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which would behave similarly to this kind of expression in regular NumPy
A[1::2, ..., :-3] =value
except without the in-place mutation that would update any aliases.
This wrapper would be similar to the lax_numpy._rewriting_take function we already have for handling complex indexing expressions, and would ultimately call into primitives like lax.dynamic_update_slice and lax.index_untake. Better name suggestions welcome!
This is a separate issue from whether to provide more convenient syntax for this kind of operation.
The text was updated successfully, but these errors were encountered:
This is a really important operation for making it simple to express certain models. When using TF I have often had to spend a lot of time figuring out exactly how to use scatter_nd or whatever so making a clear correspondence with numpy syntax is useful.
…NumPy-style indexed updates.
Create a new library `jax.ops` for user-facing ops that don't exist in NumPy or SciPy.
Progress on issue jax-ml#101. Fixesjax-ml#122.
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…NumPy-style indexed updates.
Create a new library `jax.ops` for user-facing ops that don't exist in NumPy or SciPy.
Progress on issue jax-ml#101. Fixesjax-ml#122.
Reenable some disabled TPU indexing tests that now pass.
We should provide an
update
function that lets users writewhich would behave similarly to this kind of expression in regular NumPy
except without the in-place mutation that would update any aliases.
This wrapper would be similar to the
lax_numpy._rewriting_take
function we already have for handling complex indexing expressions, and would ultimately call into primitives likelax.dynamic_update_slice
andlax.index_untake
. Better name suggestions welcome!This is a separate issue from whether to provide more convenient syntax for this kind of operation.
The text was updated successfully, but these errors were encountered: