Camera-ready release

README.md

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+---
+license: apache-2.0
+task_categories:
+- reinforcement-learning
+language:
+- en
+tags:
+- eda
+- analog
+- analog-circuits
+- circuit-layout
+- gdsii
+- sky130
+- parasitic-extraction
+- layout-optimization
+pretty_name: OSIRIS Analog Circuit Layouts and Metrics
+size_categories:
+- 10K<n<100K
+configs:
+- config_name: default
+  default: true
+  data_files:
+  - split: full
+    path: viewer/variants.parquet
+---
+
+# OSIRIS: Bridging Analog Layout Circuit Design and Machine Learning with Scalable Dataset Generation
+
+OSIRIS generates and evaluates analog circuit layouts. This repository contains a browsable table of the generated layout variants, the full circuit artifacts, and the pipeline code released with the ICLR 2026 paper.
+The [ICLR 2026 paper](https://proceedings.iclr.cc/paper_files/paper/2026/hash/9c0be694049f5b6fb35ed9ef12da34b0-Abstract-Conference.html).
+
+## Browse the dataset
+
+The **Dataset Viewer** displays one row per top-level layout GDS file in `data/Osiris_Dataset.zip`. There are **89,108 distinct rows and layout files**, covering the five circuit families below.
+
+| Circuit family | Layouts (#) |
+| --- | ---: |
+| `ahuja_ota` | 14,617 |
+| `five_transistors_ota` | 13,694 |
+| `miller_ota` | 14,870 |
+| `ota_ff` | 23,028 |
+| `ota_lpf` | 22,899 |
+| **Total** | **89,108** |
+
+| Column | Meaning |
+| --- | --- |
+| `id` | Unique path-like variant identifier: circuit family, instance, and variant. |
+| `circuit_family`, `circuit_instance`, `variant` | Identifiers from the release directory structure. |
+| `area` | Numeric value from the variant's `area.npy`. |
+| `pex_score` | Numeric array from the variant's `pex_score.npy`. |
+| `layout_member` | GDS layout path inside `data/Osiris_Dataset.zip`. |
+| `netlist_member`, `moves_member` | Associated netlist and move metadata paths inside the same archive. |
+| `simulation_pre_member`, `simulation_post_member` | Pre- and post-extraction simulation CSV paths inside the same archive. |
+
+Load the Viewer table with:
+
+```python
+from datasets import load_dataset
+
+variants = load_dataset("hardware-fab/osiris", "default", split="full")
+print(variants[0])
+```
+
+## Repository files
+
+| Path | Contents |
+| --- | --- |
+| `viewer/variants.parquet` | The typed, searchable variant table used by the Dataset Viewer. |
+| `data/Osiris_Dataset.zip` | Complete layouts, netlists, metadata, metrics, and simulations. Extracts to `Osiris_Dataset/`. |
+| `code/osiris_code.zip` | Pipeline code and supporting files. Extracts to `osiris/`. |
+
+The Parquet table is an index and summary of the original artifacts. The GDS layouts and simulation files remain in the ZIP archive.
+
+After extracting the dataset archive, its main directories are:
+
+```text
+Osiris_Dataset/
+├── data/
+│   ├── layouts/
+│   ├── metadata/
+│   ├── metrics/
+│   └── simulations/
+└── netlists/
+```
+
+Each data category is organized by circuit family, circuit instance, and variant. The `*_member` values in the table are exact paths relative to the root of this archive.
+
+## Download an artifact
+
+```python
+from zipfile import ZipFile
+from datasets import load_dataset
+from huggingface_hub import hf_hub_download
+
+row = load_dataset("hardware-fab/osiris", "default", split="full")[0]
+archive = hf_hub_download(
+    repo_id="hardware-fab/osiris",
+    repo_type="dataset",
+    filename="data/Osiris_Dataset.zip",
+)
+with ZipFile(archive) as z:
+    z.extract(row["layout_member"], path=".")
+```
+
+Download `code/osiris_code.zip` in the same way if you need the pipeline. Inside that ZIP, `osiris/README.md` describes installation and usage; it appears at that path after extraction. The dataset archive contains about 24 GB of uncompressed file contents and millions of entries, so allow additional disk space and time for full extraction.

code/osiris_code.zip

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+size 363956152

data/Osiris_Dataset.zip

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+size 5289108314

viewer/variants.parquet

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