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"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "2590bea3-bcfc-4630-8393-2c4762cb4168",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/data/dell/anaconda3/envs/torch1.8/lib/python3.8/site-packages/tqdm/auto.py:22: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
" from .autonotebook import tqdm as notebook_tqdm\n"
]
}
],
"source": [
"import torch\n",
"import joblib\n",
"import numpy as np"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "4c433f59-b8bf-47c3-9bf0-f3ca8f7a0e6c",
"metadata": {},
"outputs": [],
"source": [
"with open('torch_weights.txt', 'r') as f:\n",
" lines = f.readlines()\n",
"tkeys = [iline.strip() for iline in lines]"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "ab6977f5-2593-4dd2-9a3c-d72124ce7060",
"metadata": {},
"outputs": [],
"source": [
"with open('jax_weights.txt', 'r') as f:\n",
" lines = f.readlines()\n",
"jkeys = [iline.strip() for iline in lines]"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "67989df7-409e-43e9-8af9-6a21f0aef483",
"metadata": {},
"outputs": [],
"source": [
"# directory for jax and pytorch weights\n",
"weight_dir = '/data/dell/Desktop/GitHub/ProteinMPNN_jax/weights/torch'\n",
"dest_dir = '/data/dell/Desktop/GitHub/ProteinMPNN_jax/weights/jax'"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "c786705d-240b-4bb6-a767-adee16c501f8",
"metadata": {},
"outputs": [],
"source": [
"weight_list = [\"v_48_010\", \"v_48_020\"]"
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "b264f1d9-dab7-4f69-9486-9bffaf02adf6",
"metadata": {},
"outputs": [],
"source": [
"for iweight in weight_list:\n",
" ck = torch.load(weight_dir + '/' + iweight + '.pt', map_location='cpu')\n",
" ck_new = {}\n",
" ck_new['num_edges'] = ck['num_edges']\n",
" ck_new['noise_level'] = ck['noise_level']\n",
" ck_new['model_state_dict'] = {}\n",
" for ith, ijkey in enumerate(jkeys):\n",
" itkey = tkeys[ith]\n",
" if 'edge_embedding' in ijkey:\n",
" ck_new['model_state_dict'][ijkey] = {'w': np.array(ck['model_state_dict'][itkey]).T}\n",
" elif 'embed_token' in ijkey:\n",
" ck_new['model_state_dict'][ijkey] = {'W_s': np.array(ck['model_state_dict'][itkey])}\n",
" elif 'norm' in ijkey:\n",
" ck_new['model_state_dict'][ijkey] = {'scale': np.array(ck['model_state_dict'][itkey + '.weight']),\n",
" 'offset': np.array(ck['model_state_dict'][itkey + '.bias'])}\n",
" else:\n",
" ck_new['model_state_dict'][ijkey] = {'w': np.array(ck['model_state_dict'][itkey + '.weight']).T,\n",
" 'b': np.array(ck['model_state_dict'][itkey + '.bias']).T}\n",
" \n",
" joblib.dump(ck_new, dest_dir + '/' + iweight + '.pkl')"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "d72eca08-24b8-4e8c-942d-93ebc4e35ee3",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"id": "a6de4720-0c61-474d-9503-498c694c35f1",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"id": "c84397b9-2857-43be-90cf-2be3a6525543",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"id": "86ff0de3-2f1f-4319-a565-fa9a5eb97fdc",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3.8.13 ('torch1.8')",
"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": "3.8.13"
},
"vscode": {
"interpreter": {
"hash": "3ae0ca605930d43634b7fd9a0f47e12f386d3436786e739d9a5b581639944ad1"
}
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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