{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"name":"python","version":"3.11.13","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"},"kaggle":{"accelerator":"nvidiaTeslaT4","dataSources":[{"sourceId":112899,"databundleVersionId":13449579,"sourceType":"competition"}],"dockerImageVersionId":31090,"isInternetEnabled":true,"language":"python","sourceType":"notebook","isGpuEnabled":true}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"code","source":"import pandas as pd\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport seaborn as sns\n\n# Load the CSV\ndf = pd.read_csv('/kaggle/input/grand-xray-slam-division-a/train1.csv')\n\n# Basic overview\nprint(df.head())  # First few rows\nprint(df.info())  # Column types and non-null counts\nprint(df.describe())  # Stats for numerical columns like Age\n\n# Check for missing values (e.g., in Sex and Age)\nprint(df.isnull().sum())  # NaNs per column","metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true,"execution":{"iopub.status.busy":"2025-08-26T11:18:12.616233Z","iopub.execute_input":"2025-08-26T11:18:12.616417Z","iopub.status.idle":"2025-08-26T11:18:16.391949Z","shell.execute_reply.started":"2025-08-26T11:18:12.616401Z","shell.execute_reply":"2025-08-26T11:18:16.391073Z"}},"outputs":[{"name":"stdout","text":"             Image_name  Patient_ID  Study     Sex   Age ViewCategory  \\\n0  00000001_001_001.jpg           1      1  Female  68.0      Frontal   \n1  00000009_001_001.jpg           9      1    Male  76.0      Frontal   \n2  00000009_001_002.jpg           9      1    Male  76.0      Lateral   \n3  00000011_013_001.jpg          11     13  Female  22.0      Frontal   \n4  00000011_013_002.jpg          11     13  Female  22.0      Lateral   \n\n  ViewPosition  Atelectasis  Cardiomegaly  Consolidation  ...  \\\n0           AP            0             0              0  ...   \n1           PA            0             1              0  ...   \n2      Lateral            0             1              0  ...   \n3           PA            0             0              0  ...   \n4      Lateral            0             0              0  ...   \n\n   Enlarged Cardiomediastinum  Fracture  Lung Lesion  Lung Opacity  \\\n0                           0         0            0             0   \n1                           1         0            0             0   \n2                           1         0            0             0   \n3                           0         0            0             0   \n4                           0         0            0             0   \n\n   No Finding  Pleural Effusion  Pleural Other  Pneumonia  Pneumothorax  \\\n0           0                 0              0          0             0   \n1           0                 0              0          0             0   \n2           0                 0              0          0             0   \n3           1                 0              0          0             0   \n4           1                 0              0          0             0   \n\n   Support Devices  \n0                1  \n1                0  \n2                0  \n3                0  \n4                0  \n\n[5 rows x 21 columns]\n<class 'pandas.core.frame.DataFrame'>\nRangeIndex: 107374 entries, 0 to 107373\nData columns (total 21 columns):\n #   Column                      Non-Null Count   Dtype  \n---  ------                      --------------   -----  \n 0   Image_name                  107374 non-null  object \n 1   Patient_ID                  107374 non-null  int64  \n 2   Study                       107374 non-null  int64  \n 3   Sex                         92608 non-null   object \n 4   Age                         92608 non-null   float64\n 5   ViewCategory                107374 non-null  object \n 6   ViewPosition                107374 non-null  object \n 7   Atelectasis                 107374 non-null  int64  \n 8   Cardiomegaly                107374 non-null  int64  \n 9   Consolidation               107374 non-null  int64  \n 10  Edema                       107374 non-null  int64  \n 11  Enlarged Cardiomediastinum  107374 non-null  int64  \n 12  Fracture                    107374 non-null  int64  \n 13  Lung Lesion                 107374 non-null  int64  \n 14  Lung Opacity                107374 non-null  int64  \n 15  No Finding                  107374 non-null  int64  \n 16  Pleural Effusion            107374 non-null  int64  \n 17  Pleural Other               107374 non-null  int64  \n 18  Pneumonia                   107374 non-null  int64  \n 19  Pneumothorax                107374 non-null  int64  \n 