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[WIP] add benchmarking scripts #615

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4f4bc50
add script
radekosmulski Feb 15, 2023
e35bd1f
update
radekosmulski Feb 20, 2023
a1a6a5d
add randomized input generation (input.json)
radekosmulski Feb 21, 2023
553498d
update
radekosmulski Feb 21, 2023
b9ed7a0
update
radekosmulski Mar 7, 2023
67aec99
add train_runs
radekosmulski Mar 10, 2023
158db3e
add ability to modify schema for training
radekosmulski Apr 5, 2023
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532 changes: 532 additions & 0 deletions benchmarking.ipynb
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164 changes: 164 additions & 0 deletions generate_randomized_input_for_benchmarking.ipynb
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Original file line number Diff line number Diff line change
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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "486c0d66",
"metadata": {},
"outputs": [],
"source": [
"j = \"\"\"\n",
" { \n",
" \"data\" :\n",
" [\n",
" {\n",
" \"sess_pid_seq__values\" : [0,1,2,3,4,5,6,7,8,9,10,11,12,13,15,16,17,18,19],\n",
" \"sess_pid_seq__nnzs\" : [0,20]\n",
" }\n",
" ]\n",
" }\n",
"\"\"\""
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "8d629daf",
"metadata": {},
"outputs": [],
"source": [
"import json"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "e95ca248",
"metadata": {},
"outputs": [],
"source": [
"d = json.loads(j)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "1f7836da",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'data': [{'sess_pid_seq__values': [0,\n",
" 1,\n",
" 2,\n",
" 3,\n",
" 4,\n",
" 5,\n",
" 6,\n",
" 7,\n",
" 8,\n",
" 9,\n",
" 10,\n",
" 11,\n",
" 12,\n",
" 13,\n",
" 15,\n",
" 16,\n",
" 17,\n",
" 18,\n",
" 19],\n",
" 'sess_pid_seq__nnzs': [0, 20]}]}"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"d"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "f4cbfe0d",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'{\"data\": [{\"sess_pid_seq__values\": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 15, 16, 17, 18, 19], \"sess_pid_seq__nnzs\": [0, 20]}]}'"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"json.dumps(d)"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "18cfd44c",
"metadata": {},
"outputs": [],
"source": [
"import numpy as np"
]
},
{
"cell_type": "code",
"execution_count": 21,
"id": "353b82cb",
"metadata": {},
"outputs": [],
"source": [
"data_as_dict = {'data': []}\n",
"\n",
"for i in range(10_000):\n",
" payload = {}\n",
" payload['sess_pid_seq__values'] = np.random.randint(0, 390001, 20).tolist()\n",
" payload['sess_pid_seq__nnzs'] = [0, 20]\n",
" \n",
" data_as_dict['data'].append(payload)"
]
},
{
"cell_type": "code",
"execution_count": 22,
"id": "ef9c5f38",
"metadata": {},
"outputs": [],
"source": [
"with open('input.json', 'w') as f:\n",
" json.dump(data_as_dict, f)"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.10"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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