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Adds a readonly (static) Trackio mode (includes a BREAKING change: trackio.sync() will now output readonly Spaces by default) (#455)
Co-authored-by: gradio-pr-bot <gradio-pr-bot@users.noreply.github.com>
1 parent 3e5d950 commit f8db51a

29 files changed

Lines changed: 1816 additions & 350 deletions

‎.changeset/tough-turtles-hunt.md‎

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---
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"trackio": minor
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---
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feat:Adds a static Trackio mode via `trackio.sync(sdk="static")` and support for the `TRACKIO_SPACE_ID` environment variable

‎autonomous-experiments/02_autoresearch/train_autoresearch.py‎

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@@ -452,7 +452,7 @@ def __init__(self, config, layer_idx):
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)
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def forward(self, x, ve, cos_sin, window_size):
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B, T, C = x.size()
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B, T, _ = x.size()
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q = self.c_q(x).view(B, T, self.n_head, self.head_dim)
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k = self.c_k(x).view(B, T, self.n_kv_head, self.head_dim)
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v = self.c_v(x).view(B, T, self.n_kv_head, self.head_dim)
@@ -706,7 +706,7 @@ def setup_optimizer(
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return optimizer
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def forward(self, idx, targets=None, reduction="mean"):
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B, T = idx.size()
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_, T = idx.size()
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assert T <= self.cos.size(1)
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cos_sin = self.cos[:, :T], self.sin[:, :T]
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x = self.transformer.wte(idx)

‎examples/kitchen-sink-local-only.py‎

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"""
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Example: log metrics + system metrics + media + table + report + files locally.
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Usage:
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python examples/kitchen-sink-local-only.py
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"""
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import math
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import random
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import time
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from pathlib import Path
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import numpy as np
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import pandas as pd
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from PIL import Image as PILImage
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from PIL import ImageDraw
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import trackio
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PROJECT = f"local-full-demo-{random.randint(100000, 999999)}"
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STEPS = 8
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N_RUNS = 3
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def make_image(step: int, size: int = 128) -> PILImage.Image:
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img = PILImage.new("RGB", (size, size), "black")
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draw = ImageDraw.Draw(img)
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x = int((size / 2) + (size / 3) * math.sin(step * 0.8))
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y = int((size / 2) + (size / 3) * math.cos(step * 0.6))
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draw.ellipse((x - 10, y - 10, x + 10, y + 10), fill=(255, 120, 80))
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draw.rectangle((8, 8, size - 8, size - 8), outline=(80, 160, 255), width=2)
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return img
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def make_audio(step: int, sr: int = 16000, duration_s: float = 0.3) -> np.ndarray:
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t = np.linspace(0, duration_s, int(sr * duration_s), endpoint=False)
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freq = 220 + step * 20
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wave = 0.4 * np.sin(2 * np.pi * freq * t)
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return (wave * 32767).astype(np.int16)
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def main() -> None:
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examples_dir = Path(__file__).parent
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files_dir = examples_dir / "files"
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run_names = [f"run-{run_idx}" for run_idx in range(N_RUNS)]
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for run_idx in range(N_RUNS):
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trackio.init(
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project=PROJECT,
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name=f"run-{run_idx}",
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config={"steps": STEPS, "run_idx": run_idx, "mode": "local-only"},
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auto_log_gpu=False,
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)
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trackio.alert(
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title="Run started",
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text=f"Project: {PROJECT} | Run: run-{run_idx}",
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level=trackio.AlertLevel.INFO,
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)
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if run_idx == 0:
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trackio.save(files_dir / "config1.yml", project=PROJECT)
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trackio.save(files_dir / "config2.yml", project=PROJECT)
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for step in range(STEPS):
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train_loss = round(
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max(0.05, 1.8 * math.exp(-0.35 * step) + random.gauss(0, 0.03)),
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4,
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)
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train_acc = round(min(0.99, 0.45 + 0.07 * step + random.gauss(0, 0.015)), 4)
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img = make_image(step + run_idx)
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audio = make_audio(step + run_idx)
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table_df = pd.DataFrame(
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{
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"sample_id": [f"s-{step}-a", f"s-{step}-b"],
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"prediction": ["cat", "dog"],
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"confidence": [
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round(0.65 + 0.03 * step + 0.01 * run_idx, 3),
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round(0.58 + 0.025 * step + 0.01 * run_idx, 3),
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],
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}
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)
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trackio.log(
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{
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"train/loss": train_loss,
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"train/accuracy": train_acc,
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"media/preview_image": trackio.Image(
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img, caption=f"step {step}, run {run_idx}"
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),
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"media/preview_audio": trackio.Audio(
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audio, sample_rate=16000, format="wav"
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),
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"tables/predictions": trackio.Table(dataframe=table_df),
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},
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step=step,
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)
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trackio.log_system(
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{
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"cpu_percent": round(25 + step * 2 + random.uniform(-1.0, 1.0), 2),
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"memory_gb": round(
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3.2 + step * 0.05 + random.uniform(-0.03, 0.03), 3
107+
),
108+
}
109+
)
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if step == STEPS - 2:
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trackio.alert(
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title="Loss is drifting",
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text=f"Run run-{run_idx} step={step} loss={train_loss}",
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level=trackio.AlertLevel.WARN,
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)
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report_md = f"""# Local Full Sync Report
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Project: `{PROJECT}`
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Run: `run-{run_idx}`
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This run logs:
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- scalar metrics
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- system metrics
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- media (image + audio)
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- a table artifact
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"""
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trackio.log({"reports/summary": trackio.Markdown(report_md)})
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if run_idx == N_RUNS - 1:
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final_report_md = f"""# Final Local Kitchen Sink Report
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Project: `{PROJECT}`
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Runs: {", ".join(f"`{name}`" for name in run_names)}
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What to look for:
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- Alerts on this page and in the alert panel (run started + one drift warning).
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- Reports entries in the Reports tab (summary per run + this final report).
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"""
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trackio.log(
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{"reports/final_report": trackio.Markdown(final_report_md)},
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step=STEPS - 1,
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)
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trackio.alert(
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title="Run finished",
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text=f"Completed run-{run_idx} ({STEPS} steps).",
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level=trackio.AlertLevel.INFO,
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)
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trackio.finish()
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result = trackio.show(
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project=PROJECT,
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open_browser=False,
156+
block_thread=False,
157+
)
158+
full_url = result[3]
159+
print(f"Dashboard: {full_url}")
160+
time.sleep(3600)
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if __name__ == "__main__":
164+
main()

