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Render videos eval mode #274

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e72e16a
Added render_eval mode, minor bug fixes for building in clang
mpragnay Feb 1, 2026
4067498
revert to default configs
mpragnay Feb 1, 2026
26b7940
minor changes
mpragnay Feb 1, 2026
63d1cf1
Added Documentation for mode
mpragnay Feb 1, 2026
9dbc4c1
String Concatenation fixes, exception handling for timeout, doc sugge…
mpragnay Feb 1, 2026
712218d
Merge branch '3.0' into Render-Videos-Eval-Mode
mpragnay Feb 2, 2026
8ba1e3c
Created a Separate Render Mode, updated docs
mpragnay Feb 2, 2026
4372e44
code cleanup
mpragnay Feb 2, 2026
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10 changes: 10 additions & 0 deletions docs/src/visualizer.md
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Original file line number Diff line number Diff line change
Expand Up @@ -33,3 +33,13 @@ xvfb-run -s "-screen 0 1280x720x24" ./visualize
```

Adjust the screen size and color depth as needed. The `xvfb-run` wrapper allows Raylib to render without an attached display, which is convenient for servers and CI jobs.

## Rendering Mode
You can batch render videos for multiple maps using the evaluation mode. This will render the first `num_maps` maps (capped by the number of maps in the directory) from `map_dir` in parallel using the `visualize` binary and create these videos in an `output_dir`(All configs in [render] of `drive.ini`).

After setting the configs run:
```bash
puffer render puffer_drive
```

This mode parallelizes rendering based on `vec.num_workers`.
25 changes: 25 additions & 0 deletions pufferlib/config/ocean/drive.ini
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Expand Up @@ -132,6 +132,31 @@ human_replay_eval = False
; Control only the self-driving car
human_replay_control_mode = "control_sdc_only"

[render]
; Mode to render a bunch of maps with a given policy
; Path to dataset used for rendering
map_dir = "resources/drive/binaries/training"
; Directory to output rendered videos
output_dir = "resources/drive/render_videos"
; Evaluation will run on the first num_maps maps in the map_dir directory
num_maps = 100
; "both", "topdown", "agent"; Other args are passed from train confs
view_mode = "both"
; Policy bin file used for rendering videos
policy_path = "resources/drive/puffer_drive_weights_resampling_300.bin"
; Allows more than cpu cores workers for rendering
overwork = True
; If True, show exactly what the agent sees in agent observation
obs_only = True
; Show grid lines
show_grid = True
; Draws lines from ego agent observed ORUs and road elements to show detection range
show_lasers = True
; Display human xy logs in the background
show_human_logs = False
; If True, zoom in on a part of the map. Otherwise, show full map
zoom_in = True

[sweep.train.learning_rate]
distribution = log_normal
min = 0.001
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1 change: 1 addition & 0 deletions pufferlib/ocean/drive/drive.h
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Expand Up @@ -332,6 +332,7 @@ float point_to_segment_distance_2d(float px, float py, float x1, float y1, float
void init_goal_positions(Drive *env);
float clipSpeed(float speed);
void sample_new_goal(Drive *env, int agent_idx);
int check_lane_aligned(Entity *car, Entity *lane, int geometry_idx);
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@eugenevinitsky eugenevinitsky Feb 1, 2026

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this seems like it should not be here?

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@mpragnay mpragnay Feb 1, 2026

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Oh i added it cuz I was getting compile error on my mac. forward declaration. I can make it a separate PR but it's just a one liner.


