Spaces:
Running on Zero
Running on Zero
Vansh Chugh commited on
Commit ·
f910f14
1
Parent(s): 41c1e2b
cleanup: fix fidelity comment, rename opaque var, drop MMT-repo reference
Browse files- .gitignore +0 -1
- app.py +7 -5
.gitignore
CHANGED
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@@ -2,5 +2,4 @@ __pycache__/
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*.pyc
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.DS_Store
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.venv/
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MMT-repo/
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_outputs/
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*.pyc
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.DS_Store
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.venv/
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_outputs/
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app.py
CHANGED
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@@ -49,7 +49,7 @@ def load_model():
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"""Build the model on CPU and load the sod/ape checkpoint weights. Stays on
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CPU here even if GPU hardware is available -- ZeroGPU only allows touching
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CUDA from inside an @spaces.GPU call, not at module load time."""
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-
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dim=train_args["dim"],
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encoding=encoding,
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depth=train_args["layers"],
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@@ -65,9 +65,9 @@ def load_model():
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state_dict = torch.load(
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CKPT_DIR / "checkpoints" / "best_model.pt", map_location="cpu"
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)
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-
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-
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return
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# Checkpoint is small (~80MB) and lives in the Space repo, so load it
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@@ -224,7 +224,9 @@ def process_fn(input_midi_path, instruments_text, generation_length, temperature
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audio_path = None
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if render_audio:
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audio_path = get_default_path(ext=".wav")
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-
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report_path = get_default_path(ext=".txt")
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Path(report_path).write_text(f"{report_name}\n\nInstrument Matching\n{instrument_note}\n")
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"""Build the model on CPU and load the sod/ape checkpoint weights. Stays on
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CPU here even if GPU hardware is available -- ZeroGPU only allows touching
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CUDA from inside an @spaces.GPU call, not at module load time."""
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+
model = music_x_transformers.MusicXTransformer(
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dim=train_args["dim"],
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encoding=encoding,
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depth=train_args["layers"],
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state_dict = torch.load(
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CKPT_DIR / "checkpoints" / "best_model.pt", map_location="cpu"
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)
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model.load_state_dict(state_dict)
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model.eval()
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return model
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# Checkpoint is small (~80MB) and lives in the Space repo, so load it
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audio_path = None
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if render_audio:
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audio_path = get_default_path(ext=".wav")
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# Uses the MuseScore General soundfont muspy fetches on first use. The original repo's
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# polyphony option isn't supported by muspy==0.5.0's write_audio() (no passthrough kwarg).
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music.write(audio_path)
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report_path = get_default_path(ext=".txt")
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Path(report_path).write_text(f"{report_name}\n\nInstrument Matching\n{instrument_note}\n")
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