20  Support Devices             107374 non-null  int64  \ndtypes: float64(1), int64(16), object(4)\nmemory usage: 17.2+ MB\nNone\n         Patient_ID          Study           Age    Atelectasis  \\\ncount  1.073740e+05  107374.000000  92608.000000  107374.000000   \nmean   8.449938e+06       5.490277     54.969927       0.361670   \nstd    9.166637e+06       9.430560     18.762809       0.480486   \nmin    1.000000e+00       0.000000      0.000000       0.000000   \n25%    1.941100e+04       1.000000     42.000000       0.000000   \n50%    5.988250e+04       2.000000     56.000000       0.000000   \n75%    2.001374e+07       6.000000     68.000000       1.000000   \nmax    2.003080e+07     156.000000    110.000000       1.000000   \n\n        Cardiomegaly  Consolidation          Edema  \\\ncount  107374.000000  107374.000000  107374.000000   \nmean        0.325963       0.273660       0.248393   \nstd         0.468736       0.445839       0.432083   \nmin         0.000000       0.000000       0.000000   \n25%         0.000000       0.000000       0.000000   \n50%         0.000000       0.000000       0.000000   \n75%         1.000000       1.000000       0.000000   \nmax         1.000000       1.000000       1.000000   \n\n       Enlarged Cardiomediastinum       Fracture    Lung Lesion  \\\ncount               107374.000000  107374.000000  107374.000000   \nmean                     0.352562       0.139550       0.110818   \nstd                      0.477770       0.346521       0.313908   \nmin                      0.000000       0.000000       0.000000   \n25%                      0.000000       0.000000       0.000000   \n50%                      0.000000       0.000000       0.000000   \n75%                      1.000000       0.000000       0.000000   \nmax                      1.000000       1.000000       1.000000   \n\n        Lung Opacity     No Finding  Pleural Effusion  Pleural Other  \\\ncount  107374.000000  107374.000000     107374.000000  107374.000000   \nmean        0.452866       0.316250          0.318904       0.065761   \nstd         0.497776       0.465014          0.466054       0.247865   \nmin         0.000000       0.000000          0.000000       0.000000   \n25%         0.000000       0.000000          0.000000       0.000000   \n50%         0.000000       0.000000          0.000000       0.000000   \n75%         1.000000       1.000000          1.000000       0.000000   \nmax         1.000000       1.000000          1.000000       1.000000   \n\n           Pneumonia   Pneumothorax  Support Devices  \ncount  107374.000000  107374.000000    107374.000000  \nmean        0.133915       0.082087         0.350746  \nstd         0.340563       0.274498         0.477206  \nmin         0.000000       0.000000         0.000000  \n25%         0.000000       0.000000         0.000000  \n50%         0.000000       0.000000         0.000000  \n75%         0.000000       0.000000         1.000000  \nmax         1.000000       1.000000         1.000000  \nImage_name                        0\nPatient_ID                        0\nStudy                             0\nSex                           14766\nAge                           14766\nViewCategory                      0\nViewPosition                      0\nAtelectasis                       0\nCardiomegaly                      0\nConsolidation                     0\nEdema                             0\nEnlarged Cardiomediastinum        0\nFracture                          0\nLung Lesion                       0\nLung Opacity                      0\nNo Finding                        0\nPleural Effusion                  0\nPleural Other                     0\nPneumonia                         0\nPneumothorax                      0\nSupport Devices                   0\ndtype: int64\n","output_type":"stream"}],"execution_count":1},{"cell_type":"code","source":"# List of condition columns\nconditions = [\n    'Atelectasis', 'Cardiomegaly', 'Consolidation', 'Edema',\n    'Enlarged Cardiomediastinum', 'Fracture', 'Lung Lesion', 'Lung Opacity',\n    'No Finding', 'Pleural Effusion', 'Pleural Other', 'Pneumonia',\n    'Pneumothorax', 'Support Devices'\n]\n\n# Count positives per condition\nlabel_counts = df[conditions].sum().sort_values(ascending=False)\nprint(label_counts)\n\n# Visualize label distribution\nplt.figure(figsize=(12, 6))\nsns.barplot(x=label_counts.index, y=label_counts.values)\nplt.xticks(rotation=45, ha='right')\nplt.title('Distribution of Thoracic Conditions (Positive Counts)')\nplt.ylabel('Number of Positive Labels')\nplt.show()\n\n# Check co-occurrences (correlation heatmap)\ncorr = df[conditions].corr()\nplt.figure(figsize=(10, 8))\nsns.heatmap(corr, annot=True, cmap='coolwarm', fmt='.2f')\nplt.title('Correlation Between Conditions')\nplt.show()","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-08-26T11:18:16.393617Z","iopub.execute_input":"2025-08-26T11:18:16.393852Z","iopub.status.idle":"2025-08-26T11:18:17.463731Z","shell.execute_reply.started":"2025-08-26T11:18:16.393815Z","shell.execute_reply":"2025-08-26T11:18:17.462864Z"}},"outputs":[{"name":"stdout","text":"Lung Opacity                  48626\nAtelectasis                   38834\nEnlarged Cardiomediastinum    37856\nSupport Devices               37661\nCardiomegaly                  35000\nPleural Effusion              34242\nNo Finding                    33957\nConsolidation                 29384\nEdema                         26671\nFracture                      14984\nPneumonia                     14379\nLung Lesion                   11899\nPneumothorax                   8814\nPleural Other                  7061\ndtype: int64\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"<Figure size 1200x600 with 1 Axes>","image/png":"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\n"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"<Figure size 1000x800 with 2 Axes>","image/png":"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\n"},"metadata":{}}],"execution_count":2},{"cell_type":"code","source":"import pandas as pd\nimport numpy as np\n\n# Load training data\ndf = pd.read_csv('/kaggle/input/grand-xray-slam-division-a/train1.csv')\n\n# Handle missing values\ndf['Sex'].fillna('Unknown', inplace=True)\ndf['Age'].fillna(df['Age'].median(), inplace=True)  # Median ~56\n\n# Encode categorical variables\ndf['Sex'] = df['Sex'].map({'Male': 0, 'Female': 1, 'Unknown': 2})\ndf['ViewCategory'] = df['ViewCategory'].map({'Frontal': 0, 'Lateral': 1})\ndf['ViewPosition'] = df['ViewPosition'].map({'AP': 0, 'PA': 1, 'Lateral': 2})\n\n# Add source column\ndf['Source'] = df['Patient_ID'].apply(\n    lambda x: 'CheXpert' if str(x).startswith('0') else 'MIMIC' if str(x).startswith('1') else 'NIH'\n)\n\n# Define condition columns\nconditions = [\n    'Atelectasis', 'Cardiomegaly', 'Consolidation', 'Edema',\n    'Enlarged Cardiomediastinum', 'Fracture', 'Lung Lesion', 'Lung Opacity',\n    'No Finding', 'Pleural Effusion', 'Pleural Other', 'Pneumonia',\n    'Pneumothorax', 'Support Devices'\n]\n\n# Save preprocessed data\ndf.to_csv('/kaggle/working/train1_preprocessed.csv', index=False)","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-08-26T11:18:17.464548Z","iopub.execute_input":"2025-08-26T11:18:17.464769Z","iopub.status.idle":"2025-08-26T11:18:18.331637Z","shell.execute_reply.started":"2025-08-26T11:18:17.464751Z","shell.execute_reply":"2025-08-26T11:18:18.331075Z"}},"outputs":[{"name":"stderr","text":"/tmp/ipykernel_36/1759433920.py:8: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.\nThe behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.\n\nFor example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.\n\n\n  df['Sex'].fillna('Unknown', inplace=True)\n/tmp/ipykernel_36/1759433920.py:9: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.\nThe behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.\n\nFor example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.\n\n\n  df['Age'].fillna(df['Age'].median(), inplace=True)  # Median ~56\n","output_type":"stream"}],"execution_count":3},{"cell_type":"code","source":"import torch","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-08-26T11:18:18.33231Z","iopub.execute_input":"2025-08-26T11:18:18.332596Z","iopub.status.idle":"2025-08-26T11:18:22.515992Z","shell.execute_reply.started":"2025-08-26T11:18:18.332573Z","shell.execute_reply":"2025-08-26T11:18:22.515461Z"}},"outputs":[],"execution_count":4},{"cell_type":"code","source":"!pip install torch --index-url https://download.pytorch.org/whl/cu118","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-08-26T11:18:22.516641Z","iopub.execute_input":"2025-08-26T11:18:22.517039Z","iopub.status.idle":"2025-08-26T11:20:46.746229Z","shell.execute_reply.started":"2025-08-26T11:18:22.51702Z","shell.execute_reply":"2025-08-26T11:20:46.74543Z"}},"outputs":[{"name":"stdout","text":"Looking in indexes: https://download.pytorch.org/whl/cu118\nRequirement already satisfied: torch in /usr/local/lib/python3.11/dist-packages (2.6.0+cu124)\nRequirement already satisfied: filelock in /usr/local/lib/python3.11/dist-packages (from torch) (3.18.0)\nRequirement already satisfied: typing-extensions>=4.10.0 in /usr/local/lib/python3.11/dist-packages (from torch) (4.14.0)\nRequirement already satisfied: networkx in /usr/local/lib/python3.11/dist-packages (from torch) (3.5)\nRequirement already satisfied: jinja2 in /usr/local/lib/python3.11/dist-packages (from torch) (3.1.6)\nRequirement already satisfied: fsspec in /usr/local/lib/python3.11/dist-packages (from torch) (2025.5.1)\nINFO: pip is looking at multiple versions of torch to determine which version is compatible with other requirements. This could take a while.