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Merged
polvalente merged 3 commits into from
Aug 11, 2026
Merged

chore: update to nx 0.13 #641

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3f6f77a
chore: update to nx 0.13
polvalente Aug 11, 2026
6e3c974
fix get_weights
polvalente Aug 11, 2026
73edbf5
use Nx.Testing and fix ci
polvalente Aug 11, 2026
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22 changes: 14 additions & 8 deletions .github/workflows/test.yaml
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Original file line number Diff line number Diff line change
Expand Up @@ -22,16 +22,22 @@ jobs:
fail-fast: false
matrix:
include:
- otp: "27.1"
elixir: "1.19.0"
- otp: "28.1"
elixir: "1.20.1"
lint: true
- otp: "26.1.1"
elixir: "1.15.6"
- otp: "26.1.1"
elixir: "1.15.6"
- otp: "28.1"
elixir: "1.20.1"
test_command_prepend: "USE_EXLA=true"
- otp: "28.1"
elixir: "1.20.1"
test_command_prepend: "USE_TORCHX=true"
- otp: "27.2.2"
elixir: "1.19.0"
- otp: "27.2.2"
elixir: "1.19.0"
test_command_prepend: "USE_EXLA=true"
- otp: "26.1.1"
elixir: "1.15.6"
- otp: "27.2.2"
elixir: "1.19.0"
test_command_prepend: "USE_TORCHX=true"
steps:
- uses: actions/checkout@v3
Expand Down
8 changes: 3 additions & 5 deletions lib/axon.ex
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Original file line number Diff line number Diff line change
Expand Up @@ -281,8 +281,6 @@ defmodule Axon do

import Axon.Shared

require Logger

@type t :: %__MODULE__{}

defstruct [
Expand Down Expand Up @@ -4032,11 +4030,11 @@ defmodule Axon do
%{op_name: :container, parent: parents, op: fun} = popped ->
{popped, apply(fun, Enum.map(parents, &%Axon{nodes: nodes, output: &1}) ++ [[]])}

%{parent: [_ | _] = parents} = popped ->
{popped, Enum.map(parents, &%Axon{nodes: nodes, output: &1})}

%{parent: [parent_id]} = popped ->
{popped, %Axon{nodes: nodes, output: parent_id}}

%{parent: [_ | _] = parents} = popped ->
{popped, Enum.map(parents, &%Axon{nodes: nodes, output: &1})}
end
end

Expand Down
96 changes: 48 additions & 48 deletions lib/axon/activations.ex
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Original file line number Diff line number Diff line change
Expand Up @@ -23,7 +23,7 @@ defmodule Axon.Activations do
#Nx.Tensor<
f32[1][3]
[
[0.09003057330846786, 0.2447284758090973, 0.6652409434318542]
[0.09003057, 0.24472848, 0.66524094]
]
>

Expand Down Expand Up @@ -61,14 +61,14 @@ defmodule Axon.Activations do
iex> Axon.Activations.celu(Nx.tensor([-3.0, -2.0, -1.0, 0.0, 1.0, 2.0, 3.0]))
#Nx.Tensor<
f32[7]
[-0.9502129554748535, -0.8646647334098816, -0.6321205496788025, 0.0, 1.0, 2.0, 3.0]
[-0.95021296, -0.86466473, -0.63212055, 0.0, 1.0, 2.0, 3.0]
>

iex> Axon.Activations.celu(Nx.tensor([[-1.0, -2.0, -3.0], [1.0, 2.0, 3.0]], type: {:bf, 16}))
#Nx.Tensor<
bf16[2][3]
[
[-0.62890625, -0.86328125, -0.94921875],
[-0.63, -0.863, -0.95],
[1.0, 2.0, 3.0]
]
>
Expand Down Expand Up @@ -111,14 +111,14 @@ defmodule Axon.Activations do
iex> Axon.Activations.elu(Nx.tensor([-3.0, -2.0, -1.0, 0.0, 1.0, 2.0, 3.0]))
#Nx.Tensor<
f32[7]
[-0.9502129554748535, -0.8646647334098816, -0.6321205496788025, 0.0, 1.0, 2.0, 3.0]
[-0.95021296, -0.86466473, -0.63212055, 0.0, 1.0, 2.0, 3.0]
>

