fix: nbdev-clean notebook metadata for CI compliance

Author: nathanhubens

nbs/analysis/benchmark.ipynb

@@ -2,11 +2,11 @@
  "cells": [
   {
    "cell_type": "raw",
+   "id": "frontmatter",
    "metadata": {},
    "source": [
     "---\ntitle: \"Benchmark\"\ndescription: \"Unified benchmarking API for PyTorch models\"\nskip_showdoc: true\n---"
-   ],
-   "id": "frontmatter"
+   ]
   },
   {
    "cell_type": "code",
@@ -125,17 +125,20 @@
   },
   {
    "cell_type": "code",
+   "execution_count": null,
+   "id": "show_doc_0",
    "metadata": {},
+   "outputs": [],
    "source": [
     "show_doc(BenchmarkResult)"
-   ],
-   "id": "show_doc_0",
-   "outputs": [],
-   "execution_count": null
+   ]
   },
   {
    "cell_type": "code",
+   "execution_count": null,
+   "id": "test_basic",
    "metadata": {},
+   "outputs": [],
    "source": [
     "#| hide\n",
     "from fastcore.test import *\n",
@@ -147,10 +150,7 @@
     "assert isinstance(_r, BenchmarkResult)\n",
     "assert \"size_num_params\" in _r\n",
     "assert _r[\"size_num_params\"] > 0"
-   ],
-   "id": "test_basic",
-   "outputs": [],
-   "execution_count": null
+   ]
   },
   {
    "cell_type": "markdown",
@@ -179,4 +179,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 5
-}
+}

nbs/analysis/profiling.ipynb

@@ -2,11 +2,11 @@
  "cells": [
   {
    "cell_type": "raw",
+   "id": "frontmatter",
    "metadata": {},
    "source": [
     "---\ntitle: \"Profiling\"\ndescription: \"Per-layer profiling for deep analysis of model performance\"\nskip_showdoc: true\n---"
-   ],
-   "id": "frontmatter"
+   ]
   },
   {
    "cell_type": "code",
@@ -20,13 +20,13 @@
   },
   {
    "cell_type": "code",
+   "execution_count": null,
+   "id": "setup_showdoc",
    "metadata": {},
+   "outputs": [],
    "source": [
     "#| include: false\nfrom nbdev.showdoc import *"
-   ],
-   "id": "setup_showdoc",
-   "outputs": [],
-   "execution_count": null
+   ]
   },
   {
    "cell_type": "code",
@@ -438,61 +438,61 @@
   },
   {
    "cell_type": "code",
+   "execution_count": null,
+   "id": "show_doc_0",
    "metadata": {},
+   "outputs": [],
    "source": [
     "show_doc(LayerProfiler)"
-   ],
-   "id": "show_doc_0",
-   "outputs": [],
-   "execution_count": null
+   ]
   },
   {
    "cell_type": "code",
+   "execution_count": null,
+   "id": "show_doc_1",
    "metadata": {},
+   "outputs": [],
    "source": [
     "show_doc(LayerProfiler.profile)"
-   ],
-   "id": "show_doc_1",
-   "outputs": [],
-   "execution_count": null
+   ]
   },
   {
    "cell_type": "code",
+   "execution_count": null,
+   "id": "show_doc_2",
    "metadata": {},
+   "outputs": [],
    "source": [
     "show_doc(LayerProfiler.top)"
-   ],
-   "id": "show_doc_2",
-   "outputs": [],
-   "execution_count": null
+   ]
   },
   {
    "cell_type": "code",
+   "execution_count": null,
+   "id": "show_doc_3",
    "metadata": {},
+   "outputs": [],
    "source": [
     "show_doc(LayerProfiler.summary)"
-   ],
-   "id": "show_doc_3",
-   "outputs": [],
-   "execution_count": null
+   ]
   },
   {
    "cell_type": "code",
+   "execution_count": null,
+   "id": "test_basic",
    "metadata": {},
+   "outputs": [],
    "source": [
     "#| hide\nfrom fastcore.test import *\n\nimport torch, torch.nn as nn\n_m = nn.Sequential(nn.Linear(10, 20), nn.ReLU(), nn.Linear(20, 5))\n_x = torch.randn(1, 10)\n_lp = LayerProfiler(_m, _x)\n_results = _lp.profile(metrics=[\"size\"])\nassert len(_results) > 0\nassert all(\"params\" in r for r in _results)"
-   ],
-   "id": "test_basic",
-   "outputs": [],
-   "execution_count": null
+   ]
   },
   {
    "cell_type": "markdown",
+   "id": "see_also",
    "metadata": {},
    "source": [
     "---\n\n## See Also\n\n- [Benchmark](benchmark.html) — Unified benchmarking API\n- [Speed](../metrics/speed.html) — Latency measurement\n- [Profiling Tutorial](../tutorials/profiling.html) — Step-by-step profiling guide"
-   ],
-   "id": "see_also"
+   ]
   }
  ],
  "metadata": {
@@ -504,4 +504,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 5
-}
+}