\nCollecting torch\n  Downloading https://download.pytorch.org/whl/cu118/torch-2.7.1%2Bcu118-cp311-cp311-manylinux_2_28_x86_64.whl.metadata (28 kB)\nCollecting sympy>=1.13.3 (from torch)\n  Downloading https://download.pytorch.org/whl/sympy-1.13.3-py3-none-any.whl.metadata (12 kB)\nCollecting nvidia-cuda-nvrtc-cu11==11.8.89 (from torch)\n  Downloading https://download.pytorch.org/whl/cu118/nvidia_cuda_nvrtc_cu11-11.8.89-py3-none-manylinux1_x86_64.whl (23.2 MB)\n\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m23.2/23.2 MB\u001b[0m \u001b[31m71.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m00:01\u001b[0m00:01\u001b[0m\n\u001b[?25hCollecting nvidia-cuda-runtime-cu11==11.8.89 (from torch)\n  Downloading https://download.pytorch.org/whl/cu118/nvidia_cuda_runtime_cu11-11.8.89-py3-none-manylinux1_x86_64.whl (875 kB)\n\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m875.6/875.6 kB\u001b[0m \u001b[31m47.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n\u001b[?25hCollecting nvidia-cuda-cupti-cu11==11.8.87 (from torch)\n  Downloading https://download.pytorch.org/whl/cu118/nvidia_cuda_cupti_cu11-11.8.87-py3-none-manylinux1_x86_64.whl (13.1 MB)\n\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m13.1/13.1 MB\u001b[0m \u001b[31m88.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m00:01\u001b[0m00:01\u001b[0m\n\u001b[?25hCollecting nvidia-cudnn-cu11==9.1.0.70 (from torch)\n  Downloading https://download.pytorch.org/whl/cu118/nvidia_cudnn_cu11-9.1.0.70-py3-none-manylinux2014_x86_64.whl (663.9 MB)\n\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m663.9/663.9 MB\u001b[0m \u001b[31m2.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m00:01\u001b[0m00:01\u001b[0m\n\u001b[?25hCollecting nvidia-cublas-cu11==11.11.3.6 (from torch)\n  Downloading https://download.pytorch.org/whl/cu118/nvidia_cublas_cu11-11.11.3.6-py3-none-manylinux1_x86_64.whl (417.9 MB)\n\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m417.9/417.9 MB\u001b[0m \u001b[31m3.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m00:01\u001b[0m00:01\u001b[0m\n\u001b[?25hCollecting nvidia-cufft-cu11==10.9.0.58 (from torch)\n  Downloading https://download.pytorch.org/whl/cu118/nvidia_cufft_cu11-10.9.0.58-py3-none-manylinux1_x86_64.whl (168.4 MB)\n\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m168.4/168.4 MB\u001b[0m \u001b[31m10.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m00:01\u001b[0m00:01\u001b[0m\n\u001b[?25hCollecting nvidia-curand-cu11==10.3.0.86 (from torch)\n  Downloading https://download.pytorch.org/whl/cu118/nvidia_curand_cu11-10.3.0.86-py3-none-manylinux1_x86_64.whl (58.1 MB)\n\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m58.1/58.1 MB\u001b[0m \u001b[31m30.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m00:01\u001b[0m00:01\u001b[0m\n\u001b[?25hCollecting nvidia-cusolver-cu11==11.4.1.48 (from torch)\n  Downloading https://download.pytorch.org/whl/cu118/nvidia_cusolver_cu11-11.4.1.48-py3-none-manylinux1_x86_64.whl (128.2 MB)\n\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m128.2/128.2 MB\u001b[0m \u001b[31m13.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m00:01\u001b[0m00:01\u001b[0m\n\u001b[?25hCollecting nvidia-cusparse-cu11==11.7.5.86 (from torch)\n  Downloading https://download.pytorch.org/whl/cu118/nvidia_cusparse_cu11-11.7.5.86-py3-none-manylinux1_x86_64.whl (204.1 MB)\n\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m204.1/204.1 MB\u001b[0m \u001b[31m8.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m00:01\u001b[0m00:01\u001b[0m\n\u001b[?25hCollecting nvidia-nccl-cu11==2.21.5 (from torch)\n  Downloading https://download.pytorch.org/whl/cu118/nvidia_nccl_cu11-2.21.5-py3-none-manylinux2014_x86_64.whl (147.8 MB)\n\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m147.8/147.8 MB\u001b[0m \u001b[31m11.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m00:01\u001b[0m00:01\u001b[0m\n\u001b[?25hCollecting nvidia-nvtx-cu11==11.8.86 (from torch)\n  Downloading https://download.pytorch.org/whl/cu118/nvidia_nvtx_cu11-11.8.86-py3-none-manylinux1_x86_64.whl (99 kB)\n\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m99.1/99.1 kB\u001b[0m \u001b[31m9.