system stringclasses 1
value | conversations listlengths 2 2 |
|---|---|
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport sys\nimport pandas as pd\nimport numpy as np\nfrom PIL import Image\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.utils.data import Dataset, DataLoader, random_split\nfrom sklearn.metrics import roc_auc_score\nimport warn... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport pandas as pd\nimport numpy as np\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.utils.data import DataLoader, Dataset\nfrom torchvision import transforms, models\nfrom PIL import Image\nfrom sklearn.metrics import roc_auc_... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport pandas as pd\nimport numpy as np\nfrom PIL import Image\nimport torch\nimport torch.nn as nn\nfrom torch.utils.data import Dataset, DataLoader\nfrom torchvision import transforms, models\nfrom sklearn.model_selection import train_test_split\nfrom sklear... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport pandas as pd\nimport numpy as np\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.metrics import roc_auc_score\nfrom sklearn.preprocessing import LabelEncoder\nimport glob\nimport cv2\nimport torch\nimport torch.nn as nn\nfrom torch.u... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport pandas as pd\nimport numpy as np\nfrom PIL import Image\nimport torch\nimport torch.nn as nn\nfrom torch.utils.data import Dataset, DataLoader\nfrom torchvision import transforms, models\nfrom sklearn.model_selection import train_test_split\nfrom sklear... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport pandas as pd\nimport numpy as np\nimport torch\nimport torch.nn as nn\nfrom torch.utils.data import Dataset, DataLoader\nimport torchvision.transforms as T\nfrom torchvision.models import resnet18\nfrom sklearn.model_selection import train_test_split\nf... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport gc\nimport numpy as np\nimport pandas as pd\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.utils.data import Dataset, DataLoader\nimport torchvision.transforms as transforms\nfrom sklearn.metrics import roc_auc_score\nfrom... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport pandas as pd\nimport numpy as np\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.metrics import roc_auc_score\nfrom torch.utils.data import Dataset, DataLoader\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom P... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport pandas as pd\nimport numpy as np\nfrom PIL import Image\nfrom torch.utils.data import Dataset, DataLoader\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torchvision import transforms\nfrom sklearn.metrics import roc_auc_score\nf... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport pandas as pd\nimport numpy as np\nfrom PIL import Image\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.utils.data import Dataset, DataLoader\nfrom torchvision import transforms, models\nfrom sklearn.model_selection import ... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport pandas as pd\nimport numpy as np\nfrom PIL import Image\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.metrics import roc_auc_score\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.utils.data import Data... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport numpy as np\nimport pandas as pd\nimport torch\nimport torch.nn as nn\nfrom torch.utils.data import Dataset, DataLoader\nfrom torch.utils.data.sampler import RandomSampler\nimport glob\nimport cv2\nimport time\n\nos.environ[\"TOKENIZERS_PARALLELISM\"] =... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport pandas as pd\nimport numpy as np\nfrom PIL import Image\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.utils.data import Dataset, DataLoader\nfrom torchvision import transforms, models\nfrom sklearn.model_selection import ... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport pandas as pd\nimport numpy as np\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.utils.data import Dataset, DataLoader\nfrom torchvision import transforms, models\nfrom sklearn.model_selection import train_test_split\nfrom ... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport numpy as np\nimport pandas as pd\nimport warnings\nfrom sklearn.metrics import roc_auc_score\n\nwarnings.filterwarnings(\"ignore\")\nos.environ[\"TF_CPP_MIN_LOG_LEVEL\"] = \"3\"\n\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nimport... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport sys\nimport numpy as np\nimport pandas as pd\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.utils.data import Dataset, DataLoader\nfrom PIL import Image\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.m... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.utils.data import Dataset, DataLoader, WeightedRandomSampler\nfrom torchvision import transforms\nimport pandas as pd\nimport numpy as np\nfrom sklearn.model_selection import train_te... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport pandas as pd\nimport numpy as np\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.utils.data import Dataset, DataLoader\nfrom torchvision import transforms\nfrom PIL import Image\nfrom sklearn.model_selection import train_te... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.utils.data import DataLoader, random_split\nfrom torchvision import transforms, models\nfrom PIL import Image\nimport pandas as pd\nimport numpy as np\nfrom sklearn.metrics import roc... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport sys\nimport glob\nimport pandas as pd\nimport numpy as np\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.metrics import roc_auc_score\nfrom PIL import Image\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom tor... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport pandas as pd\nimport numpy as np\nimport torch\nimport torchvision\nfrom torch.utils.data import DataLoader, Dataset\nimport PIL.Image\nfrom sklearn.metrics import roc_auc_score\nimport cv2\nfrom tqdm import tqdm\n\n# Set seeds for reproducibility\ntorc... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport pandas as pd\nimport numpy as np\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.metrics import roc_auc_score\nfrom PIL import Image\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.utils.data import Data... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport pandas as pd\nimport numpy as np\nfrom PIL import Image\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.metrics import roc_auc_score\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.utils.data import Data... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport pandas as pd\nimport numpy as np\nfrom PIL import Image\nfrom torch.utils.data import Dataset, DataLoader\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torchvision import transforms\nfrom sklearn.metrics import roc_auc_score\nf... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport pandas as pd\nimport numpy as np\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.metrics import roc_auc_score\nfrom PIL import Image\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nimport torch.optim as optim\n... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport glob\nimport pandas as pd\nimport numpy as np\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.utils.data import Dataset, DataLoader\nfrom torchvision import transforms, models\nfrom sklearn.metrics import roc_auc_score\nimp... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport pandas as pd\nimport numpy as np\nfrom PIL import Image\nfrom sklearn.ensemble import RandomForestClassifier, GradientBoostingClassifier\nfrom sklearn.metrics import roc_auc_score\nfrom sklearn.model_selection import train_test_split\n\nnp.random.seed(4... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport pandas as pd\nimport numpy as np\nimport torch\nimport torch.nn as nn\nfrom torch.utils.data import Dataset, DataLoader\nfrom torchvision import transforms, models\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.metrics import roc_au... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport warnings\nimport pandas as pd\nimport numpy as np\nimport torch\nimport torch.nn as nn\nfrom torch.utils.data import Dataset, DataLoader\nfrom torchvision import transforms\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.metrics impo... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport pandas as pd\nimport numpy as np\nimport torch\nimport torch.nn as nn\nfrom torch.utils.data import Dataset, DataLoader\nimport torchvision.transforms as transforms\nimport timm\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.metrics... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport numpy as np\nimport pandas as pd\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.metrics import roc_auc_score\nfrom PIL import Image\nimport lightgbm as lgb\nimport glob\nimport cv2\n\n# Set paths based on Data Overview\nDATA_DIR = \... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport pandas as pd\nimport numpy as np\nfrom PIL import Image\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.utils.data import Dataset, DataLoader\nfrom torchvision import transforms\nfrom sklearn.metrics import roc_auc_score\nf... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport pandas as pd\nimport numpy as np\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.utils.data import Dataset, DataLoader\nfrom torchvision import transforms, models\nfrom PIL import Image\nfrom sklearn.metrics import roc_auc_... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport pandas as pd\nimport numpy as np\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.utils.data import Dataset, DataLoader\nfrom torchvision import transforms, models\nfrom PIL import Image\nfrom sklearn.model_selection import ... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport sys\nimport csv\nimport numpy as np\nimport pandas as pd\nfrom PIL import Image\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.metrics import roc_auc_score\nfrom scipy.sparse.linalg import lsapack\nimport torch\nimport torch.nn as n... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport pandas as pd\nimport numpy as np\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.metrics import roc_auc_score\nfrom PIL import Image\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.utils.data import Data... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport numpy as np\nimport pandas as pd\nimport torch\nfrom torchvision import transforms, models\nfrom PIL import Image\nfrom sklearn.metrics import roc_auc_score\n\n# Set seeds for reproducibility\ntorch.manual_seed(42)\nnp.random.seed(42)\n\nos.makedirs(\".... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport pandas as pd\nimport numpy as np\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.utils.data import Dataset, DataLoader\nfrom torchvision import transforms, models\nfrom PIL import Image\nfrom sklearn.model_selection import ... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport pandas as pd\nimport numpy as np\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.metrics import roc_auc_score\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.utils.data import DataLoader, Dataset\nfrom t... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.utils.data import DataLoader, Subset\nfrom torchvision import transforms, models\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.metrics import roc_auc_score\nimpo... