Download scripts/fake_data.py from OneScience-Group/CorrDiff: direct link, hf CLI and curl.
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- Download file 750 Bytes
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https://huggingface.co/OneScience-Group/CorrDiff/resolve/986404c2a61bc08c2ce76d68fd427eb583cf291b/scripts/fake_data.py
- Command line
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hf download hf://OneScience-Group/CorrDiff@986404c2a61bc08c2ce76d68fd427eb583cf291b/scripts/fake_data.py
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curl -L -o fake_data.py https://huggingface.co/OneScience-Group/CorrDiff/resolve/986404c2a61bc08c2ce76d68fd427eb583cf291b/scripts/fake_data.py
750 Bytes
| from pathlib import Path | |
| import argparse | |
| import numpy as np | |
| def main(): | |
| parser = argparse.ArgumentParser() | |
| parser.add_argument("--output", default="data/fake_corrdiff.npz") | |
| parser.add_argument("--samples", type=int, default=1) | |
| args = parser.parse_args() | |
| path = Path(args.output) | |
| path.parent.mkdir(parents=True, exist_ok=True) | |
| rng = np.random.default_rng(42) | |
| inputs = rng.standard_normal((args.samples, 12, 36, 36)).astype("float32") | |
| targets = rng.standard_normal((args.samples, 4, 448, 448)).astype("float32") | |
| np.savez_compressed(path, input=inputs, target=targets) | |
| print(f"input: {inputs.shape}") | |
| print(f"target: {targets.shape}") | |
| print(f"saved: {path}") | |
| if __name__ == "__main__": | |
| main() | |