iex> Axon.Activations.elu(Nx.tensor([[-1.0, -2.0, -3.0], [1.0, 2.0, 3.0]], type: {:bf, 16}))
#Nx.Tensor<
bf16[2][3]
[
[-0.62890625, -0.86328125, -0.94921875],
[-0.63, -0.863, -0.95],
[1.0, 2.0, 3.0]
]
>
Expand All @@ -144,15 +144,15 @@ defmodule Axon.Activations do
iex> Axon.Activations.exp(Nx.tensor([-3.0, -2.0, -1.0, 0.0, 1.0, 2.0, 3.0], names: [:data]))
#Nx.Tensor<
f32[data: 7]
[0.049787066876888275, 0.1353352814912796, 0.3678794503211975, 1.0, 2.7182817459106445, 7.389056205749512, 20.08553695678711]
[0.049787067, 0.13533528, 0.36787945, 1.0, 2.7182817, 7.389056, 20.085537]
>

iex> Axon.Activations.exp(Nx.tensor([[-1.0, -2.0, -3.0], [1.0, 2.0, 3.0]], type: {:bf, 16}, names: [:batch, :data]))
#Nx.Tensor<
bf16[batch: 2][data: 3]
[
[0.3671875, 0.134765625, 0.049560546875],
[2.703125, 7.375, 20.0]
[0.367, 0.135, 0.0496],
[2.7, 7.38, 20.0]
]
>

Expand All @@ -171,15 +171,15 @@ defmodule Axon.Activations do
iex> Axon.Activations.gelu(Nx.tensor([-3.0, -2.0, -1.0, 0.0, 1.0, 2.0, 3.0], names: [:data]))
#Nx.Tensor<
f32[data: 7]
[-0.0040496885776519775, -0.04550027847290039, -0.15865525603294373, 0.0, 0.8413447141647339, 1.9544997215270996, 2.995950222015381]
[-0.0040496886, -0.04550028, -0.15865526, 0.0, 0.8413447, 1.9544997, 2.9959502]
>

iex> Axon.Activations.gelu(Nx.tensor([[-1.0, -2.0, -3.0], [1.0, 2.0, 3.0]], type: {:bf, 16}, names: [:batch, :data]))
#Nx.Tensor<
bf16[batch: 2][data: 3]
[
[-0.16015625, -0.046875, -0.005859375],
[0.83984375, 1.953125, 2.984375]
[-0.16, -0.0469, -0.00586],
[0.84, 1.95, 2.98]
]
>

Expand Down Expand Up @@ -207,15 +207,15 @@ defmodule Axon.Activations do
iex> Axon.Activations.hard_sigmoid(Nx.tensor([-3.0, -2.0, -1.0, 0.0, 1.0, 2.0, 3.0], names: [:data]))
#Nx.Tensor<
f32[data: 7]
[0.0, 0.0, 0.0, 0.20000000298023224, 0.4000000059604645, 0.6000000238418579, 0.800000011920929]
[0.0, 0.0, 0.0, 0.2, 0.4, 0.6, 0.8]
>

iex> Axon.Activations.hard_sigmoid(Nx.tensor([[-1.0, -2.0, -3.0], [1.0, 2.0, 3.0]], type: {:bf, 16}, names: [:batch, :data]))
#Nx.Tensor<
bf16[batch: 2][data: 3]
[
[0.0, 0.0, 0.0],
[0.3984375, 0.59765625, 0.796875]
[0.398, 0.598, 0.797]
]
>

