Python PyTorch Code Generator

Text generator - Pytorch neural network code generation example

Example input

• # train a neural network in pytorch - efficient net for image classification import pytorch_lightning import torch import numpy as np import cv2

Example real generated results

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  from pytorch_lightning import __version__ as pytorch_lightning_version from pytorch_lightning.core import DataModule, Trainer from pytorch_lightning.callbacks import EarlyStopping from sklearn.model_selection import train_test_split from sklearn.preprocessing import LabelEncoder from sklearn.metrics import accuracy_score, classification_report, confusion_matrix import os from torch.utils.data import Dataset, DataLoader from

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  class EfficientNet(pytorch_lightning.LightningModule): def __init__(self, num_classes=1000): super().__init__() self.model = pytorch_lightning. Worksheeet_Module( pretrained='imagenet', num_classes=num_classes, num_initial_features=64, num_classes=num_classes ) def forward(self, x): return self

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  import pandas as pd from sklearn.model_selection import train_test_split from sklearn.metrics import accuracy_score # Define the data loading function def load_data(path): images = [] labels = [] for file in os.listdir(path): img = cv2.imread(os.path.join(path, file)) img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)

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  import torch.nn as nn from torch.utils.data import DataLoader, Dataset from torchvision import datasets, transforms from torch.optim.lr_scheduler import LrSchedule # Define a custom dataset class to load the data class ImageDataset(torch.utils.data.Dataset): def __init__(self, data, labels, transform=None): self.data = data self.labels = labels self.transform = transform def __len__(

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