Notebooks/3DPix2Pix/Pix3Pix.ipynb

{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"name":"python","version":"3.10.14","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"},"kaggle":{"accelerator":"nvidiaTeslaT4","dataSources":[{"sourceId":8265873,"sourceType":"datasetVersion","datasetId":4906907}],"dockerImageVersionId":30787,"isInternetEnabled":true,"language":"python","sourceType":"notebook","isGpuEnabled":true}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"code","source":"# This Python 3 environment comes with many helpful analytics libraries installed\n# It is defined by the kaggle/python Docker image: https://github.com/kaggle/docker-python\n# For example, here's several helpful packages to load\n\nimport numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n\n# Input data files are available in the read-only \"../input/\" directory\n# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n\nimport os\nfor dirname, _, filenames in os.walk('/kaggle/input'):\n    for filename in filenames:\n        print(os.path.join(dirname, filename))\n\n# You can write up to 20GB to the current directory (/kaggle/working/) that gets preserved as output when you create a version using \"Save & Run All\" \n# You can also write temporary files to /kaggle/temp/, but they won't be saved outside of the current session","metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"!pip install trimesh\nimport os\nimport json\nimport torch\nfrom torch.utils.data import Dataset, DataLoader\nfrom PIL import Image\nimport numpy as np\nimport scipy.io\nimport logging\nimport torch.nn as nn\nimport torchvision\nimport torchvision.models as models\nimport torchvision.datasets as datasets\nimport matplotlib.pyplot as plt\nimport plotly.express as px\nimport plotly.graph_objects as go\nimport torchvision.transforms as transforms\nimport torch.nn.functional as F\nfrom mpl_toolkits.mplot3d import Axes3D\nfrom tqdm.auto import tqdm\nfrom torchvision.utils import make_grid","metadata":{"execution":{"iopub.status.busy":"2024-10-10T03:11:32.070677Z","iopub.execute_input":"2024-10-10T03:11:32.071425Z","iopub.status.idle":"2024-10-10T03:11:57.486949Z","shell.execute_reply.started":"2024-10-10T03:11:32.071386Z","shell.execute_reply":"2024-10-10T03:11:57.485935Z"},"trusted":true},"execution_count":5,"outputs":[{"name":"stdout","text":"Collecting trimesh\n  Downloading trimesh-4.4.9-py3-none-any.whl.metadata (18 kB)\nRequirement already satisfied: numpy>=1.20 in /opt/conda/lib/python3.10/site-packages (from trimesh) (1.26.4)\nDownloading trimesh-4.4.9-py3-none-any.whl (700 kB)\n\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m700.1/700.1 kB\u001b[0m \u001b[31m10.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m \u001b[36m0:00:01\u001b[0m\n\u001b[?25hInstalling collected packages: trimesh\nSuccessfully installed trimesh-4.4.9\n","output_type":"stream"}]},{"cell_type":"code","source":"logging.basicConfig(level=logging.INFO)\n\nclass Pix3DJSONDataset(Dataset):\n    def __init__(self, base_dir, json_file, transform=None):\n        self.base_dir = base_dir\n        self.transform = transform\n        self.data = self.load_json(json_file)\n\n    def load_json(self, json_file):\n        with open(json_file, 'r') as f:\n            data = json.load(f)\n        logging.info(f\"Loaded {len(data)} samples from JSON file\")\n        return data\n\n    def __len__(self):\n        return len(self.data)\n\n    def __getitem__(self, idx):\n        item = self.data[idx]\n        \n        # Load image\n        img_path = os.path.join(self.base_dir, item['img'])\n        image = self.load_image(img_path)\n        \n        # Load 3D model (as voxel)\n        voxel_path = os.path.join(self.base_dir, item['voxel'])\n        voxel = self.load_voxel(voxel_path)\n        \n        # Get category\n        category = item['category']\n        \n        # Apply transforms\n        if self.transform:\n            image = self.transform(image)\n        \n        voxel = torch.from_numpy(voxel).float()\n\n        return image, voxel, category\n\n    def load_image(self, path):\n        try:\n            with Image.open(path) as img:\n                return img.convert('RGB')\n        except Exception as e:\n            logging.error(f\"Error loading image {path}: {str(e)}\")\n            raise\n\n    def load_voxel(self, path):\n        try:\n            voxel_data = scipy.io.loadmat(path)\n            voxel = voxel_data['voxel'].astype(np.float32)\n            return voxel\n        except Exception as e:\n            logging.error(f\"Error loading voxel {path}: {str(e)}\")\n            raise\n\n","metadata":{"execution":{"iopub.status.busy":"2024-10-10T03:11:57.488942Z","iopub.execute_input":"2024-10-10T03:11:57.489642Z","iopub.status.idle":"2024-10-10T03:11:57.502144Z","shell.execute_reply.started":"2024-10-10T03:11:57.489603Z","shell.execute_reply":"2024-10-10T03:11:57.501249Z"},"trusted":true},"execution_count":6,"outputs":[]},{"cell_type":"code","source":"# Define transforms\ntransform = transforms.Compose([\n#         transforms.Grayscale(),\n    transforms.Resize((128,128)),\n    transforms.ToTensor(),\n    transforms.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5))\n])","metadata":{"execution":{"iopub.status.busy":"2024-10-10T03:11:57.503421Z","iopub.execute_input":"2024-10-10T03:11:57.503746Z","iopub.status.idle":"2024-10-10T03:11:57.525256Z","shell.execute_reply.started":"2024-10-10T03:11:57.503712Z","shell.execute_reply":"2024-10-10T03:11:57.524236Z"},"trusted":true},"execution_count":7,"outputs":[]},{"cell_type":"code","source":"base_dir = '/kaggle/input/pix3d-dataset'\njson_file = '/kaggle/input/pix3d-dataset/pix3d.json'  # Adjust this path as needed\ndataset = Pix3DJSONDataset(base_dir, json_file, transform=transform)\ndataloader = DataLoader(dataset, batch_size=1, shuffle=True, num_workers=4)","metadata":{"execution":{"iopub.status.busy":"2024-10-10T03:11:57.528269Z","iopub.execute_input":"2024-10-10T03:11:57.528644Z","iopub.status.idle":"2024-10-10T03:11:59.389719Z","shell.execute_reply.started":"2024-10-10T03:11:57.528606Z","shell.execute_reply":"2024-10-10T03:11:59.388728Z"},"trusted":true},"execution_count":8,"outputs":[]},{"cell_type":"code","source":"# Print some information about the dataset\nprint(f\"Dataset size: {len(dataset)}\")\nprint(f\"Number of batches: {len(dataloader)}\")\n\n# Try to get the first batch\nfirst_batch = next(iter(dataloader))\nprint(f\"First batch shapes:\")\nprint(f\"  Images: {first_batch[0].shape}\")\nprint(f\"  Voxels: {first_batch[1].shape}\")\nprint(f\"First batch categories: {first_batch[2]}\")\n","metadata":{"execution":{"iopub.status.busy":"2024-10-10T03:11:59.391139Z","iopub.execute_input":"2024-10-10T03:11:59.391471Z","iopub.status.idle":"2024-10-10T03:11:59.936375Z","shell.execute_reply.started":"2024-10-10T03:11:59.391436Z","shell.execute_reply":"2024-10-10T03:11:59.935187Z"},"trusted":true},"execution_count":9,"outputs":[{"name":"stdout","text":"Dataset size: 10069\nNumber of batches: 10069\nFirst batch shapes:\n  Images: torch.Size([1, 3, 128, 128])\n  Voxels: torch.Size([1, 128, 128, 128])\nFirst batch categories: ('chair',)\n","output_type":"stream"}]},{"cell_type":"code","source":"def show_tensor_images(image_tensor, num_images=25, size=(3, 64, 64)):\n    image_tensor = (image_tensor + 1) / 2\n    image_unflat = image_tensor.detach().cpu()\n    image_grid = make_grid(image_unflat[:num_images], nrow=5)\n    plt.imshow(image_grid.permute(1, 2, 0).squeeze())\n    plt.show()","metadata":{"execution":{"iopub.status.busy":"2024-10-10T03:11:59.938361Z","iopub.execute_input":"2024-10-10T03:11:59.938825Z","iopub.status.idle":"2024-10-10T03:11:59.945732Z","shell.execute_reply.started":"2024-10-10T03:11:59.938773Z","shell.execute_reply":"2024-10-10T03:11:59.944710Z"},"trusted":true},"execution_count":10,"outputs":[]},{"cell_type":"code","source":"def downsample_volume(volume, scale_factor=0.5):\n    downsampled = F.interpolate(volume, scale_factor=scale_factor, mode='nearest')\n    return downsampled.squeeze()","metadata":{"execution":{"iopub.status.busy":"2024-10-10T03:11:59.947114Z","iopub.execute_input":"2024-10-10T03:11:59.947428Z","iopub.status.idle":"2024-10-10T03:11:59.958162Z","shell.execute_reply.started":"2024-10-10T03:11:59.947395Z","shell.execute_reply":"2024-10-10T03:11:59.957243Z"},"trusted":true},"execution_count":11,"outputs":[]},{"cell_type":"code","source":"# Matplotlib visualization (faster, simplified)\ndef get_volume_views(volume, downsample=True, scale_factor=0.5):\n    if downsample:\n        volume = downsample_volume(volume, scale_factor)\n    volume = volume.squeeze().detach().numpy()\n    \n    fig = plt.figure()\n    ax = fig.add_subplot(111, projection='3d')\n    ax.voxels(volume, edgecolor='k')  # No edges for faster rendering\n    \n    # Save or display\n    plt.show()\n    