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n\u001b[?25hCollecting triton==3.3.1 (from torch)\n  Downloading https://download.pytorch.org/whl/triton-3.3.1-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl.metadata (1.5 kB)\nRequirement already satisfied: setuptools>=40.8.0 in /usr/local/lib/python3.11/dist-packages (from triton==3.3.1->torch) (75.2.0)\nRequirement already satisfied: mpmath<1.4,>=1.1.0 in /usr/local/lib/python3.11/dist-packages (from sympy>=1.13.3->torch) (1.3.0)\nRequirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.11/dist-packages (from jinja2->torch) (3.0.2)\nDownloading https://download.pytorch.org/whl/cu118/torch-2.7.1%2Bcu118-cp311-cp311-manylinux_2_28_x86_64.whl (905.3 MB)\n\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m905.3/905.3 MB\u001b[0m \u001b[31m908.8 kB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m00:01\u001b[0m00:01\u001b[0m\n\u001b[?25hDownloading https://download.pytorch.org/whl/triton-3.3.1-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl (155.7 MB)\n\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m155.7/155.7 MB\u001b[0m \u001b[31m10.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m00:01\u001b[0m00:01\u001b[0m\n\u001b[?25hDownloading https://download.pytorch.org/whl/sympy-1.13.3-py3-none-any.whl (6.2 MB)\n\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m6.2/6.2 MB\u001b[0m \u001b[31m111.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m00:01\u001b[0m\n\u001b[?25hInstalling collected packages: triton, sympy, nvidia-nvtx-cu11, nvidia-nccl-cu11, nvidia-cusparse-cu11, nvidia-curand-cu11, nvidia-cufft-cu11, nvidia-cuda-runtime-cu11, nvidia-cuda-nvrtc-cu11, nvidia-cuda-cupti-cu11, nvidia-cublas-cu11, nvidia-cusolver-cu11, nvidia-cudnn-cu11, torch\n  Attempting uninstall: triton\n    Found existing installation: triton 3.2.0\n    Uninstalling triton-3.2.0:\n      Successfully uninstalled triton-3.2.0\n  Attempting uninstall: sympy\n    Found existing installation: sympy 1.13.1\n    Uninstalling sympy-1.13.1:\n      Successfully uninstalled sympy-1.13.1\n  Attempting uninstall: torch\n    Found existing installation: torch 2.6.0+cu124\n    Uninstalling torch-2.6.0+cu124:\n      Successfully uninstalled torch-2.6.0+cu124\n\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\ntorchaudio 2.6.0+cu124 requires torch==2.6.0, but you have torch 2.7.1+cu118 which is incompatible.\ntorchvision 0.21.0+cu124 requires torch==2.6.0, but you have torch 2.7.1+cu118 which is incompatible.\nfastai 2.7.19 requires torch<2.7,>=1.10, but you have torch 2.7.1+cu118 which is incompatible.\u001b[0m\u001b[31m\n\u001b[0mSuccessfully installed nvidia-cublas-cu11-11.11.3.6 nvidia-cuda-cupti-cu11-11.8.87 nvidia-cuda-nvrtc-cu11-11.8.89 nvidia-cuda-runtime-cu11-11.8.89 nvidia-cudnn-cu11-9.1.0.70 nvidia-cufft-cu11-10.9.0.58 nvidia-curand-cu11-10.3.0.86 nvidia-cusolver-cu11-11.4.1.48 nvidia-cusparse-cu11-11.7.5.86 nvidia-nccl-cu11-2.21.5 nvidia-nvtx-cu11-11.8.86 sympy-1.13.3 torch-2.7.1+cu118 triton-3.3.1\n","output_type":"stream"}],"execution_count":5},{"cell_type":"code","source":"!pip install --quiet torch==2.2.2 torchvision==0.17.2 torchaudio==2.2.2 --index-url https://download.pytorch.org/whl/cu118","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-08-26T11:27:11.691893Z","iopub.execute_input":"2025-08-26T11:27:11.692607Z","iopub.status.idle":"2025-08-26T11:28:34.582853Z","shell.execute_reply.started":"2025-08-26T11:27:11.692583Z","shell.execute_reply":"2025-08-26T11:28:34.581745Z"}},"outputs":[{"name":"stdout","text":"\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m819.2/819.2 MB\u001b[0m \u001b[31m2.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m00:01\u001b[0m00:01\u001b[0m\n\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m6.2/6.2 MB\u001b[0m \u001b[31m94.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0mta \u001b[36m0:00:01\u001b[0m\n\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m3.3/3.3 MB\u001b[0m \u001b[31m76.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m:00:01\u001b[0m\n\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m728.5/728.5 MB\u001b[0m \u001b[31m2.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m00:01\u001b[0m00:01\u001b[0m\n\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m135.3/135.3 MB\u001b[0m \u001b[31m7.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m00:01\u001b[0m00:01\u001b[0m\n\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m167.9/167.9 MB\u001b[0m \u001b[31m10.