#2648 - updated benchmark process to output markdown file instead of LaTeX. Added pipeline that runs benchmarking at 2am on a weekday and automatically upon creation of release branch
This commit is contained in:
Chris McCarthy
@@ -9,10 +9,6 @@ import plotly.graph_objects as go
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import polars as pl
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import yaml
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from plotly.graph_objs import Figure
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from pylatex import Command, Document
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from pylatex import Figure as LatexFigure
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from pylatex import Section, Subsection, Tabular
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from pylatex.utils import bold
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from utils import _get_system_info
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import primaite
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@@ -140,7 +136,7 @@ def _plot_all_benchmarks_combined_session_av(results_directory: Path) -> Figure:
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converted into a polars dataframe, and plotted as a scatter line in plotly.
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"""
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major_v = primaite.__version__.split(".")[0]
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title = f"Learning Benchmarking of All Released Versions under Major v{major_v}.*.*"
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title = f"Learning Benchmarking of All Released Versions under Major v{major_v}.#.#"
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subtitle = "Rolling Av (Combined Session Av)"
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if title:
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if subtitle:
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@@ -208,98 +204,77 @@ def build_benchmark_latex_report(
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fig = _plot_all_benchmarks_combined_session_av(results_directory=results_root_path)
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all_version_plot_path = results_root_path / "PrimAITE Versions Learning Benchmark.png"
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all_version_plot_path = version_result_dir / "PrimAITE Versions Learning Benchmark.png"
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fig.write_image(all_version_plot_path)
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geometry_options = {"tmargin": "2.5cm", "rmargin": "2.5cm", "bmargin": "2.5cm", "lmargin": "2.5cm"}
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data = benchmark_metadata_dict
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primaite_version = data["primaite_version"]
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# Create a new document
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doc = Document("report", geometry_options=geometry_options)
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# Title
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doc.preamble.append(Command("title", f"PrimAITE {primaite_version} Learning Benchmark"))
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doc.preamble.append(Command("author", "PrimAITE Dev Team"))
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doc.preamble.append(Command("date", datetime.now().date()))
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doc.append(Command("maketitle"))
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with open(version_result_dir / f"PrimAITE v{primaite_version} Learning Benchmark.md", "w") as file:
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# Title
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file.write(f"# PrimAITE v{primaite_version} Learning Benchmark\n")
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file.write("## PrimAITE Dev Team\n")
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file.write(f"### {datetime.now().date()}\n")
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file.write("\n---\n")
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sessions = data["total_sessions"]
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episodes = session_metadata[1]["total_episodes"] - 1
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steps = data["config"]["game"]["max_episode_length"]
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sessions = data["total_sessions"]
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episodes = session_metadata[1]["total_episodes"] - 1
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steps = data["config"]["game"]["max_episode_length"]
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# Body
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with doc.create(Section("Introduction")):
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doc.append(
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# Body
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file.write("## 1 Introduction\n")
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file.write(
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f"PrimAITE v{primaite_version} was benchmarked automatically upon release. Learning rate metrics "
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f"were captured to be referenced during system-level testing and user acceptance testing (UAT)."
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f"were captured to be referenced during system-level testing and user acceptance testing (UAT).\n"
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)
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doc.append(
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f"\nThe benchmarking process consists of running {sessions} training session using the same "
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file.write(
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f"The benchmarking process consists of running {sessions} training session using the same "
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f"config file. Each session trains an agent for {episodes} episodes, "
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f"with each episode consisting of {steps} steps."
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f"with each episode consisting of {steps} steps.\n"
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)
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doc.append(
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f"\nThe total reward per episode from each session is captured. This is then used to calculate an "
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file.write(
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f"The total reward per episode from each session is captured. This is then used to calculate an "
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f"caverage total reward per episode from the {sessions} individual sessions for smoothing. "
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f"Finally, a 25-widow rolling average of the average total reward per session is calculated for "
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f"further smoothing."
