diff --git "a/notebooks/inpainting.ipynb" "b/notebooks/inpainting.ipynb" new file mode 100644--- /dev/null +++ "b/notebooks/inpainting.ipynb" @@ -0,0 +1,217 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 35, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "import gc\n", + "import torch\n", + "\n", + "def show_mask(mask, ax, random_color=False):\n", + " if random_color:\n", + " color = np.concatenate([np.random.random(3), np.array([0.6])], axis=0)\n", + " else:\n", + " color = np.array([30 / 255, 144 / 255, 255 / 255, 0.6])\n", + " h, w = mask.shape[-2:]\n", + " mask_image = mask.reshape(h, w, 1) * color.reshape(1, 1, -1)\n", + " ax.imshow(mask_image)\n", + " del mask\n", + " gc.collect()\n", + " torch.cuda.empty_cache()\n", + "\n", + "def show_masks_on_image(raw_image, masks):\n", + " plt.imshow(np.array(raw_image))\n", + " ax = plt.gca()\n", + " ax.set_autoscale_on(False)\n", + " for mask in masks:\n", + " show_mask(mask, ax=ax, random_color=True)\n", + " plt.axis(\"off\")\n", + " plt.show()\n", + " del mask\n", + " gc.collect()\n", + " torch.cuda.empty_cache()" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [ + { + "ename": "OutOfMemoryError", + "evalue": "CUDA out of memory. Tried to allocate 26.00 MiB. GPU 0 has a total capacity of 23.64 GiB of which 15.62 MiB is free. Process 433712 has 23.62 GiB memory in use. Of the allocated memory 23.34 GiB is allocated by PyTorch, and 80.13 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mOutOfMemoryError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[32], line 2\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mtransformers\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m pipeline\n\u001b[0;32m----> 2\u001b[0m generator \u001b[38;5;241m=\u001b[39m \u001b[43mpipeline\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mmask-generation\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmodel\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mfacebook/sam-vit-huge\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdevice\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/product_diffusion_api/.venv/lib/python3.10/site-packages/transformers/pipelines/__init__.py:1107\u001b[0m, in \u001b[0;36mpipeline\u001b[0;34m(task, model, config, tokenizer, feature_extractor, image_processor, framework, revision, use_fast, token, device, device_map, torch_dtype, trust_remote_code, model_kwargs, pipeline_class, **kwargs)\u001b[0m\n\u001b[1;32m 1104\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m device \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 1105\u001b[0m kwargs[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mdevice\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m=\u001b[39m device\n\u001b[0;32m-> 1107\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mpipeline_class\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmodel\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmodel\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mframework\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mframework\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtask\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtask\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/product_diffusion_api/.venv/lib/python3.10/site-packages/transformers/pipelines/mask_generation.py:85\u001b[0m, in \u001b[0;36mMaskGenerationPipeline.__init__\u001b[0;34m(self, **kwargs)\u001b[0m\n\u001b[1;32m 84\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__init__\u001b[39m(\u001b[38;5;28mself\u001b[39m, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[0;32m---> 85\u001b[0m \u001b[38;5;28;43msuper\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[38;5;21;43m__init__\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 86\u001b[0m requires_backends(\u001b[38;5;28mself\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mvision\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 87\u001b[0m requires_backends(\u001b[38;5;28mself\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtorch\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n", + "File \u001b[0;32m~/product_diffusion_api/.venv/lib/python3.10/site-packages/transformers/pipelines/base.py:874\u001b[0m, in \u001b[0;36mPipeline.