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m00:01\u001b[0m00:01\u001b[0m\n\u001b[?25h","output_type":"stream"}],"execution_count":13},{"cell_type":"code","source":"# Calculate class weights (inverse frequency)\nclass_counts = df[conditions].sum()\nclass_weights = 1.0 / class_counts\nclass_weights = class_weights / class_weights.sum() * len(conditions)  # Normalize\nclass_weights = torch.tensor(class_weights.values, dtype=torch.float32).to('cuda')\nprint(\"Class weights:\", dict(zip(conditions, class_weights)))","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-08-26T11:20:46.995501Z","iopub.execute_input":"2025-08-26T11:20:46.995749Z","iopub.status.idle":"2025-08-26T11:20:47.438356Z","shell.execute_reply.started":"2025-08-26T11:20:46.995725Z","shell.execute_reply":"2025-08-26T11:20:47.437569Z"}},"outputs":[{"name":"stdout","text":"Class weights: {'Atelectasis': tensor(0.4915, device='cuda:0'), 'Cardiomegaly': tensor(0.5454, device='cuda:0'), 'Consolidation': tensor(0.6496, device='cuda:0'), 'Edema': tensor(0.7157, device='cuda:0'), 'Enlarged Cardiomediastinum': tensor(0.5042, device='cuda:0'), 'Fracture': tensor(1.2739, device='cuda:0'), 'Lung Lesion': tensor(1.6042, device='cuda:0'), 'Lung Opacity': tensor(0.3926, device='cuda:0'), 'No Finding': tensor(0.5621, device='cuda:0'), 'Pleural Effusion': tensor(0.5574, device='cuda:0'), 'Pleural Other': tensor(2.7033, device='cuda:0'), 'Pneumonia': tensor(1.3275, device='cuda:0'), 'Pneumothorax': tensor(2.1657, device='cuda:0'), 'Support Devices': tensor(0.5068, device='cuda:0')}\n","output_type":"stream"}],"execution_count":7},{"cell_type":"code","source":"import torch\nfrom torch.utils.data import Dataset, DataLoader\nimport cv2\nfrom torchvision import transforms\nimport albumentations as A\nfrom albumentations.pytorch import ToTensorV2\n\nclass XRayDataset(Dataset):\n    def __init__(self, df, img_dir, transform=None):\n        self.df = df\n        self.img_dir = img_dir\n        self.transform = transform\n        self.labels = df[conditions].values.astype(np.float32)\n    \n    def __len__(self):\n        return len(self.df)\n    \n    def __getitem__(self, idx):\n        img_name = self.df['Image_name'].iloc[idx]\n        img_path = os.path.join(self.img_dir, img_name)\n        image = cv2.imread(img_path, cv2.IMREAD_GRAYSCALE)\n        if image is None:\n            raise FileNotFoundError(f\"Image not found: {img_path}\")\n        image = cv2.cvtColor(image, cv2.COLOR_GRAY2RGB)  # RGB for pre-trained models\n        \n        if self.transform:\n            augmented = self.transform(image=image)\n            image = augmented['image']\n        \n        label = torch.tensor(self.labels[idx])\n        return image, label\n\n# Define augmentations\ntrain_transform = A.Compose([\n    A.Resize(224, 224),\n    A.Rotate(limit=15, p=0.5),\n    A.HorizontalFlip(p=0.5),\n    A.RandomBrightnessContrast(p=0.3),\n    A.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]),\n    ToTensorV2()\n])\n\ntest_transform = A.Compose([\n    A.Resize(224, 224),\n    A.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]),\n    ToTensorV2()\n])\n\n# Create datasets\ntrain_dataset = XRayDataset(df, '/kaggle/input/grand-xray-slam-division-a/train1', transform=train_transform)","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-08-26T11:28:45.609276Z","iopub.execute_input":"2025-08-26T11:28:45.609956Z","iopub.status.idle":"2025-08-26T11:28:46.910271Z","shell.execute_reply.started":"2025-08-26T11:28:45.609923Z","shell.execute_reply":"2025-08-26T11:28:46.909654Z"}},"outputs":[],"execution_count":14},{"cell_type":"code","source":"from sklearn.model_selection import GroupKFold\n\n# Split train/validation (80/20) by Patient_ID\ngkf = GroupKFold(n_splits=5)\ntrain_idx, val_idx = next(gkf.split(df, groups=df['Patient_ID']))\ntrain_df = df.iloc[train_idx].reset_index(drop=True)\nval_df = df.iloc[val_idx].reset_index(drop=True)\n\n# Create datasets\ntrain_dataset = XRayDataset(train_df, '/kaggle/input/grand-xray-slam-division-a/train1', transform=train_transform)\nval_dataset = XRayDataset(val_df, '/kaggle/input/grand-xray-slam-division-a/train1', transform=test_transform)\n\n# DataLoaders\ntrain_loader = DataLoader(train_dataset, batch_size=32, shuffle=True, num_workers=4)\nval_loader = DataLoader(val_dataset, batch_size=32, shuffle=False, num_workers=4)","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-08-26T11:30:27.922396Z","iopub.execute_input":"2025-08-26T11:30:27.923239Z","iopub.status.idle":"2025-08-26T11:30:28.285717Z","shell.execute_reply.started":"2025-08-26T11:30:27.923214Z","shell.execute_reply":"2025-08-26T11:30:28.285124Z"}},"outputs":[],"execution_count":15},{"cell_type":"code","source":"from