// ========================================
// Utility Functions
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92 changes: 87 additions & 5 deletions pufferlib/pufferl.py
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Expand Up @@ -24,6 +24,7 @@

import numpy as np
import psutil
from multiprocessing.pool import ThreadPool

import torch
import torch.distributed
Expand Down Expand Up @@ -1232,6 +1233,7 @@ def eval(env_name, args=None, vecenv=None, policy=None):
print("HUMAN_REPLAY_METRICS_END")

return results

else: # Standard evaluation: Render
backend = args["vec"]["backend"]
if backend != "PufferEnv":
Expand All @@ -1246,10 +1248,6 @@ def eval(env_name, args=None, vecenv=None, policy=None):
num_agents = vecenv.observation_space.shape[0]
device = args["train"]["device"]

# Rebuild visualize binary if saving frames (for C-based rendering)
if args["save_frames"] > 0:
ensure_drive_binary()

state = {}
if args["train"]["use_rnn"]:
state = dict(
Expand Down Expand Up @@ -1643,8 +1641,90 @@ def puffer_type(value):
return args


def render(env_name, args=None):
args = args or load_config(env_name)
render_configs = args.get("render", {})

# Renders first num_maps from map_dir using visualize binary
try:
map_dir = render_configs["map_dir"]
num_maps = render_configs.get("num_maps", 1)
view_mode = render_configs["view_mode"]
render_policy_path = render_configs["policy_path"]
overwork = render_configs.get("overwork", False)
num_workers = args["vec"]["num_workers"]
output_dir = render_configs["output_dir"]
except KeyError as e:
raise pufferlib.APIUsageError(f"Missing render config: {e}")

cpu_cores = psutil.cpu_count(logical=False)
if num_workers > cpu_cores and not overwork:
raise pufferlib.APIUsageError(
" ".join(
[
f"num_workers ({num_workers}) > hardware cores ({cpu_cores}) is disallowed by default.",
"PufferLib multiprocessing is heavily optimized for 1 process per hardware core.",
"If you really want to do this, set overwork=True (--vec-overwork in our demo.py).",
]
)
)

if num_maps > len(os.listdir(map_dir)):
num_maps = len(os.listdir(map_dir))

render_maps = [os.path.join(map_dir, f) for f in sorted(os.listdir(map_dir)) if f.endswith(".bin")][:num_maps]
os.makedirs(output_dir, exist_ok=True)

# Rebuild visualize binary
ensure_drive_binary()

def render_task(map_path):
base_cmd = (
["./visualize"]
if sys.platform == "darwin"
else ["xvfb-run", "-a", "-s", "-screen 0 1280x720x24", "./visualize"]
)
cmd = base_cmd.copy()
cmd.extend(["--map-name", map_path])
if render_configs.get("show_grid", False):
cmd.append("--show-grid")
if render_configs.get("obs_only", False):
cmd.append("--obs-only")
if render_configs.get("show_lasers", False):
cmd.append("--lasers")
if render_configs.get("show_human_logs", False):
cmd.append("--show-human-logs")
if render_configs.get("zoom_in", False):
cmd.append("--zoom-in")
cmd.extend(["--view", view_mode])
if render_policy_path is not None:
cmd.extend(["--policy-name", render_policy_path])

map_name = os.path.basename(map_path).replace(".bin", "")

if view_mode == "topdown" or view_mode == "both":
cmd.extend(["--output-topdown", os.path.join(output_dir, f"topdown_{map_name}.mp4")])
if view_mode == "agent" or view_mode == "both":
cmd.extend(["--output-agent", os.path.join(output_dir, f"agent_{map_name}.mp4")])

env_vars = os.environ.copy()
env_vars["ASAN_OPTIONS"] = "exitcode=0"
try:
result = subprocess.run(cmd, cwd=os.getcwd(), capture_output=True, text=True, timeout=600, env=env_vars)
if result.returncode != 0:
print(f"Error rendering {map_name}: {result.stderr}")
except subprocess.TimeoutExpired:
print(f"Timeout rendering {map_name}: exceeded 600 seconds")

if render_maps:
print(f"Rendering {len(render_maps)} from {map_dir} with {num_workers} workers...")
with ThreadPool(num_workers) as pool:
pool.map(render_task, render_maps)
print(f"Finished rendering videos to {output_dir}")


def main():
err = "Usage: puffer [train, eval, sweep, controlled_exp, autotune, profile, export, sanity] [env_name] [optional args]. --help for more info"
err = "Usage: puffer [train, eval, sweep, controlled_exp, autotune, profile, export, sanity, render] [env_name] [optional args]. --help for more info"
if len(sys.argv) < 3:
raise pufferlib.APIUsageError(err)

Expand All @@ -1666,6 +1746,8 @@ def main():
export(env_name=env_name)
elif mode == "sanity":
sanity(env_name=env_name)
elif mode == "render":
render(env_name=env_name)
else:
raise pufferlib.APIUsageError(err)

Expand Down
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