Created using Colaboratory

This commit is contained in:
Marius Ciepluch 2024-04-04 17:53:57 +02:00
parent 564ed54344
commit eef5b798b4

View File

@ -50,6 +50,8 @@
"source": [
"import sys\n",
"import os\n",
"import subprocess\n",
"\n",
"IN_COLAB = 'google.colab' in sys.modules\n",
"\n",
"if not IN_COLAB:\n",
@ -69,6 +71,12 @@
" output_path_extracted_notes = \"/content/export.txt\"\n",
" output_path_extracted_docs = \"/content/export.documents.txt\"\n",
" result_db = \"/content/evernote.db\"\n",
" subprocess.run('''\n",
" source <(curl -s https://raw.githubusercontent.com/norandom/project_bookworm/main/scripts/prepare_colab_env.sh)\n",
" ''',\n",
" shell=True, check=True,\n",
" executable='/bin/bash')\n",
"\n",
"\n",
"# To suppress some warnings\n",
"import os\n",
@ -76,16 +84,14 @@
]
},
{
"cell_type": "code",
"cell_type": "markdown",
"source": [
"# Controls:"
"# Checks"
],
"metadata": {
"id": "8tcn27pzvpRi"
"id": "yuhXPdN_z2cW"
},
"id": "8tcn27pzvpRi",
"execution_count": 2,
"outputs": []
"id": "yuhXPdN_z2cW"
},
{
"cell_type": "code",
@ -111,6 +117,16 @@
}
]
},
{
"cell_type": "markdown",
"source": [
"## For the progress bars in Colab"
],
"metadata": {
"id": "B02AY_Gez61T"
},
"id": "B02AY_Gez61T"
},
{
"cell_type": "code",
"source": [
@ -668,7 +684,7 @@
},
{
"cell_type": "code",
"execution_count": 7,
"execution_count": 28,
"id": "3081256c9cf22780",
"metadata": {
"ExecuteTime": {
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"base_uri": "https://localhost:8080/"
},
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"outputId": "0a02f0bc-42ce-4f50-e670-fd8ca48111a9"
},
"outputs": [
{
@ -698,7 +714,7 @@
"import torch\n",
"use_cuda = torch.cuda.is_available()\n",
"\n",
"USE_GPU=False\n",
"USE_GPU=True\n",
"\n",
"if use_cuda:\n",
" print('__CUDNN VERSION:', torch.backends.cudnn.version())\n",
@ -709,7 +725,8 @@
" print(\"GPU enabled\")\n",
"\n",
"if not use_cuda:\n",
" print('No CUDA available')"
" print('No CUDA available')\n",
" USE_GPU=False\n"
]
},
{
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{
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"data": {
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"def vectorize_data_in_batches(chunks, embeddings):\n",
"\n",
" num_workers = 3\n",
" batch_size = 750 # Adjust based on your needs and memory constraints\n",
" batch_size = 500 # Adjust based on your needs and memory constraints\n",
"\n",
" batches = list(divide_chunks(chunks, batch_size))\n",
" faiss_db = None\n",
@ -970,11 +987,11 @@
"print(type(faiss))"
],
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