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f"further smoothing.\n"
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)
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with doc.create(Section("System Information")):
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with doc.create(Subsection("Python")):
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with doc.create(Tabular("|l|l|")) as table:
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table.add_hline()
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table.add_row((bold("Version"), sys.version))
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table.add_hline()
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file.write("## 2 System Information\n")
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i = 1
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file.write(f"### 2.{i} Python\n")
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file.write(f"**Version:** {sys.version}\n")
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for section, section_data in data["system_info"].items():
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i += 1
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if section_data:
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with doc.create(Subsection(section)):
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if isinstance(section_data, dict):
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with doc.create(Tabular("|l|l|")) as table:
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table.add_hline()
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for key, value in section_data.items():
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table.add_row((bold(key), value))
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table.add_hline()
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elif isinstance(section_data, list):
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headers = section_data[0].keys()
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tabs_str = "|".join(["l" for _ in range(len(headers))])
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tabs_str = f"|{tabs_str}|"
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with doc.create(Tabular(tabs_str)) as table:
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table.add_hline()
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table.add_row([bold(h) for h in headers])
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table.add_hline()
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for item in section_data:
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table.add_row(item.values())
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table.add_hline()
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file.write(f"### 2.{i} {section}\n")
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if isinstance(section_data, dict):
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for key, value in section_data.items():
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file.write(f"- **{key}:** {value}\n")
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headers_map = {
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"total_sessions": "Total Sessions",
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"total_episodes": "Total Episodes",
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"total_time_steps": "Total Steps",
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"av_s_per_session": "Av Session Duration (s)",
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"av_s_per_step": "Av Step Duration (s)",
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"av_s_per_100_steps_10_nodes": "Av Duration per 100 Steps per 10 Nodes (s)",
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}
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with doc.create(Section("Stats")):
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with doc.create(Subsection("Benchmark Results")):
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with doc.create(Tabular("|l|l|")) as table:
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table.add_hline()
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for section, header in headers_map.items():
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if section.startswith("av_"):
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table.add_row((bold(header), f"{data[section]:.4f}"))
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else:
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table.add_row((bold(header), data[section]))
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table.add_hline()
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headers_map = {
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"total_sessions": "Total Sessions",
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"total_episodes": "Total Episodes",
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"total_time_steps": "Total Steps",
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"av_s_per_session": "Av Session Duration (s)",
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"av_s_per_step": "Av Step Duration (s)",
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"av_s_per_100_steps_10_nodes": "Av Duration per 100 Steps per 10 Nodes (s)",
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}
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with doc.create(Section("Graphs")):
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with doc.create(Subsection(f"v{primaite_version} Learning Benchmark Plot")):
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with doc.create(LatexFigure(position="h!")) as pic:
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pic.add_image(str(this_version_plot_path))
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pic.add_caption(f"PrimAITE {primaite_version} Learning Benchmark Plot")
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file.write("## 3 Stats\n")
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for section, header in headers_map.items():
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if section.startswith("av_"):
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file.write(f"- **{header}:** {data[section]:.4f}\n")
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else:
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file.write(f"- **{header}:** {data[section]}\n")
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with doc.create(Subsection(f"Learning Benchmarking of All Released Versions under Major v{major_v}.*.*")):
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with doc.create(LatexFigure(position="h!")) as pic:
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pic.add_image(str(all_version_plot_path))
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pic.add_caption(f"Learning Benchmarking of All Released Versions under Major v{major_v}.*.*")
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file.write("## 4 Graphs\n")
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doc.generate_pdf(str(this_version_plot_path).replace(".png", ""), clean_tex=True)
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file.write(f"### 4.1 v{primaite_version} Learning Benchmark Plot\n")
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file.write(f"\n")
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file.write(f"### 4.2 Learning Benchmarking of All Released Versions under Major v{major_v}.#.#\n")
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file.write(
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f"\n"
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)
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