plt.close()\n","metadata":{"execution":{"iopub.status.busy":"2024-10-10T03:11:59.960026Z","iopub.execute_input":"2024-10-10T03:11:59.960509Z","iopub.status.idle":"2024-10-10T03:11:59.969851Z","shell.execute_reply.started":"2024-10-10T03:11:59.960461Z","shell.execute_reply":"2024-10-10T03:11:59.968879Z"},"trusted":true},"execution_count":12,"outputs":[]},{"cell_type":"code","source":"for batch in dataloader:\n    print(batch[0].shape)\n    print(batch[1].shape)\n    break","metadata":{"execution":{"iopub.status.busy":"2024-10-10T03:11:59.971332Z","iopub.execute_input":"2024-10-10T03:11:59.971784Z","iopub.status.idle":"2024-10-10T03:12:00.234019Z","shell.execute_reply.started":"2024-10-10T03:11:59.971693Z","shell.execute_reply":"2024-10-10T03:12:00.232560Z"},"trusted":true},"execution_count":13,"outputs":[{"name":"stdout","text":"torch.Size([1, 3, 128, 128])\ntorch.Size([1, 128, 128, 128])\n","output_type":"stream"}]},{"cell_type":"code","source":"show_tensor_images(batch[0][0])","metadata":{},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"get_volume_views(batch[1][0], downsample=True, scale_factor=0.25)","metadata":{},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"class CNN_Block(nn.Module):\n    def __init__(self,in_channels,out_channels,stride=2,last=False):\n        super().__init__()\n        self.conv = nn.Sequential(\n                nn.Conv2d(in_channels, out_channels, 4, stride,1),\n                nn.BatchNorm2d(out_channels) if not last else nn.Identity(),\n                nn.LeakyReLU(0.2)\n            )\n    def forward(self, x):\n        return self.conv(x)","metadata":{"execution":{"iopub.status.busy":"2024-10-10T03:12:00.239096Z","iopub.execute_input":"2024-10-10T03:12:00.239577Z","iopub.status.idle":"2024-10-10T03:12:00.249027Z","shell.execute_reply.started":"2024-10-10T03:12:00.239523Z","shell.execute_reply":"2024-10-10T03:12:00.247848Z"},"trusted":true},"execution_count":14,"outputs":[]},{"cell_type":"code","source":"class Discriminator(nn.Module):\n    def __init__(self, in_channels=3, hidden_dim=32):\n        super().__init__()\n        self.d1=CNN_Block(in_channels+128,hidden_dim)\n        self.d2=CNN_Block(hidden_dim,hidden_dim*2)\n        self.d3=CNN_Block(hidden_dim*2,hidden_dim*4)\n        self.d4=CNN_Block(hidden_dim*4,hidden_dim*8)\n        self.d5=CNN_Block(hidden_dim*8,hidden_dim*8)\n        self.d6=CNN_Block(hidden_dim*8,hidden_dim*16)\n        self.d7=CNN_Block(hidden_dim*16,1,last=True)\n        \n    def forward(self,x,y):\n        x=torch.cat([x,y],dim=1)\n        x=self.d1(x)\n        x=self.d2(x)        \n        x=self.d3(x)        \n        x=self.d4(x)        \n        x=self.d5(x)\n        x=self.d6(x)\n        x=self.d7(x)\n        x=torch.squeeze(x)\n        return x","metadata":{"execution":{"iopub.status.busy":"2024-10-10T03:12:00.250674Z","iopub.execute_input":"2024-10-10T03:12:00.251345Z","iopub.status.idle":"2024-10-10T03:12:00.265956Z","shell.execute_reply.started":"2024-10-10T03:12:00.251307Z","shell.execute_reply":"2024-10-10T03:12:00.264944Z"},"trusted":true},"execution_count":15,"outputs":[]},{"cell_type":"code","source":"disc=Discriminator()","metadata":{"execution":{"iopub.status.busy":"2024-10-10T02:43:12.687239Z","iopub.execute_input":"2024-10-10T02:43:12.688287Z","iopub.status.idle":"2024-10-10T02:43:12.723611Z","shell.execute_reply.started":"2024-10-10T02:43:12.688230Z","shell.execute_reply":"2024-10-10T02:43:12.722668Z"},"trusted":true},"execution_count":95,"outputs":[]},{"cell_type":"code","source":"d3=batch[1].unsqueeze(1)","metadata":{"execution":{"iopub.status.busy":"2024-10-10T02:25:31.579745Z","iopub.execute_input":"2024-10-10T02:25:31.580200Z","iopub.status.idle":"2024-10-10T02:25:31.584910Z","shell.execute_reply.started":"2024-10-10T02:25:31.580155Z","shell.execute_reply":"2024-10-10T02:25:31.584067Z"},"trusted":true},"execution_count":36,"outputs":[]},{"cell_type":"code","source":"d2=batch[0].unsqueeze(-1)","metadata":{"execution":{"iopub.status.busy":"2024-10-10T02:25:31.832979Z","iopub.execute_input":"2024-10-10T02:25:31.833316Z","iopub.status.idle":"2024-10-10T02:25:31.839237Z","shell.execute_reply.started":"2024-10-10T02:25:31.833284Z","shell.execute_reply":"2024-10-10T02:25:31.838424Z"},"trusted":true},"execution_count":37,"outputs":[]},{"cell_type":"code","source":"d2=d2.repeat(1,1,1,1,128)","metadata":{"execution":{"iopub.status.busy":"2024-10-10T02:17:49.501943Z","iopub.execute_input":"2024-10-10T02:17:49.502862Z","iopub.status.idle":"2024-10-10T02:17:49.517375Z","shell.execute_reply.started":"2024-10-10T02:17:49.502817Z","shell.execute_reply":"2024-10-10T02:17:49.516388Z"},"trusted":true},"execution_count":28,"outputs":[]},{"cell_type":"code","source":"print(d2.shape)\nprint(d3.shape)","metadata":{"execution":{"iopub.status.busy":"2024-10-10T02:25:35.357200Z","iopub.execute_input":"2024-10-10T02:25:35.357584Z","iopub.status.idle":"2024-10-10T02:25:35.362317Z","shell.execute_reply.started":"2024-10-10T02:25:35.357549Z","shell.execute_reply":"2024-10-10T02:25:35.361391Z"},"trusted":true},"execution_count":38,"outputs":[{"name":"stdout","text":"torch.Size([1, 