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fix: device in window_scatter_function now uses from_nx #1640

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fix: device in window_scatter_function now uses from_nx #1640

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6a289c7
Fix reshape example in quickstart.livemd
Chapaman Sep 16, 2025
f15e7cd
now we get the device from nx instead of just defaulting to the cpu
Chapaman Oct 27, 2025
6b4b267
Merge branch 'main' into issue-679
Chapaman Nov 3, 2025
8b8b6a6
added test for indices_to_flatten
Chapaman Nov 3, 2025
b96581d
fixed test by using assert_equal
Chapaman Nov 3, 2025
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2 changes: 1 addition & 1 deletion nx/guides/getting_started/quickstart.livemd
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Original file line number Diff line number Diff line change
Expand Up @@ -162,7 +162,7 @@ Nx.shape(tensor)
We can also create a new tensor with the given shape using `Nx.reshape/2`:

```elixir
Nx.reshape(tensor, {1, 4}, names: [:batches, :values])
Nx.reshape(tensor, {1, 6}, names: [:batches, :values])
```
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@polvalente polvalente Oct 27, 2025

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I think this is a stray change. Can you open a separate PR with this?


This operation generally reuses all of the tensor data and simply
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4 changes: 3 additions & 1 deletion torchx/lib/torchx/backend.ex
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Expand Up @@ -1528,13 +1528,15 @@ defmodule Torchx.Backend do
|> then(unfold_flat)
|> then(function)

{device, _} = from_nx(tensor)

indices_to_flatten =
tensor
|> Nx.axes()
|> Enum.map(fn axis ->
tensor
|> Nx.shape()
|> Nx.iota(axis: axis, backend: Torchx.Backend)
|> Nx.iota(axis: axis, backend: {Torchx.Backend, device: device})
|> then(unfold_flat)
|> Nx.take_along_axis(Nx.new_axis(arg_idx, -1), axis: -1)
end)
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