| INTEG=AUDIOCRAFT_DORA_DIR="/tmp/magma_$(USER)" python3 -m dora -v run --clear device=cpu dataset.num_workers=0 optim.epochs=1 \ | |
| dataset.train.num_samples=10 dataset.valid.num_samples=10 \ | |
| dataset.evaluate.num_samples=10 dataset.generate.num_samples=2 sample_rate=16000 \ | |
| logging.level=DEBUG | |
| INTEG_COMPRESSION = $(INTEG) solver=compression/debug rvq.n_q=2 rvq.bins=48 checkpoint.save_last=true # SIG is 5091833e | |
| INTEG_MUSICGEN = $(INTEG) solver=musicgen/debug dset=audio/example compression_model_checkpoint=//sig/5091833e \ | |
| transformer_lm.n_q=2 transformer_lm.card=48 transformer_lm.dim=16 checkpoint.save_last=false # Using compression model from 5091833e | |
| INTEG_AUDIOGEN = $(INTEG) solver=audiogen/debug dset=audio/example compression_model_checkpoint=//sig/5091833e \ | |
| transformer_lm.n_q=2 transformer_lm.card=48 transformer_lm.dim=16 checkpoint.save_last=false # Using compression model from 5091833e | |
| INTEG_MBD = $(INTEG) solver=diffusion/debug dset=audio/example \ | |
| checkpoint.save_last=false # Using compression model from 616d7b3c | |
| INTEG_WATERMARK = AUDIOCRAFT_DORA_DIR="/tmp/wm_$(USER)" dora run device=cpu dataset.num_workers=0 optim.epochs=1 \ | |
| dataset.train.num_samples=10 dataset.valid.num_samples=10 dataset.evaluate.num_samples=10 dataset.generate.num_samples=10 \ | |
| logging.level=DEBUG solver=watermark/robustness checkpoint.save_last=false dset=audio/example | |
| default: linter tests | |
| install: | |
| pip install -U pip | |
| pip install -U -e '.[dev]' | |
| linter: | |
| flake8 audiocraft && mypy audiocraft | |
| flake8 tests && mypy tests | |
| tests: | |
| coverage run -m pytest tests | |
| coverage report | |
| tests_integ: | |
| $(INTEG_COMPRESSION) | |
| $(INTEG_MBD) | |
| $(INTEG_MUSICGEN) | |
| $(INTEG_AUDIOGEN) | |
| $(INTEG_WATERMARK) | |
| api_docs: | |
| pdoc3 --html -o api_docs -f audiocraft | |
| dist: | |
| python setup.py sdist | |
| .PHONY: linter tests api_docs dist | |