3, 128, 128, 1])\ntorch.Size([1, 1, 128, 128, 128])\n","output_type":"stream"}]},{"cell_type":"code","source":"combined_input = torch.cat((d2, d3), dim=1)","metadata":{"execution":{"iopub.status.busy":"2024-10-10T02:17:55.939987Z","iopub.execute_input":"2024-10-10T02:17:55.941003Z","iopub.status.idle":"2024-10-10T02:17:55.962634Z","shell.execute_reply.started":"2024-10-10T02:17:55.940943Z","shell.execute_reply":"2024-10-10T02:17:55.961572Z"},"trusted":true},"execution_count":30,"outputs":[]},{"cell_type":"code","source":"d2[0][0].shape","metadata":{"execution":{"iopub.status.busy":"2024-10-10T02:19:48.773175Z","iopub.execute_input":"2024-10-10T02:19:48.774053Z","iopub.status.idle":"2024-10-10T02:19:48.779914Z","shell.execute_reply.started":"2024-10-10T02:19:48.773997Z","shell.execute_reply":"2024-10-10T02:19:48.778987Z"},"trusted":true},"execution_count":34,"outputs":[{"execution_count":34,"output_type":"execute_result","data":{"text/plain":"torch.Size([128, 128, 128])"},"metadata":{}}]},{"cell_type":"code","source":"disc(batch[0],batch[1]).item()","metadata":{"execution":{"iopub.status.busy":"2024-10-10T02:43:27.644454Z","iopub.execute_input":"2024-10-10T02:43:27.644843Z","iopub.status.idle":"2024-10-10T02:43:27.670849Z","shell.execute_reply.started":"2024-10-10T02:43:27.644805Z","shell.execute_reply":"2024-10-10T02:43:27.669849Z"},"trusted":true},"execution_count":97,"outputs":[{"execution_count":97,"output_type":"execute_result","data":{"text/plain":"-0.03868498280644417"},"metadata":{}}]},{"cell_type":"code","source":"get_volume_views(d2[0][0])","metadata":{"execution":{"iopub.status.busy":"2024-10-10T02:19:56.461939Z","iopub.execute_input":"2024-10-10T02:19:56.462349Z","iopub.status.idle":"2024-10-10T02:22:47.954691Z","shell.execute_reply.started":"2024-10-10T02:19:56.462312Z","shell.execute_reply":"2024-10-10T02:22:47.953744Z"},"trusted":true},"execution_count":35,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 640x480 with 1 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"},"metadata":{}}]},{"cell_type":"code","source":"class Block(nn.Module):\n    def __init__(self,in_channels,out_channels,down=True,act='relu',drop=False,norm=True):\n        super().__init__()\n        self.drop=drop\n        self.norm=norm\n        self.dropout=nn.Dropout(0.5)\n        if self.norm==True:\n            self.block=nn.Sequential(\n                nn.Conv2d(in_channels,out_channels,4,2,1) if down else nn.ConvTranspose3d(in_channels,out_channels,4,2,1),\n                nn.BatchNorm2d(out_channels) if down else nn.BatchNorm3d(out_channels),\n                nn.ReLU() if act=='relu' else nn.LeakyReLU(0.2),\n            )\n        else:\n            self.block=nn.Sequential(\n                nn.Conv2d(in_channels,out_channels,4,2,1) if down else nn.ConvTranspose3d(in_channels,out_channels,4,2,1),\n                nn.ReLU() if act=='relu' else nn.LeakyReLU(0.2),\n            )\n            \n    def forward(self,x):\n        x=self.block(x)\n        return self.dropout(x) if self.drop else x","metadata":{"execution":{"iopub.status.busy":"2024-10-10T03:12:00.267713Z","iopub.execute_input":"2024-10-10T03:12:00.268115Z","iopub.status.idle":"2024-10-10T03:12:00.278142Z","shell.execute_reply.started":"2024-10-10T03:12:00.268073Z","shell.execute_reply":"2024-10-10T03:12:00.277028Z"},"trusted":true},"execution_count":16,"outputs":[]},{"cell_type":"code","source":"class Generator(nn.Module):\n    def __init__(self,hidden_dim=32,in_channels=3):\n        super(Generator,self).