controller:eth-1", + "switch_1:eth-2<->web_server:eth-1", + 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"type": "NODE_FOLDER_CHECKHASH" + }, + { + "type": "NODE_FOLDER_REPAIR" + }, + { + "type": "NODE_FOLDER_RESTORE" + }, + { + "type": "NODE_OS_SCAN" + }, + { + "type": "NODE_SHUTDOWN" + }, + { + "type": "NODE_STARTUP" + }, + { + "type": "NODE_RESET" + }, + { + "type": "ROUTER_ACL_ADDRULE" + }, + { + "type": "ROUTER_ACL_REMOVERULE" + }, + { + "type": "HOST_NIC_ENABLE" + }, + { + "type": "HOST_NIC_DISABLE" + } + ], + "action_map": { + "0": { + "action": "DONOTHING", + "options": {} + }, + "1": { + "action": "NODE_SERVICE_SCAN", + "options": { + "node_id": 1, + "service_id": 0 + } + }, + "2": { + "action": "NODE_SERVICE_STOP", + "options": { + "node_id": 1, + "service_id": 0 + } + }, + "3": { + "action": "NODE_SERVICE_START", + "options": { + "node_id": 1, + "service_id": 0 + } + }, + "4": { + "action": "NODE_SERVICE_PAUSE", + "options": { + "node_id": 1, + "service_id": 0 + } + }, + "5": { + "action": "NODE_SERVICE_RESUME", + "options": { + "node_id": 1, + "service_id": 0 + } + }, + "6": { 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"position": 6, + "permission": 2, + "source_ip_id": 8, + "dest_ip_id": 4, + "source_port_id": 1, + "dest_port_id": 1, + "protocol_id": 3, + "source_wildcard_id": 0, + "dest_wildcard_id": 0 + } + }, + "52": { + "action": "ROUTER_ACL_REMOVERULE", + "options": { + "target_router": "router_1", + "position": 0 + } + }, + "53": { + "action": "ROUTER_ACL_REMOVERULE", + "options": { + "target_router": "router_1", + "position": 1 + } + }, + "54": { + "action": "ROUTER_ACL_REMOVERULE", + "options": { + "target_router": "router_1", + "position": 2 + } + }, + "55": { + "action": "ROUTER_ACL_REMOVERULE", + "options": { + "target_router": "router_1", + "position": 3 + } + }, + "56": { + "action": "ROUTER_ACL_REMOVERULE", + "options": { + "target_router": "router_1", + "position": 4 + } + }, + "57": { + "action": "ROUTER_ACL_REMOVERULE", + "options": { + "target_router": "router_1", + "position": 5 + } + }, + "58": { + "action": "ROUTER_ACL_REMOVERULE", + "options": { + "target_router": "router_1", + "position": 6 + } + }, + "59": { + "action": "ROUTER_ACL_REMOVERULE", + "options": { + "target_router": "router_1", + "position": 7 + } + }, + "60": { + "action": "ROUTER_ACL_REMOVERULE", + "options": { + "target_router": "router_1", + "position": 8 + } + }, + "61": { + "action": "ROUTER_ACL_REMOVERULE", + "options": { + "target_router": "router_1", + "position": 9 + } + }, + "62": { + "action": "HOST_NIC_DISABLE", + "options": { + "node_id": 0, + "nic_id": 0 + } + }, + "63": { + "action": "HOST_NIC_ENABLE", + "options": { + "node_id": 0, + "nic_id": 0 + } + }, + "64": { + "action": "HOST_NIC_DISABLE", + "options": { + "node_id": 1, + "nic_id": 0 + } + }, + "65": { + "action": "HOST_NIC_ENABLE", + "options": { + "node_id": 1, + "nic_id": 0 + } + }, + "66": { + "action": "HOST_NIC_DISABLE", + "options": { + "node_id": 2, + "nic_id": 0 + } + }, + "67": { + "action": "HOST_NIC_ENABLE", + "options": { + "node_id": 2, + "nic_id": 0 + } + }, + "68": { + "action": "HOST_NIC_DISABLE", + "options": { + "node_id": 3, + "nic_id": 0 + } + }, + "69": { + "action": "HOST_NIC_ENABLE", + "options": { + "node_id": 3, + "nic_id": 0 + } + }, + "70": { + "action": "HOST_NIC_DISABLE", + "options": { + "node_id": 4, + "nic_id": 0 + } + }, + "71": { + "action": "HOST_NIC_ENABLE", + "options": { + "node_id": 4, + "nic_id": 0 + } + }, + "72": { + "action": "HOST_NIC_DISABLE", + "options": { + "node_id": 4, + "nic_id": 