Fix momo crash when loss value is a Python float #1502
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Thanks! Can you adjust the type annotation to reflect the value requirement? Should probably drop Optional and use |
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@rdyro Thanks for the review! I've made the suggested changes and updated the type annotation to use jax.typing.ArrayLike. Ready for another look. |
Fixes google-deepmind#1500 The momo and momo_adam update functions declared the value parameter as Optional[jax.Array] but never enforced that type. When calling value.astype(state.barf.dtype), passing a Python float or NumPy scalar would raise AttributeError since these types don't have an astype method. This fix uses jnp.asarray(value, dtype=state.barf.dtype) instead of value.astype(state.barf.dtype) to handle Python floats, NumPy scalars, and JAX arrays uniformly.
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Fixes #1500
The momo and momo_adam update functions declared the value parameter as Optional[jax.Array] but never enforced that type. When calling value.astype(state.barf.dtype), passing a Python float or NumPy scalar would raise AttributeError since these types don't have an astype method.
This fix uses jnp.asarray(value, dtype=state.barf.dtype) instead of value.astype(state.barf.dtype) to handle Python floats, NumPy scalars, and JAX arrays uniformly.