__init__\u001b[0;34m(self, model, tokenizer, feature_extractor, image_processor, modelcard, framework, task, args_parser, device, torch_dtype, binary_output, **kwargs)\u001b[0m\n\u001b[1;32m 867\u001b[0m \u001b[38;5;66;03m# We shouldn't call `model.to()` for models loaded with accelerate\u001b[39;00m\n\u001b[1;32m 868\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m (\n\u001b[1;32m 869\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mframework \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mpt\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 870\u001b[0m \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdevice \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m 871\u001b[0m \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m (\u001b[38;5;28misinstance\u001b[39m(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdevice, \u001b[38;5;28mint\u001b[39m) \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdevice \u001b[38;5;241m<\u001b[39m \u001b[38;5;241m0\u001b[39m)\n\u001b[1;32m 872\u001b[0m \u001b[38;5;129;01mand\u001b[39;00m hf_device_map \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m 873\u001b[0m ):\n\u001b[0;32m--> 874\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmodel\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mto\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdevice\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 876\u001b[0m \u001b[38;5;66;03m# Update config and generation_config with task specific parameters\u001b[39;00m\n\u001b[1;32m 877\u001b[0m task_specific_params \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmodel\u001b[38;5;241m.\u001b[39mconfig\u001b[38;5;241m.\u001b[39mtask_specific_params\n", + "File \u001b[0;32m~/product_diffusion_api/.venv/lib/python3.10/site-packages/transformers/modeling_utils.py:2556\u001b[0m, in \u001b[0;36mPreTrainedModel.to\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m 2551\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m dtype_present_in_args:\n\u001b[1;32m 2552\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[1;32m 2553\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mYou cannot cast a GPTQ model in a new `dtype`. Make sure to load the model using `from_pretrained` using the desired\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 2554\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m `dtype` by passing the correct `torch_dtype` argument.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 2555\u001b[0m )\n\u001b[0;32m-> 2556\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43msuper\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mto\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/product_diffusion_api/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:1152\u001b[0m, in \u001b[0;36mModule.to\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m 1148\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m t\u001b[38;5;241m.\u001b[39mto(device, dtype \u001b[38;5;28;01mif\u001b[39;00m t\u001b[38;5;241m.\u001b[39mis_floating_point() \u001b[38;5;129;01mor\u001b[39;00m t\u001b[38;5;241m.\u001b[39mis_complex() \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[1;32m 1149\u001b[0m non_blocking, memory_format\u001b[38;5;241m=\u001b[39mconvert_to_format)\n\u001b[1;32m 1150\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m t\u001b[38;5;241m.\u001b[39mto(device, dtype \u001b[38;5;28;01mif\u001b[39;00m t\u001b[38;5;241m.\u001b[39mis_floating_point() \u001b[38;5;129;01mor\u001b[39;00m t\u001b[38;5;241m.\u001b[39mis_complex() \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m, non_blocking)\n\u001b[0;32m-> 1152\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_apply\u001b[49m\u001b[43m(\u001b[49m\u001b[43mconvert\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/product_diffusion_api/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:802\u001b[0m, in \u001b[0;36mModule._apply\u001b[0;34m(self, fn, recurse)\u001b[0m\n\u001b[1;32m 800\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m recurse:\n\u001b[1;32m 801\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m module \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mchildren():\n\u001b[0;32m--> 802\u001b[0m \u001b[43mmodule\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_apply\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfn\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 804\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mcompute_should_use_set_data\u001b[39m(tensor, tensor_applied):\n\u001b[1;32m 805\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m torch\u001b[38;5;241m.