__init__() \n        self.down1=Block(in_channels,hidden_dim,down=True,act='leaky',drop=False)\n        self.down2=Block(hidden_dim,hidden_dim*2,down=True,act='leaky',drop=False)\n        self.down3=Block(hidden_dim*2,hidden_dim*4,down=True,act='leaky',drop=False)        \n        self.down4=Block(hidden_dim*4,hidden_dim*8,down=True,act='leaky',drop=False)        \n        self.down5=Block(hidden_dim*8,hidden_dim*8,down=True,act='leaky',drop=False)\n        self.down6=Block(hidden_dim*8,hidden_dim*8,down=True,act='leaky',drop=False)\n        self.down7=Block(hidden_dim*8,hidden_dim*8,down=True,act='leaky',drop=False,norm=False)\n \n        self.bottleneck=nn.Sequential(\n            nn.Conv3d(hidden_dim*8,hidden_dim*8,3,2,1),\n            nn.ReLU()\n        )\n        \n        self.up1=Block(hidden_dim*8*2,hidden_dim*8,down=False,act='relu',drop=True)\n        self.up2=Block(hidden_dim*8*2,hidden_dim*8,down=False,act='relu',drop=True)\n        self.up3=Block(hidden_dim*8*2,hidden_dim*8,down=False,act='relu',drop=True)\n        self.up4=Block(hidden_dim*8*2,hidden_dim*4,down=False,act='relu',drop=True)\n        self.up5=Block(hidden_dim*4*2,hidden_dim*2,down=False,act='relu',drop=True)\n        self.up6=Block(hidden_dim*2*2,hidden_dim,down=False,act='relu',drop=True)\n        self.up7=Block(hidden_dim*2,1,down=False,act='relu',drop=True)\n        \n        self.final_up=nn.Sequential(\n            nn.ConvTranspose3d(hidden_dim*2,in_channels,4,2,1),\n            nn.Tanh()\n        )\n        \n    def forward(self,x):\n        d1=self.down1(x)\n#         print(\"down1: \",d1.shape) #[BATCH_SIZE,32,64,64]\n        d2=self.down2(d1)\n#         print(\"down2: \",d2.shape) #[BATCH_SIZE,64,32,32]\n        d3=self.down3(d2)\n#         print(\"down3: \",d3.shape) #[BATCH_SIZE,128,16,16]\n        d4=self.down4(d3)\n#         print(\"down4: \",d4.shape) #[BATCH_SIZE,256,8,8]\n        d5=self.down5(d4)\n#         print(\"down5: \",d5.shape) #[BATCH_SIZE,256,4,4]\n        d6=self.down6(d5)\n#         print(\"down6: \",d6.shape) #[BATCH_SIZE,256,2,2]\n        d7=self.down7(d6)\n#         print(\"down7: \",d7.shape) #[BATCH_SIZE,256,1,1]\n        \n\n        d7_resh=d7.view(-1,256,1,1,1)\n#         print(\"down7 reshaped: \",d7_resh.shape) #[BATCH_SIZE,256,1,1,1]\n#         print(\"=\"*50)\n\n        bottleneck=self.bottleneck(d7_resh)\n#         print(\"bottleneck: \",bottleneck.shape) #[BATCH_SIZE, 256, 1, 1, 1]\n        \n#         print(\"=\"*50)\n        \n        up1=self.up1(torch.cat([bottleneck,d7_resh],dim=1))\n#         print(\"up1: \",up1.shape) #[BATCH_SIZE, 256, 2, 2, 2]\n        \n        d6_resh=d6.view(-1,256,2,2,1).repeat(1,1,1,1,2)\n        up2=self.up2(torch.cat([up1,d6_resh],dim=1))\n#         print(\"up2: \",up2.shape) #[BATCH_SIZE, 256, 4, 4, 4]\n        d5_resh=d5.view(-1,256,4,4,1).repeat(1,1,1,1,4)\n        up3=self.up3(torch.cat([up2,d5_resh],dim=1))\n#         print(\"up3: \",up3.shape) #[BATCH_SIZE, 256, 8, 8, 8]\n        d4_resh=d4.view(-1,256,8,8,1).repeat(1,1,1,1,8)\n        up4=self.up4(torch.cat([up3,d4_resh],dim=1))\n#         print(\"up4: \",up4.shape) #[BATCH_SIZE, 128, 16, 16, 16]\n        d3_resh=d3.view(-1,128,16,16,1).repeat(1,1,1,1,16)\n        up5=self.up5(torch.cat([up4,d3_resh],dim=1))\n#         print(\"up5: \",up5.shape) #[BATCH_SIZE, 64, 32, 32, 32]\n        d2_resh=d2.view(-1,64,32,32,1).repeat(1,1,1,1,32)\n        up6=self.up6(torch.cat([up5,d2_resh],dim=1))\n#         print(\"up6: \",up6.shape) #[BATCH_SIZE, 32, 64, 64,64]\n        d1_resh=d1.view(-1,32,64,64,1).repeat(1,1,1,1,64)\n        up7=self.up7(torch.cat([up6,d1_resh],dim=1))\n#         print(\"up7: \",up7.shape) #[BATCH_SIZE, 1, 128,128, 128]\n        \n        return up7.squeeze(0)\n#         return up7","metadata":{"execution":{"iopub.status.busy":"2024-10-10T03:12:00.280063Z","iopub.execute_input":"2024-10-10T03:12:00.280455Z","iopub.status.idle":"2024-10-10T03:12:00.304322Z","shell.execute_reply.started":"2024-10-10T03:12:00.280413Z","shell.execute_reply":"2024-10-10T03:12:00.303320Z"},"trusted":true},"execution_count":17,"outputs":[]},{"cell_type":"code","source":"gen=Generator()","metadata":{"execution":{"iopub.status.busy":"2024-10-10T02:27:12.617194Z","iopub.execute_input":"2024-10-10T02:27:12.617582Z","iopub.status.idle":"2024-10-10T02:27:12.917793Z","shell.execute_reply.started":"2024-10-10T02:27:12.617546Z","shell.execute_reply":"2024-10-10T02:27:12.916994Z"},"trusted":true},"execution_count":41,"outputs":[]},{"cell_type":"code","source":"gen(batch[0]).shape","metadata":{"execution":{"iopub.status.busy":"2024-10-10T02:27:30.063850Z","iopub.execute_input":"2024-10-10T02:27:30.064619Z","iopub.status.idle":"2024-10-10T02:27:30.886861Z","shell.execute_reply.started":"2024-10-10T02:27:30.064576Z","shell.execute_reply":"2024-10-10T02:27:30.885902Z"},"trusted":true},"execution_count":43,"outputs":[{"execution_count":43,"output_type":"execute_result","data":{"text/plain":"torch.Size([1, 128, 128, 128])"},"metadata":{}}]},{"cell_type":"code","source":"class net_D(torch.nn.Module):\n    def __init__(self):\n        super(net_D, self).