source/modelling/dashboard/loader.py

source-code dashboard data-loading caching

File Path: src/modelling/dashboard/loader.py

Purpose: Data access layer for the dashboard. Handles efficient loading of models and datasets using Streamlit caching.

Functions

get_checkpoints_num_signs(checkpoint_path)

Decorator: @st.cache_data Extracts class count from checkpoint file.

load_cached_checkpoints(checkpoints_dir)

Decorator: @st.cache_data Scans directory for .pth files.

load_cached_model(checkpoint_path, num_signs)

Decorator: @st.cache_resource Loads the PyTorch model and sets it to eval mode.

Calls: model.load_model()

get_cached_dataloaders(num_signs)

Decorator: @st.cache_resource Creates lazy dataloaders for Train/Val/Test splits.

run_inference(_model, _dataloader, device, ...)

Decorator: @st.cache_data Runs full inference pass on a split.

• Returns: (y_true, y_pred, y_probs) as numpy arrays.

Related Documentation

• dataloader.py
• app.py - Consumer

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File Location: src/modelling/dashboard/loader.py