support parameters to be string represenations of complex types #37
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for terratorch config is passed in as yaml config, therefore we need to be able to go from string to complex type
WillTrojak
suggested changes
Jan 20, 2025
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I think this is a bit dodgey. You are saying that any string that is passed to the model as these inputs should be evaluated, this can allow malicious code execution. What would probably be better would be to use numpy fromstring, depending on what you're trying to do.
| if isinstance(static_input_scalers_mu, str): static_input_scalers_mu = eval(static_input_scalers_mu) | ||
| if isinstance(static_input_scalers_sigma, str): static_input_scalers_sigma = eval(static_input_scalers_sigma) | ||
| if isinstance(output_scalers, str): output_scalers = eval(output_scalers) | ||
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| @@ -803,6 +803,14 @@ def __init__( | |||
| """ | |||
| super().__init__() | |||
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| # assume input_scalers_mu is string of form: torch.tensor([0] * 1280) | |||
| if isinstance(input_scalers_mu, str): input_scalers_mu = eval(input_scalers_mu) | |||
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I'm not sure about these evals.
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@romeokienzler, any update on this? Also, can you roll back the changes force pushed to main. |
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for terratorch config is passed in as yaml config, therefore we need to be able to go from string to complex type