__init__()\n#         self.args = args\n        self.cube_len = 128\n        self.leak_value = 0.2\n        self.bias = False\n\n        padd = (0,0,0)\n        if self.cube_len == 32:\n            padd = (1,1,1)\n\n        self.f_dim = 32\n\n        self.layer1 = self.conv_layer(1, self.f_dim, kernel_size=4, stride=2, padding=(1,1,1), bias=self.bias)\n        self.layer2 = self.conv_layer(self.f_dim, self.f_dim*2, kernel_size=4, stride=2, padding=(1,1,1), bias=self.bias)\n        self.layer3 = self.conv_layer(self.f_dim*2, self.f_dim*4, kernel_size=4, stride=2, padding=(1,1,1), bias=self.bias)\n        self.layer4 = self.conv_layer(self.f_dim*4, self.f_dim*8, kernel_size=4, stride=2, padding=(1,1,1), bias=self.bias)\n        self.layer5=self.conv_layer(self.f_dim*8, self.f_dim*8, kernel_size=4, stride=2, padding=(1,1,1), bias=self.bias)\n        self.layer6=self.conv_layer(self.f_dim*8, self.f_dim*8, kernel_size=3, stride=2, padding=(1,1,1), bias=self.bias)\n#         self.layer8=self.conv_layer(self.f_dim*8, 1, kernel_size=4, stride=2, padding=(1,1,1), bias=self.bias)\n\n\n        self.layer7 = torch.nn.Sequential(\n            torch.nn.Conv3d(self.f_dim*8, 1, kernel_size=2, stride=2, bias=self.bias, padding=padd),\n#             torch.nn.Sigmoid()\n        )\n\n    def conv_layer(self, input_dim, output_dim, kernel_size=4, stride=2, padding=(1,1,1), bias=False):\n        layer = torch.nn.Sequential(\n            torch.nn.Conv3d(input_dim, output_dim, kernel_size=kernel_size, stride=stride, bias=bias, padding=padding),\n            torch.nn.BatchNorm3d(output_dim),\n            torch.nn.LeakyReLU(self.leak_value, inplace=True)\n        )\n        return layer\n\n    def forward(self, x):\n        # out = torch.unsqueeze(x, dim=1)\n        out = x.view(-1, 1, self.cube_len, self.cube_len, self.cube_len)\n        # print(out.size()) # torch.Size([32, 1, 32, 32, 32])\n        out = self.layer1(out)\n        # print(out.size())  # torch.Size([32, 32, 16, 16, 16])\n        out = self.layer2(out)\n        # print(out.size())  # torch.Size([32, 64, 8, 8, 8])\n        out = self.layer3(out)\n        # print(out.size())  # torch.Size([32, 128, 4, 4, 4])\n        out = self.layer4(out)\n        # print(out.size())  # torch.Size([32, 256, 2, 2, 2])\n        # out = out.view(-1, 256*2*2*2)\n        # print (out.size())\n        out=self.layer5(out)\n#         print(out.shape)\n        out=self.layer6(out)\n#         print(out.shape)\n        out = self.layer7(out)\n#         print(out.size())  # torch.Size([32, 1, 1, 1, 1])\n        out = torch.squeeze(out)\n        return out","metadata":{"execution":{"iopub.status.busy":"2024-10-10T03:17:02.044601Z","iopub.execute_input":"2024-10-10T03:17:02.045502Z","iopub.status.idle":"2024-10-10T03:17:02.067061Z","shell.execute_reply.started":"2024-10-10T03:17:02.045461Z","shell.execute_reply":"2024-10-10T03:17:02.065942Z"},"trusted":true},"execution_count":32,"outputs":[]},{"cell_type":"code","source":"disc2=net_D()","metadata":{"execution":{"iopub.status.busy":"2024-10-10T03:12:00.325817Z","iopub.execute_input":"2024-10-10T03:12:00.328826Z","iopub.status.idle":"2024-10-10T03:12:00.438047Z","shell.execute_reply.started":"2024-10-10T03:12:00.328784Z","shell.execute_reply":"2024-10-10T03:12:00.437086Z"},"trusted":true},"execution_count":19,"outputs":[]},{"cell_type":"code","source":"disc2(batch[1])","metadata":{"execution":{"iopub.status.busy":"2024-10-10T02:47:50.306308Z","iopub.execute_input":"2024-10-10T02:47:50.307153Z","iopub.status.idle":"2024-10-10T02:47:50.482463Z","shell.execute_reply.started":"2024-10-10T02:47:50.307111Z","shell.execute_reply":"2024-10-10T02:47:50.481502Z"},"trusted":true},"execution_count":114,"outputs":[{"name":"stdout","text":"torch.Size([1, 256, 4, 4, 4])\ntorch.Size([1, 256, 2, 2, 2])\ntorch.Size([1, 1, 1, 1, 1])\n","output_type":"stream"},{"execution_count":114,"output_type":"execute_result","data":{"text/plain":"tensor(-0.2084, grad_fn=<SqueezeBackward0>)"},"metadata":{}}]},{"cell_type":"code","source":"def weights_init(m):\n    if isinstance(m, nn.Conv2d) or isinstance(m, nn.ConvTranspose2d) or isinstance(m, nn.Conv3d) or isinstance(m, nn.ConvTranspose3d):\n        torch.nn.init.normal_(m.weight, 0.0, 0.02)\n    if isinstance(m, nn.BatchNorm2d) or isinstance(m, nn.BatchNorm3d):\n        torch.nn.init.normal_(m.weight, 0.0, 0.02)\n        torch.nn.init.constant_(m.bias, 0)","metadata":{"execution":{"iopub.status.busy":"2024-10-10T03:18:41.871411Z","iopub.execute_input":"2024-10-10T03:18:41.872416Z","iopub.status.idle":"2024-10-10T03:18:41.879078Z","shell.execute_reply.started":"2024-10-10T03:18:41.872375Z","shell.execute_reply":"2024-10-10T03:18:41.877821Z"},"trusted":true},"execution_count":34,"outputs":[]},{"cell_type":"code","source":"gen=Generator().cuda()\ndisc=Discriminator().cuda()\ndisc2=net_D().cuda()","metadata":{"execution":{"iopub.status.busy":"2024-10-10T03:18:42.056354Z","iopub.execute_input":"2024-10-10T03:18:42.056783Z","iopub.status.idle":"2024-10-10T03:18:42.488481Z","shell.execute_reply.started":"2024-10-10T03:18:42.056744Z","shell.execute_reply":"2024-10-10T03:18:42.487596Z"},"trusted":true},"execution_count":35,"outputs":[]},{"cell_type":"code","source":"gen = gen.apply(weights_init)\ndisc = disc.apply(weights_init)\ndisc2=disc2.apply(weights_init)","metadata":{"execution":{"iopub.status.busy":"2024-10-10T03:18:42.490136Z","iopub.execute_input":"2024-10-10T03:18:42.490468Z","iopub.status.idle":"2024-10-10T03:18:42.499799Z","shell.execute_reply.started":"2024-10-10T03:18:42.490433Z","shell.execute_reply":"2024-10-10T03:18:42.498927Z"},"trusted":true},"execution_count":36,"outputs":[]},{"cell_type":"code","source":"LR=0.0002\nBETAS=(0.5,0.999)\nLAMBDA=100\nEPOCHS=10","metadata":{"execution":{"iopub.status.busy":"2024-10-10T03:18:45.256915Z","iopub.execute_input":"2024-10-10T03:18:45.257356Z","iopub.status.idle":"2024-10-10T03:18:45.262371Z","shell.execute_reply.started":"2024-10-10T03:18:45.257316Z","shell.execute_reply":"2024-10-10T03:18:45.261346Z"},"trusted":true},"execution_count":37,"outputs":[]},{"cell_type":"code","source":"gen_opt=torch.optim.Adam(gen.parameters(),lr=LR,betas=BETAS)\ndisc_opt=torch.optim.Adam(disc.parameters(),lr=LR,betas=BETAS)\ndisc2_opt=torch.optim.Adam(disc2.parameters(),lr=LR,betas=BETAS)","metadata":{"execution":{"iopub.status.busy":"2024-10-10T03:18:45.533682Z","iopub.execute_input":"2024-10-10T03:18:45.534100Z","iopub.status.idle":"2024-10-10T03:18:45.542411Z","shell.execute_reply.started":"2024-10-10T03:18:45.534059Z","shell.execute_reply":"2024-10-10T03:18:45.541399Z"},"trusted":true},"execution_count":38,"outputs":[]},{"cell_type":"code","source":"BCE_Loss=nn.BCEWithLogitsLoss()\nL1_Loss=nn.L1Loss()","metadata":{"execution":{"iopub.status.busy":"2024-10-10T03:18:46.938495Z","iopub.execute_input":"2024-10-10T03:18:46.939435Z","iopub.status.idle":"2024-10-10T03:18:46.944120Z","shell.execute_reply.started":"2024-10-10T03:18:46.939392Z","shell.execute_reply":"2024-10-10T03:18:46.942960Z"},"trusted":true},"execution_count":39,"outputs":[]},{"cell_type":"code","source":"get_volume_views(batch[1])","metadata":{"execution":{"iopub.status.busy":"2024-10-10T04:27:40.866123Z","iopub.execute_input":"2024-10-10T04:27:40.866559Z","iopub.status.idle":"2024-10-10T04:28:54.349330Z","shell.execute_reply.started":"2024-10-10T04:27:40.866516Z","shell.execute_reply":"2024-10-10T04:28:54.348172Z"},"trusted":true},"execution_count":48,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 640x480 with 1 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"},"metadata":{}}]},{"cell_type":"code","source":"gen=gen.cpu()\nget_volume_views(gen(batch[0]))","metadata":{"execution":{"iopub.status.busy":"2024-10-10T04:26:56.780895Z","iopub.execute_input":"2024-10-10T04:26:56.781331Z","iopub.status.idle":"2024-10-10T04:27:29.548917Z","shell.execute_reply.started":"2024-10-10T04:26:56.781290Z","shell.execute_reply":"2024-10-10T04:27:29.547689Z"},"trusted":true},"execution_count":47,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 640x480 with 1 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"},"metadata":{}}]},{"cell_type":"code","source":"gen=gen.cuda()","metadata":{"execution":{"iopub.status.busy":"2024-10-10T03:46:33.736578Z","iopub.execute_input":"2024-10-10T03:46:33.736997Z","iopub.status.idle":"2024-10-10T03:46:33.830647Z","shell.execute_reply.started":"2024-10-10T03:46:33.736957Z","shell.execute_reply":"2024-10-10T03:46:33.829804Z"},"trusted":true},"execution_count":45,"outputs":[]},{"cell_type":"code","source":"for epoch in range(10):\n    for batch in