{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# [Intro](https://github.com/Ziaeemehr/vbi_paper/blob/main/docs/examples/intro.ipynb)\n",
"\n",
"![\"Open](\"https://colab.research.google.com/assets/colab-badge.svg\")
"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import vbi"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"Integrating: 100%|██████████| 1500/1500 [00:07<00:00, 204.70it/s]\n",
"Integrating: 100%|██████████| 1500/1500 [00:00<00:00, 2459.72it/s]\n",
"Integrating: 100%|██████████| 11999/11999 [00:02<00:00, 4653.43it/s]\n",
"----------------------------------------------------------------------\n",
"Ran 108 tests in 27.541s\n",
"\n",
"OK\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"0.9908645365510211\n"
]
}
],
"source": [
"vbi.tests()"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" Dependency Check \n",
" \n",
" Package Version Status \n",
" ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ \n",
" vbi v0.2 ✅ Available \n",
" numpy 1.26.4 ✅ Available \n",
" scipy 1.15.2 ✅ Available \n",
" matplotlib 3.10.0 ✅ Available \n",
" sbi 0.23.3 ✅ Available \n",
" torch 2.6.0+cu124 ✅ Available \n",
" cupy 13.3.0 ✅ Available \n",
" \n",
"\n"
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" \u001b[1;36m \u001b[0m\u001b[1;36mvbi \u001b[0m\u001b[1;36m \u001b[0m \u001b[1;32m \u001b[0m\u001b[1;32mv0.2 \u001b[0m\u001b[1;32m \u001b[0m \u001b[1;33m \u001b[0m\u001b[1;33m✅ Available\u001b[0m\u001b[1;33m \u001b[0m \n",
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" \u001b[1;36m \u001b[0m\u001b[1;36mmatplotlib\u001b[0m\u001b[1;36m \u001b[0m \u001b[1;32m \u001b[0m\u001b[1;32m3.10.0 \u001b[0m\u001b[1;32m \u001b[0m \u001b[1;33m \u001b[0m\u001b[1;33m✅ Available\u001b[0m\u001b[1;33m \u001b[0m \n",
" \u001b[1;36m \u001b[0m\u001b[1;36msbi \u001b[0m\u001b[1;36m \u001b[0m \u001b[1;32m \u001b[0m\u001b[1;32m0.23.3 \u001b[0m\u001b[1;32m \u001b[0m \u001b[1;33m \u001b[0m\u001b[1;33m✅ Available\u001b[0m\u001b[1;33m \u001b[0m \n",
" \u001b[1;36m \u001b[0m\u001b[1;36mtorch \u001b[0m\u001b[1;36m \u001b[0m \u001b[1;32m \u001b[0m\u001b[1;32m2.6.0+cu124\u001b[0m\u001b[1;32m \u001b[0m \u001b[1;33m \u001b[0m\u001b[1;33m✅ Available\u001b[0m\u001b[1;33m \u001b[0m \n",
" \u001b[1;36m \u001b[0m\u001b[1;36mcupy \u001b[0m\u001b[1;36m \u001b[0m \u001b[1;32m \u001b[0m\u001b[1;32m13.3.0 \u001b[0m\u001b[1;32m \u001b[0m \u001b[1;33m \u001b[0m\u001b[1;33m✅ Available\u001b[0m\u001b[1;33m \u001b[0m \n",
" \n"
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"metadata": {},
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{
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"\n"
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{
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"text": [
"CUDA Version: 12.6\n",
"Device Name: NVIDIA RTX A5000\n",
"Total Memory: 23.68 GB\n",
"Compute Capability: 8.6\n"
]
}
],
"source": [
"vbi.test_imports()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
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"name": "python"
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