‎examples/sync-static-space-everything.py‎

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"""
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Example: log metrics + system metrics + media + table + report + files, then sync to a static HF Space.
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Usage:
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python examples/sync-static-space-everything.py
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"""
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import math
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import random
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from pathlib import Path
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12+
import numpy as np
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import pandas as pd
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from PIL import Image as PILImage
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from PIL import ImageDraw
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import trackio
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PROJECT = f"sync-full-demo-{random.randint(100000, 999999)}"
20+
STEPS = 8
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22+
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def make_image(step: int, size: int = 128) -> PILImage.Image:
24+
img = PILImage.new("RGB", (size, size), "black")
25+
draw = ImageDraw.Draw(img)
26+
x = int((size / 2) + (size / 3) * math.sin(step * 0.8))
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y = int((size / 2) + (size / 3) * math.cos(step * 0.6))
28+
draw.ellipse((x - 10, y - 10, x + 10, y + 10), fill=(255, 120, 80))
29+
draw.rectangle((8, 8, size - 8, size - 8), outline=(80, 160, 255), width=2)
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return img
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33+
def make_audio(step: int, sr: int = 16000, duration_s: float = 0.3) -> np.ndarray:
34+
t = np.linspace(0, duration_s, int(sr * duration_s), endpoint=False)
35+
freq = 220 + step * 20
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wave = 0.4 * np.sin(2 * np.pi * freq * t)
37+
return (wave * 32767).astype(np.int16)
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def main():
41+
examples_dir = Path(__file__).parent
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files_dir = examples_dir / "files"
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44+
trackio.init(
45+
project=PROJECT,
46+
name="run-all-artifacts",
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config={"steps": STEPS, "mode": "static-sync-full"},
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auto_log_gpu=False,
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)
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trackio.save(files_dir / "config1.yml")
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trackio.save(files_dir / "config2.yml")
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for step in range(STEPS):
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train_loss = round(
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max(0.05, 1.8 * math.exp(-0.35 * step) + random.gauss(0, 0.03)), 4
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)
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train_acc = round(min(0.99, 0.45 + 0.07 * step + random.gauss(0, 0.015)), 4)
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img = make_image(step)
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audio = make_audio(step)
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table_df = pd.DataFrame(
63+
{
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"sample_id": [f"s-{step}-a", f"s-{step}-b"],
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"prediction": ["cat", "dog"],
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"confidence": [
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round(0.65 + 0.03 * step, 3),
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round(0.58 + 0.025 * step, 3),
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],
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}
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)
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trackio.log(
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{
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"train/loss": train_loss,
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"train/accuracy": train_acc,
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"media/preview_image": trackio.Image(img, caption=f"step {step}"),
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"media/preview_audio": trackio.Audio(
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audio, sample_rate=16000, format="wav"
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),
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"tables/predictions": trackio.Table(dataframe=table_df),
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},
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step=step,
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)
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trackio.log_system(
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{
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"cpu_percent": round(25 + step * 2 + random.uniform(-1.0, 1.0), 2),
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"memory_gb": round(3.2 + step * 0.05 + random.uniform(-0.03, 0.03), 3),
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}
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)
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report_md = f"""# Full Static Sync Report
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Project: `{PROJECT}`
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This run logs:
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- scalar metrics
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- system metrics
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- media (image + audio)
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- a table artifact
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- saved files
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"""
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trackio.log({"reports/summary": trackio.Markdown(report_md)})
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trackio.finish()
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space_id = trackio.sync(project=PROJECT)
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print(f"Dashboard: https://huggingface.co/spaces/{space_id}")
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if __name__ == "__main__":
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main()