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport glob\nimport pickle\nimport json\nimport numpy as np\nimport pandas as pd\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.utils.data import Dataset, DataLoader\nfrom sklearn.model_selection import train_test_split\nfrom skl... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport pandas as pd\nimport numpy as np\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.utils.data import Dataset, DataLoader\nfrom torchvision import transforms, models\nfrom sklearn.model_selection import train_test_split\nfrom ... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport pandas as pd\nimport numpy as np\nfrom PIL import Image\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.utils.data import Dataset, DataLoader\nfrom torchvision import transforms\nimport timm\nfrom sklearn.model_selection im... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport numpy as np\nimport pandas as pd\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.utils.data import Dataset, DataLoader\nfrom PIL import Image\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.metrics impor... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport pandas as pd\nimport numpy as np\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.metrics import roc_auc_score\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.utils.data import DataLoader, Dataset\nfrom t... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport pandas as pd\nimport numpy as np\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.metrics import roc_auc_score\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.utils.data import DataLoader, Dataset\nfrom t... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport sys\nfrom pathlib import Path\nimport numpy as np\nimport pandas as pd\nfrom torch.utils.data import Dataset, DataLoader\nimport torch\nimport torch.nn as nn\nimport torchvision.transforms as T\nfrom sklearn.metrics import roc_auc_score\nfrom PIL import... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport numpy as np\nimport pandas as pd\nimport torch\nimport torch.nn as nn\nfrom torch.utils.data import Dataset, DataLoader\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.metrics import roc_auc_score\nfrom collections import defaultdict... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport pandas as pd\nimport numpy as np\nfrom PIL import Image\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.utils.data import Dataset, DataLoader\nfrom torchvision import transforms\nimport torchvision.models as models\nfrom sk... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport pandas as pd\nimport numpy as np\nimport torch\nimport torch.nn as nn\nfrom torch.utils.data import Dataset, DataLoader\nfrom torchvision import transforms\nimport timm\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.metrics import r... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport pandas as pd\nimport numpy as np\nfrom PIL import Image\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.metrics import roc_auc_score\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.utils.data import Data... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport numpy as np\nimport pandas as pd\nfrom PIL import Image\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.preprocessing import RobustScaler\nfrom sklearn.metrics import roc_auc_score\nimport xgboost as xgb\nimport cv2\nimport warnings\... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport pandas as pd\nimport numpy as np\nimport torch\nimport torch.nn as nn\nfrom torch.utils.data import Dataset, DataLoader\nfrom torchvision import transforms, models\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.metrics import roc_au... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport numpy as np\nimport pandas as pd\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.metrics import roc_auc_score\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.utils.data import DataLoader, Dataset\nfrom t... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport pandas as pd\nimport numpy as np\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.metrics import roc_auc_score\nimport torch\nimport torch.nn as nn\nfrom torch.utils.data import DataLoader, Dataset\nfrom torchvision import transforms,... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport shutil\nimport numpy as np\nimport pandas as pd\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.metrics import roc_auc_score\nfrom sklearn.ensemble import RandomForestClassifier\nfrom PIL import Image\n\n\ndef load_train_data():\n ... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport glob\nimport numpy as np\nimport pandas as pd\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.utils.data import Dataset, DataLoader\nfrom torchvision import transforms\nfrom sklearn.model_selection import train_test_split\n... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport numpy as np\nimport pandas as pd\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.utils.data import Dataset, DataLoader\nfrom torchvision import models, transforms\nfrom PIL import Image\nfrom sklearn.model_selection import ... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport sys\nimport numpy as np\nimport pandas as pd\nimport torch\nimport torchvision\nfrom torch.utils.data import Dataset, DataLoader\nfrom PIL import Image\nfrom torchvision import transforms\nfrom sklearn.metrics import roc_auc_score\nimport warnings\n\nwa... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.utils.data import DataLoader, Dataset\nfrom torchvision import transforms\nfrom PIL import Image\nimport pandas as pd\nimport numpy as np\nfrom sklearn.model_selection import train_te... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport numpy as np\nimport pandas as pd\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.metrics import roc_auc_score\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torchvision import datasets, transforms\nfrom PIL i... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport pandas as pd\nimport numpy as np\nfrom PIL import Image\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.utils.data import Dataset, DataLoader\nfrom torchvision import transforms, models\nfrom sklearn.model_selection import ... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport pandas as pd\nimport numpy as np\nimport torch\nimport torch.nn as nn\nimport time\nfrom torch.utils.data import Dataset, DataLoader\nfrom torchvision import transforms\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.metrics import r... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport numpy as np\nimport pandas as pd\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.ensemble import GradientBoostingClassifier\nfrom sklearn.metrics import roc_auc_score\nfrom PIL import Image\n\n# Set up paths\ninput_dir = \"./input\"\... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.utils.data import DataLoader, Dataset\nfrom torchvision import transforms\nfrom PIL import Image\nimport pandas as pd\nimport numpy as np\nfrom sklearn.model_selection import train_te... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport sys\nimport warnings\nimport numpy as np\nimport pandas as pd\nimport torch\nfrom torch import nn\nfrom torch.utils.data import Dataset, DataLoader\nfrom torchvision import transforms, models\nfrom PIL import Image\nfrom sklearn.metrics import roc_auc_s... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport numpy as np\nimport pandas as pd\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.utils.data import Dataset, DataLoader\nfrom torchvision import transforms\nfrom torchvision.models import efficientnet_b0, EfficientNet_B0_Wei... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport pandas as pd\nimport numpy as np\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.utils.data import DataLoader, Dataset\nfrom torchvision import transforms, models\nfrom sklearn.model_selection import train_test_split\nfrom ... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport numpy as np\nimport pandas as pd\nimport torch\nimport torch.nn as nn\nfrom torchvision import transforms\nfrom torch.utils.data import DataLoader, TensorDataset\nfrom sklearn.metrics import roc_auc_score\nfrom PIL import Image\n\n# Set seeds for reprod... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport numpy as np\nimport pandas as pd\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.utils.data import Dataset, DataLoader\nfrom torchvision import transforms, utils\nfrom torchvision.models import efficientnet_b0, EfficientNet... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport pandas as pd\nimport numpy as np\nfrom PIL import Image\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.metrics import roc_auc_score\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.utils.data import Data... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport pandas as pd\nimport numpy as np\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.utils.data import Dataset, DataLoader\nfrom torchvision import transforms\nfrom PIL import Image\nfrom sklearn.model_selection import train_te... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport glob\nimport numpy as np\nimport pandas as pd\nfrom PIL import Image\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.utils.data import Dataset, DataLoader\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.utils.data import Dataset, DataLoader, WeightedRandomSampler\nfrom torchvision import transforms\nimport pandas as pd\nimport numpy as np\nfrom sklearn.model_selection import train_te... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nThe user is asking me to fix a buggy PyTorch implementation. Let me analyze the problem:\n\n1. **The main bug**: The model is on CPU (weights are downloaded from torchvision but not moved to CUDA), but the input images are being passed to CUDA (`imgs = imgs.to(DEVICE)`).... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport sys\nimport numpy as np\nimport pandas as pd\nfrom pathlib import Path\nimport torch\nimport torchvision\nfrom torchvision import models, transforms\nfrom PIL import Image\nfrom sklearn.metrics import roc_auc_score\nimport warnings\n\nwarnings.filterwar... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport pandas as pd\nimport numpy as np\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.utils.data import Dataset, DataLoader\nfrom torchvision import transforms, models\nfrom PIL import Image\nfrom sklearn.metrics import roc_auc_... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport glob\nimport pandas as pd\nimport numpy as np\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.utils.data import Dataset, DataLoader\nfrom sklearn.metrics import roc_auc_score\nfrom PIL import Image\nimport torch.nn.function... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport numpy as np\nimport pandas as pd\nfrom sklearn.model_selection import train_test_split\nfrom xgboost import XGBClassifier\nfrom sklearn.metrics import roc_auc_score\nfrom PIL import Image\nimport io\nimport json\n\n# Set up paths\ninput_dir = \"./input\... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport numpy as np\nimport pandas as pd\nfrom PIL import Image\nfrom torch.utils.data import Dataset, DataLoader\nimport torch\nimport torch.nn as nn\nfrom sklearn.metrics import roc_auc_score\nimport glob\nimport random\nfrom pathlib import Path\nimport warni... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.utils.data import DataLoader, Dataset, WeightedRandomSampler\nimport pandas as pd\nimport numpy as np\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.metrics impor... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport numpy as np\nimport pandas as pd\nfrom PIL import Image\nfrom torch.utils.data import Dataset, DataLoader\nimport torch\nimport torch.nn as nn\nfrom sklearn.metrics import roc_auc_score\nimport glob\nimport random\nfrom pathlib import Path\nimport warni... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport pandas as pd\nimport numpy as np\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.utils.data import Dataset, DataLoader\nfrom sklearn.model_selection import StratifiedKFold\nfrom sklearn.metrics import roc_auc_score\nfrom to... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport pandas as pd\nimport numpy as np\nfrom PIL import Image\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.utils.data import Dataset, DataLoader\nfrom torchvision import transforms, models\nfrom sklearn.model_selection import ... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport pandas as pd\nimport numpy as np\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.utils.data import Dataset, DataLoader\nfrom torchvision import transforms, models\nfrom PIL import Image\nfrom sklearn.metrics import roc_auc_... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport numpy as np\nimport pandas as pd\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.utils.data import Dataset, DataLoader\nfrom sklearn.metrics import roc_auc_score\nfrom sklearn.model_selection import train_test_split\nimport... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport numpy as np\nimport pandas as pd\nimport torch\nfrom torch.utils.data import Dataset, DataLoader\nimport torchvision.transforms as transforms\nimport torchvision.models as models\nfrom sklearn.metrics import roc_auc_score\nfrom tqdm import tqdm\nimport ... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport pandas as pd\nimport numpy as np\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.utils.data import Dataset, DataLoader\nfrom torchvision import transforms, models\nfrom sklearn.model_selection import train_test_split\nfrom ... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport numpy as np\nimport pandas as pd\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.metrics import roc_auc_score\nimport xgboost as xgb\nfrom PIL import Image\nimport cv2\nimport copy\n\n# Load data\ntrain_df = pd.read_csv(\"./input/tra... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.utils.data import DataLoader, TensorDataset\nimport torchvision.transforms as transforms\nimport numpy as np\nimport pandas as pd\nimport cv2\nfrom sklearn.metrics import roc_auc_scor... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport numpy as np\nimport pandas as pd\nimport torch\nimport torch.nn as nn\nfrom torch.utils.data import DataLoader, Dataset\nfrom torchvision import transforms, models\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.metrics import roc_au... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport numpy as np\nimport pandas as pd\nfrom sklearn.metrics import roc_auc_score\nfrom sklearn.model_selection import train_test_split\nimport torch\nimport torch.nn as nn\nfrom torch.utils.data import Dataset, DataLoader\nfrom PIL import Image\nimport cv2\n... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport warnings\n\nwarnings.filterwarnings(\"ignore\")\nimport pandas as pd\nimport numpy as np\nimport torch\nimport torch.nn as nn\nfrom torch.optim import AdamW\nfrom torch.optim.lr_scheduler import CosineAnnealingLR\nfrom torch.utils.data import Dataset, D... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport pandas as pd\nimport numpy as np\nfrom PIL import Image\nfrom torch.utils.data import Dataset, DataLoader\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torchvision import transforms\nfrom sklearn.metrics import roc_auc_score\nf... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport pandas as pd\nimport numpy as np\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.metrics import roc_auc_score\nfrom PIL import Image\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.utils.data import Data... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport sys\nimport pandas as pd\nimport numpy as np\nfrom sklearn.ensemble import GradientBoostingClassifier\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.metrics import roc_auc_score, roc_curve\nfrom sklearn.preprocessing import Standard... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport sys\nimport pandas as pd\nimport numpy as np\nfrom PIL import Image\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.utils.data import Dataset, DataLoader, random_split\nfrom sklearn.metrics import roc_auc_score\nimport warn... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport pandas as pd\nimport numpy as np\nimport torch\nimport torch.nn as nn\nfrom torch.utils.data import Dataset, DataLoader\nfrom torchvision import transforms\nfrom PIL import Image\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.metric... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport numpy as np\nimport pandas as pd\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.utils.data import DataLoader, Dataset, random_split\nfrom torchvision import transforms\nfrom sklearn.model_selection import train_test_split\... |
Predict the outcome and terminal output (stdout+stderr) of a Python ML script.
Input, in order:
- <code>, the script, run as runfile.py.
- <environment>, the importable packages. Authoritative: a library not listed is not importable, and the listed version is the one whose API applies.
- <data_overview>, truth for fil... | [
{
"from": "human",
"value": "<code>\nimport os\nimport pandas as pd\nimport numpy as np\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.utils.data import DataLoader, Dataset\nfrom torchvision import transforms, models\nfrom sklearn.model_selection import train_test_split\nfrom ... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.