1 + } + }, + "73": { + "action": "HOST_NIC_ENABLE", + "options": { + "node_id": 4, + "nic_id": 1 + } + }, + "74": { + "action": "HOST_NIC_DISABLE", + "options": { + "node_id": 5, + "nic_id": 0 + } + }, + "75": { + "action": "HOST_NIC_ENABLE", + "options": { + "node_id": 5, + "nic_id": 0 + } + }, + "76": { + "action": "HOST_NIC_DISABLE", + "options": { + "node_id": 6, + "nic_id": 0 + } + }, + "77": { + "action": "HOST_NIC_ENABLE", + "options": { + "node_id": 6, + "nic_id": 0 + } + } + }, + "options": { + "nodes": [ + { + "node_name": "domain_controller" + }, + { + "node_name": "web_server", + "applications": [ + { + "application_name": "DatabaseClient" + } + ], + "services": [ + { + "service_name": "WebServer" + } + ] + }, + { + "node_name": "database_server", + "folders": [ + { + "folder_name": "database", + "files": [ + { + "file_name": "database.db" + } + ] + } + ], + "services": [ + { + "service_name": "DatabaseService" + } + ] + }, + { + "node_name": "backup_server" + }, + { + "node_name": "security_suite" + }, + { + "node_name": "client_1" + }, + { + "node_name": "client_2" + } + ], + "max_folders_per_node": 2, + "max_files_per_folder": 2, + "max_services_per_node": 2, + "max_nics_per_node": 8, + "max_acl_rules": 10, + "ip_list": [ + "192.168.1.10", + "192.168.1.12", + "192.168.1.14", + "192.168.1.16", + "192.168.1.110", + "192.168.10.21", + "192.168.10.22", + "192.168.10.110" + ] + } + }, + "reward_function": { + "reward_components": [ + { + "type": "DATABASE_FILE_INTEGRITY", + "weight": 0.4, + "options": { + "node_hostname": "database_server", + "folder_name": "database", + "file_name": "database.db" + } + }, + { + "type": "SHARED_REWARD", + "weight": 1.0, + "options": { + "agent_name": "client_1_green_user" + } + }, + { + "type": "SHARED_REWARD", + "weight": 1.0, + "options": { + "agent_name": "client_2_green_user" + } + } + ] + }, + "agent_settings": { + "flatten_obs": true + } + } + ], + "simulation": { + "network": { + "nmne_config": { + "capture_nmne": true, + "nmne_capture_keywords": [ + "DELETE" + ] + }, + "nodes": [ + { + "hostname": "router_1", + "type": "router", + "num_ports": 5, + "ports": { + "1": { + "ip_address": "192.168.1.1", + "subnet_mask": "255.255.255.0" + }, + "2": { + "ip_address": "192.168.10.1", + "subnet_mask": "255.255.255.0" + } + }, + "acl": { + "18": { + "action": "PERMIT", + "src_port": "POSTGRES_SERVER", + "dst_port": "POSTGRES_SERVER" + }, + "19": { + "action": "PERMIT", + "src_port": "DNS", + "dst_port": "DNS" + }, + "20": { + "action": "PERMIT", + "src_port": "FTP", + "dst_port": "FTP" + }, + "21": { + "action": "PERMIT", + "src_port": "HTTP", + "dst_port": "HTTP" + }, + "22": { + "action": "PERMIT", + "src_port": "ARP", + "dst_port": "ARP" + }, + "23": { + "action": "PERMIT", + "protocol": "ICMP" + } + } + }, + { + "hostname": "switch_1", + "type": "switch", + "num_ports": 8 + }, + { + "hostname": "switch_2", + "type": "switch", + "num_ports": 8 + }, + { + "hostname": "domain_controller", + "type": "server", + "ip_address": "192.168.1.10", + "subnet_mask": "255.255.255.0", + "default_gateway": "192.168.1.1", + "services": [ + { + "type": "DNSServer", + "options": { + "domain_mapping": { + "arcd.com": "192.168.1.12" + } + } + } + ] + }, + { + "hostname": "web_server", + "type": "server", + "ip_address": "192.168.1.12", + "subnet_mask": "255.255.255.0", + "default_gateway": "192.168.1.1", + "dns_server": "192.168.1.10", + "services": [ + { + "type": "WebServer" + } + ], + "applications": [ + { + "type": "DatabaseClient", + "options": { + "db_server_ip": "192.168.1.14" + } + } + ] + }, + { + "hostname": "database_server", + "type": "server", + "ip_address": "192.168.1.14", + "subnet_mask": "255.255.255.0", + "default_gateway": "192.168.1.1", + "dns_server": "192.168.1.10", + "services": [ + { + "type": "DatabaseService", + "options": { + "backup_server_ip": "192.168.1.16" + } + }, + { + "type": "FTPClient" + } + ] + }, + { + "hostname": "backup_server", + "type": "server", + "ip_address": "192.168.1.16", + "subnet_mask": "255.255.255.0", + "default_gateway": "192.168.1.1", + "dns_server": "192.168.1.10", + "services": [ + { + "type": "FTPServer" + } + ] + }, + { + "hostname": "security_suite", + "type": "server", + "ip_address": "192.168.1.110", + "subnet_mask": "255.255.255.0", + "default_gateway": "192.168.1.1", + "dns_server": "192.168.1.10", + "network_interfaces": { + "2": { + "ip_address": "192.168.10.110", + "subnet_mask": "255.255.255.0" + } + } + }, + { + "hostname": "client_1", + "type": "computer", + "ip_address": "192.168.10.21", + "subnet_mask": "255.255.255.0", + "default_gateway": "192.168.10.1", + "dns_server": "192.168.1.10", + "applications": [ + { + "type": "DataManipulationBot", + "options": { + "port_scan_p_of_success": 0.8, + "data_manipulation_p_of_success": 0.8, + "payload": "DELETE", + "server_ip": "192.168.1.14" + } + }, + { + "type": "WebBrowser", + "options": { + "target_url": "http://arcd.com/users/" + } + }, + { + "type": "DatabaseClient", + "options": { + "db_server_ip": "192.168.1.14" + } + } + ], + "services": [ + { + "type": "DNSClient" + } + ] + }, + { + "hostname": "client_2", + "type": "computer", + "ip_address": "192.168.10.22", + "subnet_mask": "255.255.255.0", + "default_gateway": "192.168.10.1", + "dns_server": "192.168.1.10", + "applications": [ + { + "type": "WebBrowser", + "options": { + "target_url": "http://arcd.com/users/" + } + }, + { + "type": "DataManipulationBot", + "options": { + "port_scan_p_of_success": 0.8, + "data_manipulation_p_of_success": 0.8, + "payload": "DELETE", + "server_ip": "192.168.1.14" + } + }, + { + "type": "DatabaseClient", + "options": { + "db_server_ip": "192.168.1.14" + } + } + ], + "services": [ + { + "type": "DNSClient" + } + ] + } + ], + "links": [ + { + "endpoint_a_hostname": "router_1", + "endpoint_a_port": 1, + "endpoint_b_hostname": "switch_1", + "endpoint_b_port": 8 + }, + { + "endpoint_a_hostname": "router_1", + "endpoint_a_port": 2, + "endpoint_b_hostname": "switch_2", + "endpoint_b_port": 8 + }, + { + "endpoint_a_hostname": "switch_1", + "endpoint_a_port": 1, + "endpoint_b_hostname": "domain_controller", + "endpoint_b_port": 1 + }, + { + "endpoint_a_hostname": "switch_1", + "endpoint_a_port": 2, + "endpoint_b_hostname": "web_server", + "endpoint_b_port": 1 + }, + { + "endpoint_a_hostname": "switch_1", + "endpoint_a_port": 3, + "endpoint_b_hostname": "database_server", + "endpoint_b_port": 1 + }, + { + "endpoint_a_hostname": "switch_1", + "endpoint_a_port": 4, + "endpoint_b_hostname": "backup_server", + "endpoint_b_port": 1 + }, + { + "endpoint_a_hostname": "switch_1", + "endpoint_a_port": 7, + "endpoint_b_hostname": "security_suite", + "endpoint_b_port": 1 + }, + { + "endpoint_a_hostname": "switch_2", + "endpoint_a_port": 1, + "endpoint_b_hostname": "client_1", + "endpoint_b_port": 1 + }, + { + "endpoint_a_hostname": "switch_2", + "endpoint_a_port": 2, + "endpoint_b_hostname": "client_2", + "endpoint_b_port": 1 + }, + { + "endpoint_a_hostname": "switch_2", + "endpoint_a_port": 7, + "endpoint_b_hostname": "security_suite", + "endpoint_b_port": 2 + } + ] + } + } + } +} \ No newline at end of file