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[docs] Optimize tutorial code in operator_custom_with_taichi.ipynb of documentations #546

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merged 4 commits into from
Nov 16, 2023
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[docs] Optimize tutorial code in operator_custom_with_taichi.ipynb of documentations #546

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366daaf
Update operator_custom_with_taichi.ipynb
Routhleck Nov 15, 2023
3b9cc9b
Merge branch 'brainpy:master' into master
Routhleck Nov 15, 2023
4bb6718
Rename the title in taichi op register tutorial
Routhleck Nov 16, 2023
a3f73df
Update operator_custom_with_taichi.ipynb
Routhleck Nov 16, 2023
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24 changes: 12 additions & 12 deletions docs/tutorial_advanced/operator_custom_with_taichi.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -4,7 +4,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"# Operator Customization with Numba"
"# Operator Customization with Taichi"
]
},
{
Expand All @@ -18,7 +18,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"Brain dynamics is sparse and event-driven, however, proprietary operators for brain dynamics are not well abstracted and summarized. As a result, we are often faced with the need to customize operators. In this tutorial, we will explore how to customize brain dynamics operators using ti.\n",
"Brain dynamics is sparse and event-driven, however, proprietary operators for brain dynamics are not well abstracted and summarized. As a result, we are often faced with the need to customize operators. In this tutorial, we will explore how to customize brain dynamics operators using taichi.\n",
"\n",
"Start by importing the relevant Python package."
]
Expand Down Expand Up @@ -242,11 +242,11 @@
" vector: ti.types.ndarray(ndim=1), \n",
" weight: ti.types.ndarray(ndim=1), \n",
" out: ti.types.ndarray(ndim=1)):\n",
" weight_0 = weight[0]\n",
" ti.loop_config(block_dim=64)\n",
" for i, j in ti.ndrange(indices.shape[0], indices.shape[1]):\n",
" if vector[i]:\n",
" out[indices[i, j]] += weight_0\n",
" weight_0 = weight[0]\n",
" ti.loop_config(block_dim=64)\n",
" for ij in ti.grouped(indices):\n",
" if vector[ij[0]]:\n",
" out[ij[1]] += weight_0\n",
"\n",
"prim = bm.XLACustomOp(cpu_kernel=event_ell_cpu, gpu_kernel=event_ell_gpu)\n",
"\n",
Expand Down Expand Up @@ -503,11 +503,11 @@
" vector: ti.types.ndarray(ndim=1), \n",
" weight: ti.types.ndarray(ndim=1), \n",
" out: ti.types.ndarray(ndim=1)):\n",
" weight_0 = weight[0]\n",
" ti.loop_config(block_dim=64)\n",
" for i, j in ti.ndrange(indices.shape[0], indices.shape[1]):\n",
" if vector[i]:\n",
" out[indices[i, j]] += weight_0\n",
" weight_0 = weight[0]\n",
" ti.loop_config(block_dim=64)\n",
" for ij in ti.grouped(indices):\n",
" if vector[ij[0]]:\n",
" out[ij[1]] += weight_0\n",
"\n",
"prim = bm.XLACustomOp(cpu_kernel=event_ell_cpu, gpu_kernel=event_ell_gpu)\n",
"\n",
Expand Down