Expand All @@ -242,15 +242,15 @@ defmodule Axon.Activations do
iex> Axon.Activations.hard_silu(Nx.tensor([-3.0, -2.0, -1.0, 0.0, 1.0, 2.0, 3.0], names: [:data]))
#Nx.Tensor<
f32[data: 7]
[-0.0, -0.0, -0.0, 0.0, 0.4000000059604645, 1.2000000476837158, 2.4000000953674316]
[-0.0, -0.0, -0.0, 0.0, 0.4, 1.2, 2.4]
>

iex> Axon.Activations.hard_silu(Nx.tensor([[-1.0, -2.0, -3.0], [1.0, 2.0, 3.0]], type: {:bf, 16}, names: [:batch, :data]))
#Nx.Tensor<
bf16[batch: 2][data: 3]
[
[-0.0, -0.0, -0.0],
[0.3984375, 1.1953125, 2.390625]
[0.398, 1.195, 2.39]
]
>

Expand Down Expand Up @@ -359,15 +359,15 @@ defmodule Axon.Activations do
iex> Axon.Activations.log_sumexp(Nx.tensor([-3.0, -2.0, -1.0, 0.0, 1.0, 2.0, 3.0], names: [:data]))
#Nx.Tensor<
f32[data: 1]
[3.4577627182006836]
[3.4577627]
>

iex> Axon.Activations.log_sumexp(Nx.tensor([[-1.0, -2.0, -3.0], [1.0, 2.0, 3.0]], type: {:bf, 16}, names: [:batch, :data]))
#Nx.Tensor<
bf16[batch: 2][data: 1]
[
[-0.59375],
[3.390625]
[-0.594],
[3.39]
]
>

Expand Down Expand Up @@ -417,15 +417,15 @@ defmodule Axon.Activations do
iex> Axon.Activations.log_sigmoid(Nx.tensor([-3.0, -2.0, -1.0, 0.0, 1.0, 2.0, 3.0], type: {:f, 32}, names: [:data]))
#Nx.Tensor<
f32[data: 7]
[-3.0485873222351074, -2.1269280910491943, -1.3132617473602295, -0.6931471824645996, -0.3132616877555847, -0.12692801654338837, -0.04858734831213951]
[-3.0485873, -2.126928, -1.3132617, -0.6931472, -0.3132617, -0.12692802, -0.04858735]
>

iex> Axon.Activations.log_sigmoid(Nx.tensor([[-1.0, -2.0, -3.0], [1.0, 2.0, 3.0]], type: {:bf, 16}, names: [:batch, :data]))
#Nx.Tensor<
bf16[batch: 2][data: 3]
[
[-1.3125, -2.125, -3.046875],
[-0.3125, -0.1259765625, -0.04833984375]
[-1.31, -2.12, -3.05],
[-0.312, -0.126, -0.0483]
]
>

Expand All @@ -442,15 +442,15 @@ defmodule Axon.Activations do
iex> Axon.Activations.log_softmax(Nx.tensor([-3.0, -2.0, -1.0, 0.0, 1.0, 2.0, 3.0], type: {:f, 32}, names: [:data]))
#Nx.Tensor<
f32[data: 7]
[-6.457762718200684, -5.457762718200684, -4.457762718200684, -3.4577627182006836, -2.4577627182006836, -1.4577628374099731, -0.45776283740997314]
[-6.4577627, -5.4577627, -4.4577627, -3.4577627, -2.4577627, -1.4577628, -0.45776284]
>

iex> Axon.Activations.log_softmax(Nx.tensor([[-1.0, -2.0, -3.0], [1.0, 2.0, 3.0]], type: {:bf, 16}, names: [:batch, :data]))
#Nx.Tensor<
bf16[batch: 2][data: 3]
[
[-0.404296875, -1.3984375, -2.390625],
[-2.390625, -1.3984375, -0.404296875]
[-0.404, -1.4, -2.39],
[-2.39, -1.4, -0.404]
]
>
"""
Expand All @@ -477,15 +477,15 @@ defmodule Axon.Activations do
iex> Axon.Activations.mish(Nx.tensor([-3.0, -2.0, -1.0, 0.0, 1.0, 2.0, 3.0], type: {:f, 32}, names: [:data]))
#Nx.Tensor<
f32[data: 7]
[-0.14564745128154755, -0.2525014877319336, -0.30340147018432617, 0.0, 0.8650984168052673, 1.9439589977264404, 2.98653507232666]
[-0.14564745, -0.2525015, -0.30340147, 0.0, 0.8650984, 1.943959, 2.986535]
>

