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Use correct input in layernorm example (#960)

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* Update CI

* Use correct example in layernorm section

* update
This commit is contained in:
Sebastian Raschka
2026-02-18 22:35:57 -05:00
committed by GitHub
parent be5e2a3331
commit 2d600ccb5b
2 changed files with 20 additions and 12 deletions
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30
ch04/01_main-chapter-code/ch04.ipynb
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@@ -38,9 +38,9 @@
"name": "stdout",
"output_type": "stream",
"text": [
"matplotlib version: 3.10.0\n",
"torch version: 2.6.0\n",
"tiktoken version: 0.9.0\n"
"matplotlib version: 3.10.8\n",
"torch version: 2.10.0\n",
"tiktoken version: 0.12.0\n"
]
}
],
@@ -492,8 +492,8 @@
"output_type": "stream",
"text": [
"Mean:\n",
" tensor([[ -0.0000],\n",
" [ 0.0000]], grad_fn=<MeanBackward1>)\n",
" tensor([[-0.0000],\n",
" [ 0.0000]], grad_fn=<MeanBackward1>)\n",
"Variance:\n",
" tensor([[1.0000],\n",
" [1.0000]], grad_fn=<VarBackward0>)\n"
@@ -564,8 +564,8 @@
"metadata": {},
"outputs": [],
"source": [
"ln = LayerNorm(emb_dim=5)\n",
"out_ln = ln(batch_example)"
"ln = LayerNorm(emb_dim=6)\n",
"out_ln = ln(out)"
]
},
{
@@ -579,11 +579,11 @@
"output_type": "stream",
"text": [
"Mean:\n",
" tensor([[ -0.0000],\n",
" [ 0.0000]], grad_fn=<MeanBackward1>)\n",
" tensor([[-0.0000],\n",
" [-0.0000]], grad_fn=<MeanBackward1>)\n",
"Variance:\n",
" tensor([[1.0000],\n",
" [1.0000]], grad_fn=<VarBackward0>)\n"
" tensor([[0.9995],\n",
" [0.9997]], grad_fn=<VarBackward0>)\n"
]
}
],
@@ -595,6 +595,14 @@
"print(\"Variance:\\n\", var)"
]
},
{
"cell_type": "markdown",
"id": "07220af7-cf53-48c8-8831-813a7088edea",
"metadata": {},
"source": [
"- Variance is not exactly 1 because we use `eps`"
]
},
{
"cell_type": "markdown",
"id": "e136cfc4-7c89-492e-b120-758c272bca8c",

2
reasoning-from-scratch

Submodule reasoning-from-scratch updated: edcae1d894...7b6a9d0f90