File size: 5,193 Bytes
d2b26ce | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 | #!/usr/bin/env python3
import argparse
import json
from collections import defaultdict
from pathlib import Path
from typing import Dict, List, Optional, Set, Tuple
import matplotlib
matplotlib.use("Agg")
import matplotlib.pyplot as plt
def parse_int_list(value: Optional[str]) -> Optional[Set[int]]:
if not value:
return None
return {int(item.strip()) for item in value.split(",") if item.strip()}
def load_l1_rel_records(json_path: Path) -> List[dict]:
with json_path.open("r") as f:
payload = json.load(f)
if isinstance(payload, list):
return payload
if isinstance(payload, dict) and isinstance(payload.get("records"), list):
return payload["records"]
raise ValueError(f"Cannot find records in {json_path}")
def collect_by_chunk(records: List[dict], chunk_ids: Optional[Set[int]], max_chunks: Optional[int]) -> Dict[int, List[dict]]:
chunks = defaultdict(list)
for record in records:
chunk_idx = int(record["chunk_idx"])
if chunk_ids is not None and chunk_idx not in chunk_ids:
continue
chunks[chunk_idx].append(record)
chunks = dict(sorted(chunks.items()))
if max_chunks is not None:
chunks = dict(list(chunks.items())[:max_chunks])
return chunks
def plot_l1_rel(
chunks: Dict[int, List[dict]],
output_path: Path,
x_field: str,
y_field: str,
reverse_x: bool,
title: Optional[str],
figsize: Tuple[float, float],
dpi: int,
) -> None:
fig, ax = plt.subplots(figsize=figsize)
for chunk_idx, records in chunks.items():
points = []
for record in records:
if x_field not in record or y_field not in record:
continue
if record[x_field] is None or record[y_field] is None:
continue
points.append((float(record[x_field]), float(record[y_field])))
if not points:
continue
points.sort(key=lambda item: item[0])
xs, ys = zip(*points)
ax.plot(xs, ys, marker="o", linewidth=1.6, markersize=3, label=f"chunk {chunk_idx}")
ax.set_xlabel(x_field)
ax.set_ylabel(y_field)
ax.set_title(title or f"{y_field} by timestep")
ax.grid(True, alpha=0.3)
if reverse_x:
ax.invert_xaxis()
ax.legend(loc="best", fontsize="small", ncols=2)
fig.tight_layout()
output_path.parent.mkdir(parents=True, exist_ok=True)
fig.savefig(output_path, dpi=dpi)
plt.close(fig)
def parse_arguments():
parser = argparse.ArgumentParser(description="Plot per-chunk MAGI relative L1 change curves.")
parser.add_argument("json_path", type=Path, help="Path to L1 relative change JSON saved by --l1_rel_stats_path.")
parser.add_argument("-o", "--output", type=Path, help="Output image path. Defaults to <json stem>_plot.png.")
parser.add_argument("--chunks", type=str, help="Comma-separated chunk_idx list to plot, for example: 0,1,2.")
parser.add_argument("--max-chunks", type=int, help="Plot at most this many chunks after filtering.")
parser.add_argument(
"--x-field",
choices=["timestep", "next_timestep", "cur_denoise_step", "denoise_idx"],
default="next_timestep",
help="Record field used for the x axis. next_timestep is the cleaner MAGI step.",
)
parser.add_argument(
"--y-field",
choices=[
"l1_rel",
"l1_rel_ratio",
"delta_l1_norm",
"x_l1_norm",
"x_embedder_l1_rel",
"x_embedder_l1_rel_ratio",
"x_embedder_delta_l1_norm",
"x_embedder_x_l1_norm",
"flowcache_rel_l1",
"flowcache_rel_l1_ratio",
"flowcache_delta_l1_norm",
"flowcache_prev_feat_l1_norm",
"flowcache_accumulated_rel_l1",
"rel_l1_thresh",
],
default="l1_rel",
help="Record field used for the y axis.",
)
parser.add_argument("--reverse-x", action="store_true", help="Reverse the x axis.")
parser.add_argument("--title", type=str, help="Figure title.")
parser.add_argument("--figsize", type=str, default="10,6", help="Figure size as width,height.")
parser.add_argument("--dpi", type=int, default=160, help="Output image DPI.")
return parser.parse_args()
def main():
args = parse_arguments()
output_path = args.output or args.json_path.with_name(f"{args.json_path.stem}_plot.png")
figsize = [float(part.strip()) for part in args.figsize.split(",")]
if len(figsize) != 2:
raise ValueError("--figsize must be formatted as width,height")
records = load_l1_rel_records(args.json_path)
chunks = collect_by_chunk(records, parse_int_list(args.chunks), args.max_chunks)
if not chunks:
raise ValueError("No records matched the requested chunks.")
plot_l1_rel(
chunks=chunks,
output_path=output_path,
x_field=args.x_field,
y_field=args.y_field,
reverse_x=args.reverse_x,
title=args.title,
figsize=(figsize[0], figsize[1]),
dpi=args.dpi,
)
print(f"Saved plot to {output_path}")
if __name__ == "__main__":
main()
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