tqdm(dataloader):\n        image_2d=batch[0].cuda()\n        image_3d=batch[1].cuda()\n        fake_3d=gen(image_2d)\n#         ========Train Disc2\n#         D2_real=disc2(fake_3d)\n#         D2_loss=BCE_Loss(D2_real,torch.ones_like(D2_real))\n\n#         disc2.zero_grad()\n#         D2_loss.backward(retain_graph=True)\n#         disc2_opt.step()\n#         ========  \n#         ========Train Disc1\n        D1_real=disc(image_2d,image_3d)\n        D1_real_loss=BCE_Loss(D1_real,torch.ones_like(D1_real))\n        D1_fake=disc(image_2d,fake_3d)\n        D1_fake_loss=BCE_Loss(D1_fake,torch.zeros_like(D1_fake))\n        D1_loss=(D1_real_loss+D1_fake_loss)/2\n        disc.zero_grad()\n        D1_loss.backward(retain_graph=True)\n        disc_opt.step()\n#         ======== \n#         ========Train Gen\n        D1_fake=disc(image_2d,fake_3d)\n        G_fake_loss1=BCE_Loss(D1_fake,torch.ones_like(D1_fake))\n#         G_fake_loss2=BCE_Loss(D2_real)\n        L1=L1_Loss(fake_3d,image_3d)*LAMBDA\n        G_loss=G_fake_loss1+L1\n        gen.zero_grad()\n        G_loss.backward()\n        gen_opt.step()\n        ","metadata":{"execution":{"iopub.status.busy":"2024-10-10T03:46:34.582016Z","iopub.execute_input":"2024-10-10T03:46:34.582816Z","iopub.status.idle":"2024-10-10T04:26:51.573455Z","shell.execute_reply.started":"2024-10-10T03:46:34.582769Z","shell.execute_reply":"2024-10-10T04:26:51.571823Z"},"collapsed":true,"jupyter":{"outputs_hidden":true},"trusted":true},"execution_count":46,"outputs":[{"output_type":"display_data","data":{"text/plain":"  0%|          | 0/10069 [00:00<?, ?it/s]","application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"adc4cc4d6d7e4758afabbf3ee57e2de0"}},"metadata":{}},{"name":"stderr","text":"/opt/conda/lib/python3.10/site-packages/PIL/Image.py:1056: UserWarning: Palette images with Transparency expressed in bytes should be converted to RGBA images\n  warnings.warn(\n/opt/conda/lib/python3.10/site-packages/PIL/Image.py:1056: UserWarning: Palette images with Transparency expressed in bytes should be converted to RGBA images\n  warnings.warn(\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"  0%|          | 0/10069 [00:00<?, ?it/s]","application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"2006741053bf46f28a5fa1526001c766"}},"metadata":{}},{"name":"stderr","text":"/opt/conda/lib/python3.10/site-packages/PIL/Image.py:1056: UserWarning: Palette images with Transparency expressed in bytes should be converted to RGBA images\n  warnings.warn(\n/opt/conda/lib/python3.10/site-packages/PIL/Image.py:1056: UserWarning: Palette images with Transparency expressed in bytes should be converted to RGBA images\n  warnings.warn(\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"  0%|          | 0/10069 [00:00<?, ?it/s]","application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"ef06390ac7be4dfe888f39f075b204ea"}},"metadata":{}},{"traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)","Cell \u001b[0;32mIn[46], line 3\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m epoch \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mrange\u001b[39m(\u001b[38;5;241m10\u001b[39m):\n\u001b[1;32m      2\u001b[0m     \u001b[38;5;28;01mfor\u001b[39;00m batch \u001b[38;5;129;01min\u001b[39;00m tqdm(dataloader):\n\u001b[0;32m----> 3\u001b[0m         image_2d\u001b[38;5;241m=\u001b[39m\u001b[43mbatch\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m]\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcuda\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m      4\u001b[0m         image_3d\u001b[38;5;241m=\u001b[39mbatch[\u001b[38;5;241m1\u001b[39m]\u001b[38;5;241m.\u001b[39mcuda()\n\u001b[1;32m      5\u001b[0m         fake_3d\u001b[38;5;241m=\u001b[39mgen(image_2d)\n","\u001b[0;31mKeyboardInterrupt\u001b[0m: "],"ename":"KeyboardInterrupt","evalue":"","output_type":"error"}]},{"cell_type":"code","source":"gen_PATH='/kaggle/working/gen_3'\ndisc_PATH='/kaggle/working/disc_3'\ntorch.save(disc.state_dict(), disc_PATH)\ntorch.save(gen.state_dict(), gen_PATH)","metadata":{"execution":{"iopub.status.busy":"2024-10-10T04:29:54.268307Z","iopub.execute_input":"2024-10-10T04:29:54.269019Z","iopub.status.idle":"2024-10-10T04:29:54.510433Z","shell.execute_reply.started":"2024-10-10T04:29:54.268978Z","shell.execute_reply":"2024-10-10T04:29:54.509011Z"},"trusted":true},"execution_count":50,"outputs":[]},{"cell_type":"code","source":"","metadata":{},"execution_count":null,"outputs":[]}]}