85 lines
1.7 KiB
Plaintext
85 lines
1.7 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"import os\n",
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"\n",
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"root = \"model_assets/jvnv-F1\"\n",
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"pth_files = [os.path.join(root, f) for f in os.listdir(root) if f.endswith(\".pth\")]"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"metadata": {},
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"outputs": [],
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"source": [
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"import torch\n",
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"\n",
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"model_name = \"G_0.pth\"\n",
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"model = torch.load(f\"pretrained/{model_name}\", map_location=torch.device(\"cpu\"))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"enc_p.emo_proj.bias\n",
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"enc_p.emo_q_proj.weight\n",
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"enc_p.emo_q_proj.bias\n"
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]
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}
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],
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"source": [
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"from safetensors.torch import save_file\n",
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"state_dict = model[\"model\"]\n",
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"new_dict = {}\n",
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"for k in state_dict.keys():\n",
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" if k.startswith(\"enc_p.emo\"):\n",
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" print(k)\n",
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" else:\n",
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" new_dict[k] = state_dict[k]\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"metadata": {},
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"outputs": [],
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"source": [
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"save_file(new_dict, f\"pretrained/{model_name.replace('.pth', '.safetensors')}\")"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "venv",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.10.11"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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