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Running
on
Zero
File size: 3,487 Bytes
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{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"id": "9c480696",
"metadata": {},
"outputs": [],
"source": [
"%cd /home/ubuntu/Qwen-Image-Edit-Angles"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "671fc929",
"metadata": {},
"outputs": [],
"source": [
"import os\n",
"import subprocess\n",
"from pathlib import Path\n",
"import argparse\n",
"import warnings\n",
"\n",
"import yaml\n",
"import diffusers\n",
"\n",
"\n",
"from wandml.trainers.experiment_trainer import ExperimentTrainer\n",
"from wandml import WandDataPipe\n",
"import wandml\n",
"from wandml import WandAuth\n",
"from wandml import utils as wandml_utils\n",
"from wandml.trainers.datamodels import ExperimentTrainerParameters\n",
"from wandml.trainers.experiment_trainer import ExperimentTrainer\n",
"\n",
"\n",
"from qwenimage.finetuner import QwenLoraFinetuner\n",
"from qwenimage.sources import EditingSource, RegressionSource, StyleSourceWithRandomRef, StyleImagetoImageSource\n",
"from qwenimage.task import RegressionTask, TextToImageWithRefTask\n",
"from qwenimage.datamodels import QwenConfig\n",
"from qwenimage.foundation import QwenImageFoundation, QwenImageRegressionFoundation\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "6a646ed7",
"metadata": {},
"outputs": [],
"source": [
"src = EditingSource(\n",
" data_dir=\"/data/CrispEdit\",\n",
" total_per=10,\n",
")"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "35dda5f4",
"metadata": {},
"outputs": [],
"source": [
"config = QwenConfig(\n",
" training_type=\"regression\",\n",
" regression_base_pipe_steps=8,\n",
")\n",
"foundation = QwenImageRegressionFoundation(config=config)\n",
"# finetuner = QwenLoraFinetuner(foundation, config)\n",
"# finetuner.load(\"/data/checkpoints/reg-mse-pixel-mse_015000\", config.lora_rank)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "8d5ddfa5",
"metadata": {},
"outputs": [],
"source": [
"src[0]"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "264070a6",
"metadata": {},
"outputs": [],
"source": [
"foundation.config.regression_base_pipe_steps = 4\n",
"\n",
"inp = src[100]\n",
"\n",
"out = foundation.base_pipe(foundation.INPUT_MODEL(\n",
" prompt=inp[0],\n",
" image=[inp[2]],\n",
"))\n",
"out"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "46a09a41",
"metadata": {},
"outputs": [],
"source": [
"print(inp[0])\n",
"inp[2]"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "da4157ea",
"metadata": {},
"outputs": [],
"source": [
"out[0]"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "7446e6b3",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"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": "3.10.12"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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