\u001b[39m_has_compatible_shallow_copy_type(tensor, tensor_applied):\n\u001b[1;32m 806\u001b[0m \u001b[38;5;66;03m# If the new tensor has compatible tensor type as the existing tensor,\u001b[39;00m\n\u001b[1;32m 807\u001b[0m \u001b[38;5;66;03m# the current behavior is to change the tensor in-place using `.data =`,\u001b[39;00m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 812\u001b[0m \u001b[38;5;66;03m# global flag to let the user control whether they want the future\u001b[39;00m\n\u001b[1;32m 813\u001b[0m \u001b[38;5;66;03m# behavior of overwriting the existing tensor or not.\u001b[39;00m\n", + "File \u001b[0;32m~/product_diffusion_api/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:802\u001b[0m, in \u001b[0;36mModule._apply\u001b[0;34m(self, fn, recurse)\u001b[0m\n\u001b[1;32m 800\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m recurse:\n\u001b[1;32m 801\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m module \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mchildren():\n\u001b[0;32m--> 802\u001b[0m \u001b[43mmodule\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_apply\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfn\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 804\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mcompute_should_use_set_data\u001b[39m(tensor, tensor_applied):\n\u001b[1;32m 805\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m torch\u001b[38;5;241m.\u001b[39m_has_compatible_shallow_copy_type(tensor, tensor_applied):\n\u001b[1;32m 806\u001b[0m \u001b[38;5;66;03m# If the new tensor has compatible tensor type as the existing tensor,\u001b[39;00m\n\u001b[1;32m 807\u001b[0m \u001b[38;5;66;03m# the current behavior is to change the tensor in-place using `.data =`,\u001b[39;00m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 812\u001b[0m \u001b[38;5;66;03m# global flag to let the user control whether they want the future\u001b[39;00m\n\u001b[1;32m 813\u001b[0m \u001b[38;5;66;03m# behavior of overwriting the existing tensor or not.\u001b[39;00m\n", + " \u001b[0;31m[... skipping similar frames: Module._apply at line 802 (2 times)]\u001b[0m\n", + "File \u001b[0;32m~/product_diffusion_api/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:802\u001b[0m, in \u001b[0;36mModule._apply\u001b[0;34m(self, fn, recurse)\u001b[0m\n\u001b[1;32m 800\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m recurse:\n\u001b[1;32m 801\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m module \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mchildren():\n\u001b[0;32m--> 802\u001b[0m \u001b[43mmodule\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_apply\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfn\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 804\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mcompute_should_use_set_data\u001b[39m(tensor, tensor_applied):\n\u001b[1;32m 805\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m torch\u001b[38;5;241m.\u001b[39m_has_compatible_shallow_copy_type(tensor, tensor_applied):\n\u001b[1;32m 806\u001b[0m \u001b[38;5;66;03m# If the new tensor has compatible tensor type as the existing tensor,\u001b[39;00m\n\u001b[1;32m 807\u001b[0m \u001b[38;5;66;03m# the current behavior is to change the tensor in-place using `.data =`,\u001b[39;00m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 812\u001b[0m \u001b[38;5;66;03m# global flag to let the user control whether they want the future\u001b[39;00m\n\u001b[1;32m 813\u001b[0m \u001b[38;5;66;03m# behavior of overwriting the existing tensor or not.\u001b[39;00m\n", + "File \u001b[0;32m~/product_diffusion_api/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:825\u001b[0m, in \u001b[0;36mModule._apply\u001b[0;34m(self, fn, recurse)\u001b[0m\n\u001b[1;32m 821\u001b[0m \u001b[38;5;66;03m# Tensors stored in modules are graph leaves, and we don't want to\u001b[39;00m\n\u001b[1;32m 822\u001b[0m \u001b[38;5;66;03m# track autograd history of `param_applied`, so we have to use\u001b[39;00m\n\u001b[1;32m 823\u001b[0m \u001b[38;5;66;03m# `with torch.no_grad():`\u001b[39;00m\n\u001b[1;32m 824\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m torch\u001b[38;5;241m.