Update requirements.txt

requirements.txt

@@ -1,124 +1,9 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "964ccced",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import torch\n",
-    "\n",
-    "from shap_e.diffusion.sample import sample_latents\n",
-    "from shap_e.diffusion.gaussian_diffusion import diffusion_from_config\n",
-    "from shap_e.models.download import load_model, load_config\n",
-    "from shap_e.util.notebooks import create_pan_cameras, decode_latent_images, gif_widget"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "8eed3a76",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "2d922637",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "xm = load_model('transmitter', device=device)\n",
-    "model = load_model('text300M', device=device)\n",
-    "diffusion = diffusion_from_config(load_config('diffusion'))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "53d329d0",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "batch_size = 4\n",
-    "guidance_scale = 15.0\n",
-    "prompt = \"a shark\"\n",
-    "\n",
-    "latents = sample_latents(\n",
-    "    batch_size=batch_size,\n",
-    "    model=model,\n",
-    "    diffusion=diffusion,\n",
-    "    guidance_scale=guidance_scale,\n",
-    "    model_kwargs=dict(texts=[prompt] * batch_size),\n",
-    "    progress=True,\n",
-    "    clip_denoised=True,\n",
-    "    use_fp16=True,\n",
-    "    use_karras=True,\n",
-    "    karras_steps=64,\n",
-    "    sigma_min=1e-3,\n",
-    "    sigma_max=160,\n",
-    "    s_churn=0,\n",
-    ")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "633da2ec",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "render_mode = 'nerf' # you can change this to 'stf'\n",
-    "size = 64 # this is the size of the renders; higher values take longer to render.\n",
-    "\n",
-    "cameras = create_pan_cameras(size, device)\n",
-    "for i, latent in enumerate(latents):\n",
-    "    images = decode_latent_images(xm, latent, cameras, rendering_mode=render_mode)\n",
-    "    display(gif_widget(images))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "85a4dce4",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Example of saving the latents as meshes.\n",
-    "from shap_e.util.notebooks import decode_latent_mesh\n",
-    "\n",
-    "for i, latent in enumerate(latents):\n",
-    "    t = decode_latent_mesh(xm, latent).tri_mesh()\n",
-    "    with open(f'example_mesh_{i}.ply', 'wb') as f:\n",
-    "        t.write_ply(f)\n",
-    "    with open(f'example_mesh_{i}.obj', 'w') as f:\n",
-    "        t.write_obj(f)"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
-   "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": "3.11.3"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}
+torch==2.0.1
+torchvision==0.15.2
+diffusers==0.19.3
+transformers==4.30.2
+gradio==3.39.0
+numpy==1.23.5
+Pillow==9.5.0
+requests==2.31.0
+xformers==0.0.20