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0d31687638
Encoder.eval() alone still builds an autograd graph because parameters require grad by default. On 8GB GPUs that ballooned TADA encode VRAM far past the model footprint (issue 890). Wrap the encode forward in inference_mode and add a unit test that asserts the flag is set. Co-authored-by: fooSynaptic <[email protected]>
Backend Tests
Manual test scripts for debugging and validating backend functionality.
Test Files
test_generation_progress.py
Tests TTS generation with SSE progress monitoring to identify UX issues where users see download progress even when the model is already cached.
Usage:
cd backend
python tests/test_generation_progress.py
Prerequisites:
- Server must be running (
python main.py) - At least one voice profile must exist
test_real_download.py
Tests real model download with SSE progress monitoring.
Usage:
cd backend
# Delete cache first to force fresh download
rm -rf ~/.cache/huggingface/hub/models--openai--whisper-base
python tests/test_real_download.py
Prerequisites:
- Server must be running (
python main.py)
test_progress.py
Unit tests for ProgressManager and HFProgressTracker functionality.
Usage:
cd backend
python tests/test_progress.py
test_check_progress_state.py
Debugging script to inspect the internal state of ProgressManager and TaskManager.
Usage:
cd backend
python tests/test_check_progress_state.py
Notes
These are manual test scripts, not automated unit tests. They're designed for:
- Debugging progress tracking issues
- Validating SSE event streams
- Monitoring real-time download behavior
- Inspecting internal state during development