prolific_dreamer_2D.ipynb

{"cells":[{"attachments":{},"cell_type":"markdown","metadata":{"id":""},"source":["### 2D Implementation of paper [ProlificDreamer: High-Fidelity and Diverse Text-to-3D Generation with Variational Score Distillation](https://arxiv.org/abs/2305.16213)"]},{"cell_type":"code","execution_count":1,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":1836,"status":"ok","timestamp":1688415664816,"user":{"displayName":"Mr. Z","userId":"12849447431415807254"},"user_tz":-120},"id":"nZ8O3OaMb6tO","outputId":"94a6e43d-e1eb-4760-e7ac-e6797b90a8b2"},"outputs":[{"name":"stdout","output_type":"stream","text":["Cloning into 'prolific_dreamer2d'...\n","remote: Enumerating objects: 48, done.\u001b[K\n","remote: Counting objects: 100% (48/48), done.\u001b[K\n","remote: Compressing objects: 100% (36/36), done.\u001b[K\n","remote: Total 48 (delta 24), reused 34 (delta 11), pack-reused 0\u001b[K\n","Unpacking objects: 100% (48/48), 11.70 MiB | 12.70 MiB/s, done.\n"]}],"source":["### clone the repo\n","!git clone https://github.com/yuanzhi-zhu/prolific_dreamer2d.git"]},{"cell_type":"code","execution_count":2,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":229,"status":"ok","timestamp":1688415667441,"user":{"displayName":"Mr. Z","userId":"12849447431415807254"},"user_tz":-120},"id":"M3XU3N2HaG2Q","outputId":"e955f257-a153-4e5c-df3a-46dd99998fe6"},"outputs":[{"name":"stdout","output_type":"stream","text":["Mon Jul  3 20:21:06 2023       \n","+-----------------------------------------------------------------------------+\n","| NVIDIA-SMI 525.85.12    Driver Version: 525.85.12    CUDA Version: 12.0     |\n","|-------------------------------+----------------------+----------------------+\n","| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |\n","| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |\n","|                               |                      |               MIG M. |\n","|===============================+======================+======================|\n","|   0  Tesla T4            Off  | 00000000:00:04.0 Off |                    0 |\n","| N/A   53C    P8    10W /  70W |      0MiB / 15360MiB |      0%      Default |\n","|                               |                      |                  N/A |\n","+-------------------------------+----------------------+----------------------+\n","                                                                               \n","+-----------------------------------------------------------------------------+\n","| Processes:                                                                  |\n","|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |\n","|        ID   ID                                                   Usage      |\n","|=============================================================================|\n","|  No running processes found                                                 |\n","+-----------------------------------------------------------------------------+\n"]}],"source":["!nvidia-smi"]},{"cell_type":"code","execution_count":3,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":243,"status":"ok","timestamp":1688415673108,"user":{"displayName":"Mr. Z","userId":"12849447431415807254"},"user_tz":-120},"id":"fSKEAVEmXlNY","outputId":"c22ad3ec-0e48-4d4d-a497-2c4e04046df0"},"outputs":[{"name":"stdout","output_type":"stream","text":["/content/prolific_dreamer2d\n"]}],"source":["cd prolific_dreamer2d"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"FrOaU53OZQ4p"},"outputs":[],"source":["!pip install --upgrade pip\n","!pip install -r requirements.txt"]},{"cell_type":"code","execution_count":7,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":858791,"status":"ok","timestamp":1688416997796,"user":{"displayName":"Mr. Z","userId":"12849447431415807254"},"user_tz":-120},"id":"aX7Y9TqvYlmg","outputId":"100b4aee-864d-4cc0-b278-cb566bda1bd8"},"outputs":[{"name":"stdout","output_type":"stream","text":["2023-07-03 20:29:05.531330: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n","/content/prolific_dreamer2d/model_utils.py:113: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).\n","  betas = torch.tensor(betas)\n","/content/prolific_dreamer2d/prolific_dreamer2d.py:253: FutureWarning: Accessing config attribute `in_channels` directly via 'UNet2DConditionModel' object attribute is deprecated. Please access 'in_channels' over 'UNet2DConditionModel's config object instead, e.g. 'unet.config.in_channels'.\n","  particles = torch.randn((args.batch_size, unet.in_channels, args.height // 8, args.width // 8))\n","Total number of trainable parameters in particles: 16384; number of particles: 1\n","number of trainable parameters of phi model in optimizer: 829952\n","Loss: 0.059880, sampled t : 663: 100% 500/500 [13:22<00:00,  1.61s/it]\n"]}],"source":["!bash run.sh"]}],"metadata":{"accelerator":"GPU","colab":{"authorship_tag":"ABX9TyNKWAFmj6bMlwWn4SdDP5HL","provenance":[]},"gpuClass":"standard","kernelspec":{"display_name":"Python 3","name":"python3"},"language_info":{"name":"python"}},"nbformat":4,"nbformat_minor":0}