torchvision import models\nfrom torch import nn\nimport torch\nfrom sklearn.metrics import roc_auc_score\n\n# Model\nmodel = models.resnet50(pretrained=True)\nmodel.fc = nn.Sequential(\n    nn.Linear(model.fc.in_features, 14),  # 14 conditions\n    nn.Sigmoid()  # Multi-label\n)\n\n# Move to GPU\ndevice = torch.device('cuda' if torch.cuda.is_available() else 'cpu')\nmodel.to(device)\n\n# Loss and optimizer\ncriterion = nn.BCELoss(weight=class_weights)\noptimizer = torch.optim.Adam(model.parameters(), lr=0.001)\n\n# Training loop\nnum_epochs = 5  # Adjust based on resources\nfor epoch in range(num_epochs):\n    model.train()\n    train_loss = 0\n    for images, labels in train_loader:\n        images, labels = images.to(device), labels.to(device)\n        outputs = model(images)\n        loss = criterion(outputs, labels)\n        optimizer.zero_grad()\n        loss.backward()\n        optimizer.step()\n        train_loss += loss.item()\n    \n    # Validation\n    model.eval()\n    val_preds, val_labels = [], []\n    with torch.no_grad():\n        for images, labels in val_loader:\n            images, labels = images.to(device), labels.to(device)\n            outputs = model(images)\n            val_preds.append(outputs.cpu().numpy())\n            val_labels.append(labels.cpu().numpy())\n    \n    val_preds = np.vstack(val_preds)\n    val_labels = np.vstack(val_labels)\n    auc_scores = [roc_auc_score(val_labels[:, i], val_preds[:, i]) for i in range(14)]\n    print(f\"Epoch {epoch+1}, Train Loss: {train_loss/len(train_loader):.4f}, \"\n          f\"Mean AUC: {np.mean(auc_scores):.4f}, Per-class AUC: {dict(zip(conditions, auc_scores))}\")","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-08-26T11:34:49.881395Z","iopub.execute_input":"2025-08-26T11:34:49.881652Z","iopub.status.idle":"2025-08-26T11:34:50.33207Z","shell.execute_reply.started":"2025-08-26T11:34:49.881634Z","shell.execute_reply":"2025-08-26T11:34:50.331072Z"}},"outputs":[{"traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mImportError\u001b[0m                               Traceback (most recent call last)","\u001b[0;32m/tmp/ipykernel_36/1196719169.py\u001b[0m in \u001b[0;36m<cell line: 0>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     17\u001b[0m \u001b[0;31m# Loss and optimizer\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     18\u001b[0m \u001b[0mcriterion\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnn\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mBCELoss\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mweight\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mclass_weights\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 19\u001b[0;31m \u001b[0moptimizer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtorch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0moptim\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mAdam\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmodel\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mparameters\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlr\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m0.001\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     20\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     21\u001b[0m \u001b[0;31m# Training loop\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/usr/local/lib/python3.11/dist-packages/torch/optim/adam.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, params, lr, betas, eps, weight_decay, amsgrad, foreach, maximize, capturable, differentiable, fused)\u001b[0m\n\u001b[1;32m     97\u001b[0m                         \u001b[0mstate\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'max_exp_avg_sq'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtorch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mzeros_like\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mp\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmemory_format\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtorch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpreserve_format\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     98\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 99\u001b[0;31m                 \u001b[0mexp_avgs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstate\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'exp_avg'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    100\u001b[0m                 \u001b[0mexp_avg_sqs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstate\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'exp_avg_sq'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    101\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/usr/local/lib/python3.11/dist-packages/torch/optim/optimizer.