iex> Axon.Activations.mish(Nx.tensor([[-1.0, -2.0, -3.0], [1.0, 2.0, 3.0]], type: {:bf, 16}, names: [:batch, :data]))
#Nx.Tensor<
bf16[batch: 2][data: 3]
[
[-0.30078125, -0.25, -0.1435546875],
[0.86328125, 1.9375, 2.96875]
[-0.3, -0.25, -0.144],
[0.863, 1.94, 2.97]
]
>
"""
Expand Down Expand Up @@ -572,15 +572,15 @@ defmodule Axon.Activations do
iex> Axon.Activations.sigmoid(Nx.tensor([-3.0, -2.0, -1.0, 0.0, 1.0, 2.0, 3.0], names: [:data]))
#Nx.Tensor<
f32[data: 7]
[0.04742587357759476, 0.11920291930437088, 0.2689414322376251, 0.5, 0.7310585975646973, 0.8807970881462097, 0.9525741338729858]
[0.047425874, 0.11920292, 0.26894143, 0.5, 0.7310586, 0.8807971, 0.95257413]
>

iex> Axon.Activations.sigmoid(Nx.tensor([[-1.0, -2.0, -3.0], [1.0, 2.0, 3.0]], type: {:bf, 16}, names: [:batch, :data]))
#Nx.Tensor<
bf16[batch: 2][data: 3]
[
[0.267578125, 0.119140625, 0.04736328125],
[0.73046875, 0.87890625, 0.94921875]
[0.268, 0.119, 0.0474],
[0.73, 0.88, 0.95]
]
>

Expand All @@ -601,15 +601,15 @@ defmodule Axon.Activations do
iex> Axon.Activations.silu(Nx.tensor([-3.0, -2.0, -1.0, 0.0, 1.0, 2.0, 3.0], names: [:data]))
#Nx.Tensor<
f32[data: 7]
[-0.14227762818336487, -0.23840583860874176, -0.2689414322376251, 0.0, 0.7310585975646973, 1.7615941762924194, 2.857722282409668]
[-0.14227763, -0.23840584, -0.26894143, 0.0, 0.7310586, 1.7615942, 2.8577223]
>

iex> Axon.Activations.silu(Nx.tensor([[-1.0, -2.0, -3.0], [1.0, 2.0, 3.0]], type: {:bf, 16}, names: [:batch, :data]))
#Nx.Tensor<
bf16[batch: 2][data: 3]
[
[-0.267578125, -0.23828125, -0.1416015625],
[0.73046875, 1.7578125, 2.84375]
[-0.268, -0.238, -0.142],
[0.73, 1.76, 2.84]
]
>

Expand Down Expand Up @@ -638,15 +638,15 @@ defmodule Axon.Activations do
iex> Axon.Activations.selu(Nx.tensor([-3.0, -2.0, -1.0, 0.0, 1.0, 2.0, 3.0], names: [:data]))
#Nx.Tensor<
f32[data: 7]
[-1.670568823814392, -1.5201665163040161, -1.1113307476043701, 0.0, 1.0507010221481323, 2.1014020442962646, 3.1521029472351074]
[-1.6705688, -1.5201665, -1.1113307, 0.0, 1.050701, 2.101402, 3.152103]
>

iex> Axon.Activations.selu(Nx.tensor([[-1.0, -2.0, -3.0], [1.0, 2.0, 3.0]], type: {:bf, 16}, names: [:batch, :data]))
#Nx.Tensor<
bf16[batch: 2][data: 3]
[
[-1.09375, -1.5, -1.65625],
[1.046875, 2.09375, 3.140625]
[-1.09, -1.5, -1.66],
[1.05, 2.1, 3.14]
]
>