‎examples/sync-static-space.py‎

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"""
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Example: Log some fake training data, then sync to a static HF Space.
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Usage:
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python examples/sync-static-space.py
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This will:
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1. Log a few runs of fake training metrics locally
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2. Call trackio.sync() which exports data as Parquet to an HF Dataset
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and deploys a static dashboard Space (no running server needed)
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Set HF_TOKEN or run `huggingface-cli login` first.
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"""
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import math
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import random
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import trackio
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PROJECT = f"sync-demo-{random.randint(100000, 999999)}"
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EPOCHS = 15
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def fake_loss(epoch, max_epochs):
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progress = epoch / max_epochs
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return max(0.05, 2.5 * math.exp(-3 * progress) + random.gauss(0, 0.2))
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def fake_accuracy(epoch, max_epochs):
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progress = epoch / max_epochs
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return min(
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0.95, 0.9 / (1 + math.exp(-6 * (progress - 0.5))) + random.gauss(0, 0.05)
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)
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for run_idx in range(3):
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trackio.init(
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project=PROJECT,
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name=f"run-{run_idx}",
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config={"lr": 0.001 * (run_idx + 1), "epochs": EPOCHS},
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)
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for epoch in range(EPOCHS):
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trackio.log(
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{
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"train/loss": round(fake_loss(epoch, EPOCHS), 4),
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"train/accuracy": round(fake_accuracy(epoch, EPOCHS), 4),
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"val/loss": round(fake_loss(epoch, EPOCHS) * 1.1, 4),
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}
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)
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trackio.finish()
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space_id = trackio.sync(project=PROJECT)
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print(f"Dashboard: https://huggingface.co/spaces/{space_id}")

‎pyproject.toml‎

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[tool.ruff.lint]
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# Enable Pyflakes (`F`) and a subset of the pycodestyle (`E`)
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select = ["E", "F", "I"]
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extend-select = ["PLC0415"]
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preview = true
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# Ignore line length violations
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ignore = ["E501"]
9698

@@ -100,6 +102,17 @@ fixable = ["ALL"]
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# Allow unused variables when underscore-prefixed.
101103
dummy-variable-rgx = "^(_+|(_+[a-zA-Z0-9_]*[a-zA-Z0-9]+?))$"
102104

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[tool.ruff.lint.per-file-ignores]
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"autonomous-experiments/**/*.py" = ["PLC0415"]
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"tests/**/*.py" = ["PLC0415"]
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"trackio/apple_gpu.py" = ["PLC0415"]
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"trackio/cli.py" = ["PLC0415"]
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"trackio/gpu.py" = ["PLC0415"]
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"trackio/imports.py" = ["PLC0415"]
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"trackio/run.py" = ["PLC0415"]
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"trackio/sqlite_storage.py" = ["PLC0415"]
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"trackio/utils.py" = ["PLC0415"]
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[tool.ruff.format]
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# Use single quotes for strings.
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quote-style = "double"

‎tests/ui/test_ui_display.py‎

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locator = page.locator(".vega-embed")
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expect(locator).to_have_count(0)
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checkbox.check()
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page.locator(".nav-link", has_text="Media").click()
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page.wait_for_load_state("networkidle")
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gallery = page.locator(".gallery")

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