{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[2024-01-25 14:09:17,046] [INFO] [real_accelerator.py:161:get_accelerator] Setting ds_accelerator to cuda (auto detect)\n" ] } ], "source": [ "import torch\n", "import diffusers\n", "from utils import patch_attention_proc, remove_patch\n", "from diffusers.utils.import_utils import is_xformers_available\n", "from torch.nn import functional as F\n", "\n", "xformers_is_available = is_xformers_available()\n", "\n", "if hasattr(F, \"scaled_dot_product_attention\"):\n", " torch2_is_available = True\n", "else:\n", " torch2_is_available = False\n", "\n" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "unet/diffusion_pytorch_model.safetensors not found\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "729070b2f3cf4da59050d36c0f58b7e2", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Loading pipeline components...: 0%| | 0/7 [00:00" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "base_img" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "pipe.unet.down_blocks[0].attentions[0].transformer_blocks[0].attn1.processor" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "ecc359d85a344dc4a72b7ba6e476f746", "version_major": 2, "version_minor": 0 }, "text/plain": [ " 0%| | 0/25 [00:00" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "merged_img" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'size': (256, 256),\n", " 'timestep': 1.0,\n", " 'hooks': [],\n", " 'args': {'ratio': 0.75,\n", " 'sx': 2,\n", " 'sy': 2,\n", " 'use_rand': True,\n", " 'generator': ,\n", " 'merge_tokens': 'keys/values',\n", " 'merge_method': 'downsample',\n", " 'downsample_method': 'nearest-exact',\n", " 'downsample_factor': 4,\n", " 'timestep_threshold_switch': 0.2,\n", " 'timestep_threshold_stop': 0.0,\n", " 'secondary_merge_method': 'similarity',\n", " 'downsample_factor_level_2': 2,\n", " 'ratio_level_2': 0.5}}" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "pipe.unet._tome_info" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "pipe.unet.down_blocks[0].attentions[0].transformer_blocks[0].attn1.processor" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "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": "3.8.10" } }, "nbformat": 4, "nbformat_minor": 2 }