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Add function to safely compute the norm
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import jax.numpy as jnp | ||
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import jaxsim.typing as jtp | ||
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def safe_norm(array: jtp.ArrayLike, axis=None) -> jtp.Array: | ||
""" | ||
Provides a calculation for an array norm so that it is safe | ||
to compute the gradient and the NaNs are handled. | ||
Args: | ||
array: The array for which to compute the norm | ||
axis: The axis for which to compute the norm | ||
""" | ||
is_zero = jnp.allclose(array, 0.0) | ||
array = jnp.where(is_zero, jnp.ones_like(array), array) | ||
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norm = jnp.linalg.norm(array, axis=axis) | ||
return jnp.where(is_zero, 0.0, norm) |
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