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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "acb05338-490d-44c8-9923-7fb70d3465a2",
"metadata": {},
"outputs": [],
"source": [
"import torch\n",
"import json\n",
"class Config:pass"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "7dcd2d48-0ad7-4cde-99f7-d8c719026a85",
"metadata": {},
"outputs": [],
"source": [
"walloc_20x = torch.load(\"Stereo_Li_27c_test2.pth\",map_location='cpu', weights_only=False)\n",
"config = walloc_20x['config']\n",
"with open('stereo_20x.json', 'w') as f:\n",
" json.dump(config.__dict__, f, indent=4)\n",
"del walloc_20x['config']\n",
"torch.save(walloc_20x, 'stereo_20x.pth')"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "0b5ddce5-8f83-484b-9a86-b6e3b799904c",
"metadata": {},
"outputs": [],
"source": [
"walloc_5x = torch.load(\"Stereo_Li_108c_test2.pth\",map_location='cpu', weights_only=False)\n",
"config = walloc_5x['config']\n",
"with open('stereo_5x.json', 'w') as f:\n",
" json.dump(config.__dict__, f, indent=4)\n",
"del walloc_5x['config']\n",
"torch.save(walloc_20x, 'stereo_5x.pth')"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "0de59093-db74-4b08-ac45-f1b832529dcb",
"metadata": {},
"outputs": [],
"source": [
"walloc_16x = torch.load(\"RGB_Li_12c_J3_nf8_v1.0.2.pth\",map_location='cpu', weights_only=False)\n",
"config = walloc_16x['config']\n",
"with open('RGB_16x.json', 'w') as f:\n",
" json.dump(config.__dict__, f, indent=4)\n",
"del walloc_16x['config']\n",
"del walloc_16x['i_epoch']\n",
"del walloc_16x['learning_rates']\n",
"del walloc_16x['dist_losses']\n",
"torch.save(walloc_16x, 'RGB_16x.pth')"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "235117df-ddf4-4f72-a5a8-8395412f8eff",
"metadata": {},
"outputs": [],
"source": [
"walloc_4x = torch.load(\"RGB_Li_48c_J3_nf8_v1.0.2.pth\",map_location='cpu', weights_only=False)\n",
"config = walloc_4x['config']\n",
"with open('RGB_4x.json', 'w') as f:\n",
" json.dump(config.__dict__, f, indent=4)\n",
"del walloc_4x['config']\n",
"del walloc_4x['i_epoch']\n",
"del walloc_4x['learning_rates']\n",
"del walloc_4x['dist_losses']\n",
"torch.save(walloc_4x, 'RGB_4x.pth')"
]
}
],
"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": "3.12.3"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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