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, params, defaults)\u001b[0m\n\u001b[1;32m    375\u001b[0m             \u001b[0mstate_dict\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mdict\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0moptimizer\u001b[0m \u001b[0mstate\u001b[0m\u001b[0;34m.\u001b[0m \u001b[0mShould\u001b[0m \u001b[0mbe\u001b[0m \u001b[0man\u001b[0m \u001b[0mobject\u001b[0m \u001b[0mreturned\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    376\u001b[0m                 \u001b[0;32mfrom\u001b[0m \u001b[0ma\u001b[0m \u001b[0mcall\u001b[0m \u001b[0mto\u001b[0m \u001b[0;34m:\u001b[0m\u001b[0mmeth\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;31m`\u001b[0m\u001b[0mstate_dict\u001b[0m\u001b[0;31m`\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 377\u001b[0;31m         \"\"\"\n\u001b[0m\u001b[1;32m    378\u001b[0m         \u001b[0;31m# deepcopy, to be consistent with module API\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    379\u001b[0m         \u001b[0mstate_dict\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdeepcopy\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstate_dict\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/usr/local/lib/python3.11/dist-packages/torch/_compile.py\u001b[0m in \u001b[0;36minner\u001b[0;34m(*args, **kwargs)\u001b[0m\n","\u001b[0;32m/usr/local/lib/python3.11/dist-packages/torch/_dynamo/__init__.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0;32mfrom\u001b[0m \u001b[0;34m.\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mallowed_functions\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mconvert_frame\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0meval_frame\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mresume_execution\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0;34m.\u001b[0m\u001b[0mbackends\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mregistry\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mlist_backends\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mregister_backend\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0;34m.\u001b[0m\u001b[0mconvert_frame\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mreplay\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m from .eval_frame import (\n\u001b[1;32m      5\u001b[0m     \u001b[0massume_constant_result\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/usr/local/lib/python3.11/dist-packages/torch/_dynamo/allowed_functions.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m     16\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0;34m.\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mconfig\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     17\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0;34m.\u001b[0m\u001b[0mexternal_utils\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mis_compiling\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 18\u001b[0;31m \u001b[0;32mfrom\u001b[0m \u001b[0;34m.\u001b[0m\u001b[0mutils\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mHAS_NUMPY\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mis_safe_constant\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     19\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     20\u001b[0m \"\"\"\n","\u001b[0;31mImportError\u001b[0m: cannot import name 'HAS_NUMPY' from 'torch._dynamo.utils' (/usr/local/lib/python3.11/dist-packages/torch/_dynamo/utils.py)"],"ename":"ImportError","evalue":"cannot import name 'HAS_NUMPY' from 'torch._dynamo.utils' (/usr/local/lib/python3.11/dist-packages/torch/_dynamo/utils.py)","output_type":"error"}],"execution_count":23},{"cell_type":"code","source":"# Test one batch\nfor images, labels in train_loader:\n    print(f\"Images shape: {images.shape}, Labels shape: {labels.shape}\")\n    break","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-08-26T11:35:40.544241Z","iopub.execute_input":"2025-08-26T11:35:40.544503Z","iopub.status.idle":"2025-08-26T11:35:45.291681Z","shell.execute_reply.started":"2025-08-26T11:35:40.544486Z","shell.execute_reply":"2025-08-26T11:35:45.290963Z"}},"outputs":[{"name":"stdout","text":"Images shape: torch.Size([32, 3, 224, 224]), Labels shape: torch.Size([32, 14])\n","output_type":"stream"}],"execution_count":25}]}