Expand Down Expand Up @@ -686,16 +686,16 @@ defmodule Axon.Activations do
#Nx.Tensor<
f32[batch: 1][data: 7]
[
[0.0015683004166930914, 0.004263082519173622, 0.011588259600102901, 0.03150015324354172, 0.08562629669904709, 0.23275642096996307, 0.6326975226402283]
[0.0015683004, 0.0042630825, 0.01158826, 0.031500153, 0.0856263, 0.23275642, 0.6326975]
]
>

iex> Axon.Activations.softmax(Nx.tensor([[-1.0, -2.0, -3.0], [1.0, 2.0, 3.0]], type: {:bf, 16}, names: [:batch, :data]))
#Nx.Tensor<
bf16[batch: 2][data: 3]
[
[0.6640625, 0.2431640625, 0.08935546875],
[0.08935546875, 0.2431640625, 0.6640625]
[0.664, 0.243, 0.0894],
[0.0894, 0.243, 0.664]
]
>

Expand Down Expand Up @@ -746,15 +746,15 @@ defmodule Axon.Activations do
iex> Axon.Activations.softplus(Nx.tensor([-3.0, -2.0, -1.0, 0.0, 1.0, 2.0, 3.0], names: [:data]))
#Nx.Tensor<
f32[data: 7]
[0.04858734831213951, 0.12692801654338837, 0.3132616877555847, 0.6931471824645996, 1.3132617473602295, 2.1269280910491943, 3.0485873222351074]
[0.04858735, 0.12692802, 0.3132617, 0.6931472, 1.3132617, 2.126928, 3.0485873]
>

iex> Axon.Activations.softplus(Nx.tensor([[-1.0, -2.0, -3.0], [1.0, 2.0, 3.0]], type: {:bf, 16}, names: [:batch, :data]))
#Nx.Tensor<
bf16[batch: 2][data: 3]
[
[0.3125, 0.1259765625, 0.04833984375],
[1.3125, 2.125, 3.046875]
[0.312, 0.126, 0.0483],
[1.31, 2.12, 3.05]
]
>

Expand All @@ -780,15 +780,15 @@ defmodule Axon.Activations do
iex> Axon.Activations.softsign(Nx.tensor([-3.0, -2.0, -1.0, 0.0, 1.0, 2.0, 3.0], names: [:data]))
#Nx.Tensor<
f32[data: 7]
[-0.75, -0.6666666865348816, -0.5, 0.0, 0.5, 0.6666666865348816, 0.75]
[-0.75, -0.6666667, -0.5, 0.0, 0.5, 0.6666667, 0.75]
>

iex> Axon.Activations.softsign(Nx.tensor([[-1.0, -2.0, -3.0], [1.0, 2.0, 3.0]], type: {:bf, 16}, names: [:batch, :data]))
#Nx.Tensor<
bf16[batch: 2][data: 3]
[
[-0.5, -0.6640625, -0.75],
[0.5, 0.6640625, 0.75]
[-0.5, -0.664, -0.75],
[0.5, 0.664, 0.75]
]
>

Expand All @@ -811,15 +811,15 @@ defmodule Axon.Activations do
iex> Axon.Activations.tanh(Nx.tensor([-3.0, -2.0, -1.0, 0.0, 1.0, 2.0, 3.0], names: [:data]))
#Nx.Tensor<
f32[data: 7]
[-0.9950547814369202, -0.9640275835990906, -0.7615941762924194, 0.0, 0.7615941762924194, 0.9640275835990906, 0.9950547814369202]
[-0.9950548, -0.9640276, -0.7615942, 0.0, 0.7615942, 0.9640276, 0.9950548]
>

iex> Axon.Activations.tanh(Nx.tensor([[-1.0, -2.0, -3.0], [1.0, 2.0, 3.0]], type: {:bf, 16}, names: [:batch, :data]))
#Nx.Tensor<
bf16[batch: 2][data: 3]
[
[-0.7578125, -0.9609375, -0.9921875],
[0.7578125, 0.9609375, 0.9921875]
[-0.758, -0.96, -0.992],
[0.758, 0.96, 0.992]
]
>

Expand Down
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