\u001b[39mno_grad():\n\u001b[0;32m--> 825\u001b[0m param_applied \u001b[38;5;241m=\u001b[39m \u001b[43mfn\u001b[49m\u001b[43m(\u001b[49m\u001b[43mparam\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 826\u001b[0m should_use_set_data \u001b[38;5;241m=\u001b[39m compute_should_use_set_data(param, param_applied)\n\u001b[1;32m 827\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m should_use_set_data:\n", + "File \u001b[0;32m~/product_diffusion_api/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py:1150\u001b[0m, in \u001b[0;36mModule.to..convert\u001b[0;34m(t)\u001b[0m\n\u001b[1;32m 1147\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m convert_to_format \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mand\u001b[39;00m t\u001b[38;5;241m.\u001b[39mdim() \u001b[38;5;129;01min\u001b[39;00m (\u001b[38;5;241m4\u001b[39m, \u001b[38;5;241m5\u001b[39m):\n\u001b[1;32m 1148\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m t\u001b[38;5;241m.\u001b[39mto(device, dtype \u001b[38;5;28;01mif\u001b[39;00m t\u001b[38;5;241m.\u001b[39mis_floating_point() \u001b[38;5;129;01mor\u001b[39;00m t\u001b[38;5;241m.\u001b[39mis_complex() \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[1;32m 1149\u001b[0m non_blocking, memory_format\u001b[38;5;241m=\u001b[39mconvert_to_format)\n\u001b[0;32m-> 1150\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mt\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mto\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdevice\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdtype\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mif\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mt\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mis_floating_point\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01mor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mt\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mis_complex\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01melse\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mnon_blocking\u001b[49m\u001b[43m)\u001b[49m\n", + "\u001b[0;31mOutOfMemoryError\u001b[0m: CUDA out of memory. Tried to allocate 26.00 MiB. GPU 0 has a total capacity of 23.64 GiB of which 15.62 MiB is free. Process 433712 has 23.62 GiB memory in use. Of the allocated memory 23.34 GiB is allocated by PyTorch, and 80.13 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)" + ] + } + ], + "source": [ + "from transformers import pipeline\n", + "generator = pipeline(\"mask-generation\", model=\"facebook/sam-vit-huge\", device=0)\n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": {}, + "outputs": [], + "source": [ + "torch.cuda.empty_cache()" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from PIL import Image\n", + "import requests\n", + "\n", + "\n", + "raw_image = Image.open('/home/product_diffusion_api/sample_data/example1.jpg')\n", + "\n", + "plt.imshow(raw_image)\n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/product_diffusion_api/.venv/lib/python3.10/site-packages/transformers/pipelines/base.py:1157: UserWarning: You seem to be using the pipelines sequentially on GPU. In order to maximize efficiency please use a dataset\n", + " warnings.warn(\n" + ] + } + ], + "source": [ + "\n", + "outputs = generator(raw_image, points_per_batch=128, pred_iou_thresh=1)" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "masks = outputs[\"masks\"]\n", + "for mask in masks:\n", + " show_mask(mask, ax=plt.gca(), random_color=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Fetching 18 files: 33%|███▎ | 6/18 [01:56<05:01, 25.11s/it]" + ] + } + ], + "source": [ + "import torch\n", + "from diffusers import DiffusionPipeline\n", + "from diffusers.utils import load_image, make_image_grid\n", + "\n", + "pipeline = DiffusionPipeline.from_pretrained(\n", + " \"AlekseyKorshuk/sdxl-v0-product-outpainting\", torch_dtype=torch.float16\n", + ").to(\"cuda\")\n", + "pipeline.enable_model_cpu_offload()\n", + "# remove following line if xFormers is not installed or you have PyTorch 2.0 or higher installed\n", + "\n", + "\n", + "# load base and mask image\n", + "init_image = load_image(\"/home/product_diffusion_api/sample_data/example1.jpg\")\n", + "mask_image = load_image(\"/home/product_diffusion_api/masks/mask_0.jpg\")\n", + "\n", + "generator = torch.Generator(\"cuda\").manual_seed(92)\n", + "prompt = \"the object being used in a kitchen for meal prepration , ultrarealistic, high quality, high resolution, 8k\"\n", + "image = pipeline(prompt=prompt, image=init_image, mask_image=mask_image, generator=generator).images[0]\n", + "make_image_grid([init_image, image], rows=1, cols=2)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": ".venv", + "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": "3.10.13" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +}