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aiuNN
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develop #4

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Fabel merged 103 commits from develop into main 2025-03-01 21:47:17 +00:00
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src/aiunn/finetune.py
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@ -15,7 +15,7 @@ class UpscaleDataset(Dataset):
combined_df = pd.DataFrame() combined_df = pd.DataFrame()
for parquet_file in parquet_files: for parquet_file in parquet_files:
# Load data with chunking for memory efficiency # Load data with chunking for memory efficiency
df = pd.read_parquet(parquet_file, columns=['image_512', 'image_1024']).head(2500) df = pd.read_parquet(parquet_file, columns=['image_512', 'image_1024']).head(1250)
combined_df = pd.concat([combined_df, df], ignore_index=True) combined_df = pd.concat([combined_df, df], ignore_index=True)
# Validate data format # Validate data format
@ -94,7 +94,7 @@ from torch.utils.data import DataLoader
# Create your dataset and dataloader # Create your dataset and dataloader
dataset = UpscaleDataset(["/root/training_data/vision-dataset/image_upscaler.parquet", "/root/training_data/vision-dataset/image_vec_upscaler.parquet"], transform=transform) dataset = UpscaleDataset(["/root/training_data/vision-dataset/image_upscaler.parquet", "/root/training_data/vision-dataset/image_vec_upscaler.parquet"], transform=transform)
data_loader = DataLoader(dataset, batch_size=2, shuffle=True) data_loader = DataLoader(dataset, batch_size=1, shuffle=True)
# Define a loss function and optimizer # Define a loss function and optimizer
criterion = nn.MSELoss() criterion = nn.MSELoss()