
iprog4u
Machine Learning in Elixir: Chapter 1 - Unable to train model (page 19)
I am really enjoying the book so far but came across an issue in the first chapter. When running:
trained_model_state =
model
|> Axon.Loop.trainer(:categorical_cross_entropy, :sgd)
|> Axon.Loop.metric(:accuracy)
|> Axon.Loop.run(data_stream, %{}, iterations: 500, epochs: 10)
Still too new to debug this but it appears an issue with expecting either an f32 or f64 and getting the other and/or passing parameter maps rather than using Axon.ModelState{}:
13:42:29.641 [warning] passing parameter map to initialization is deprecated, use %Axon.ModelState{} instead
Epoch: 0, Batch: 0, accuracy: 0.4750000 loss: 0.0000000
** (ArgumentError) argument at position 3 is not compatible with compiled function template.
%{i: #Nx.Tensor<
s32
>, model_state: #Inspect.Error<
got Protocol.UndefinedError with message:
"""
protocol Enumerable not implemented for type Nx.Defn.TemplateDiff (a struct). This protocol is implemented for the following type(s): Date.Range, Explorer.Series.Iterator, File.Stream, Function, GenEvent.Stream, HashDict, HashSet, IO.Stream, Kino.Control, Kino.Input, Kino.JS.Live, List, Map, MapSet, Range, Stream, Table.Mapper, Table.Zipper
Got value:
#Nx.Tensor<
f32[3]
>
"""
while inspecting:
%{
data: %{
"dense_0" => %{
"bias" => #Nx.Tensor<
f32[3]
>,
"kernel" => #Nx.Tensor<
f32[4][3]
>
}
},
state: %{},
__struct__: Axon.ModelState,
parameters: %{"dense_0" => ["bias", "kernel"]},
frozen_parameters: %{}
}
Stacktrace:
(elixir 1.18.3) lib/enum.ex:1: Enumerable.impl_for!/1
(elixir 1.18.3) lib/enum.ex:166: Enumerable.reduce/3
(elixir 1.18.3) lib/enum.ex:4515: Enum.reduce/3
(axon 0.7.0) lib/axon/model_state.ex:359: anonymous fn/2 in Inspect.Axon.ModelState.get_param_info/1
(stdlib 6.2.2.1) maps.erl:860: :maps.fold_1/4
(axon 0.7.0) lib/axon/model_state.ex:359: anonymous fn/2 in Inspect.Axon.ModelState.get_param_info/1
(stdlib 6.2.2.1) maps.erl:860: :maps.fold_1/4
(axon 0.7.0) lib/axon/model_state.ex:320: Inspect.Axon.ModelState.inspect/2
>, y_true: #Nx.Tensor<
u8[120][3]
>, y_pred: #Nx.Tensor<
f64[120][3]
>, loss:
<<<<< Expected <<<<<
#Nx.Tensor<
f32
>
==========
#Nx.Tensor<
f64
>
>>>>> Argument >>>>>
, optimizer_state: {%{scale: #Nx.Tensor<
f32
>}}, loss_scale_state: %{}}
(nx 0.10.0) lib/nx/defn.ex:342: anonymous fn/7 in Nx.Defn.compile_flatten/5
(nx 0.10.0) lib/nx/lazy_container.ex:73: anonymous fn/3 in Nx.LazyContainer.Map.traverse/3
(elixir 1.18.3) lib/enum.ex:1840: Enum."-map_reduce/3-lists^mapfoldl/2-0-"/3
(elixir 1.18.3) lib/enum.ex:1840: Enum."-map_reduce/3-lists^mapfoldl/2-0-"/3
(nx 0.10.0) lib/nx/lazy_container.ex:72: Nx.LazyContainer.Map.traverse/3
(nx 0.10.0) lib/nx/defn.ex:339: Nx.Defn.compile_flatten/5
(nx 0.10.0) lib/nx/defn.ex:331: anonymous fn/4 in Nx.Defn.compile/3
#cell:3r6bhsjthve53hp7:5: (file)
In my terminal running the livebook I get another warning:
[warning] passing parameter map to initialization is deprecated, use %Axon.ModelState{} instead
but I do not yet know how to do this. Please guide me in the right direction. Thank you.
Marked As Solved

iprog4u
Solution is found at:
https://devtalk.com/t/machine-learning-in-elixir-chapter-1-doesnt-work-with-axon-0-7-page-26/173984
Explicitly converting the training and test sets to :f32 corrects the issue and the simulation can run.
feature_columns = [
"sepal_length",
"sepal_width",
"petal_length",
"petal_width"
]
label_column = "species"
x_train = Nx.stack(train_df[feature_columns], axis: 1)
|> Nx.as_type(:f32)
y_train =
train_df
|> DF.pull(label_column)
|> Explorer.Series.to_list()
|> Enum.map(fn
"Iris-setosa" -> 0
"Iris-versicolor" -> 1
"Iris-virginica" -> 2
end)
|> Nx.tensor(type: :u8)
|> Nx.new_axis(-1)
|> Nx.equal(Nx.iota({1, 3}, axis: -1))
|> Nx.as_type(:f32)
x_test = Nx.stack(test_df[feature_columns], axis: 1)
|> Nx.as_type(:f32)
y_test =
test_df
|> DF.pull(label_column)
|> Explorer.Series.to_list()
|> Enum.map(fn
"Iris-setosa" -> 0
"Iris-versicolor" -> 1
"Iris-virginica" -> 2
end)
|> Nx.tensor(type: :u8)
|> Nx.new_axis(-1)
|> Nx.equal(Nx.iota({1, 3}, axis: -1))
|> Nx.as_type(:f32)
Popular Pragmatic Bookshelf topics

page 20: … protoc command…
I had to additionally run the following go get commands in order to be able to compile protobuf code using go...
New

Running the examples in chapter 5 c under pytest 5.4.1 causes an AttributeError: ‘module’ object has no attribute ‘config’.
In particula...
New

your book suggests to use Image.toByteData() to convert image to bytes, however I get the following error: "the getter ‘toByteData’ isn’t...
New

The following is cross-posted from the original Ray Tracer Challenge forum, from a post by garfieldnate. I’m cross-posting it so that the...
New

Title: Hands-On Rust (Chapter 11: prefab)
Just played a couple of amulet-less games. With a bit of debugging, I believe that your can_p...
New

Hi @Margaret ,
On page VII the book tells us the example and snippets will be all using Elixir version 1.11
But on page 3 almost the en...
New

I can’t setup the Rails source code. This happens in a working directory containing multiple (postgres) Rails apps.
With:
ruby-3.0.0
s...
New

In general, the book isn’t yet updated for Phoenix version 1.6. On page 18 of the book, the authors indicate that an auto generated of ro...
New

root_layout: {PentoWeb.LayoutView, :root},
This results in the following following error:
no “root” html template defined for PentoWeb...
New

Getting an error when installing the dependencies at the start of this chapter:
could not compile dependency :exla, "mix compile" failed...
New
Other popular topics

Hello Devtalk World!
Please let us know a little about who you are and where you’re from :nerd_face:
New

Reading something? Working on something? Planning something? Changing jobs even!?
If you’re up for sharing, please let us know what you’...
New

A thread that every forum needs!
Simply post a link to a track on YouTube (or SoundCloud or Vimeo amongst others!) on a separate line an...
New

Curious to know which languages and frameworks you’re all thinking about learning next :upside_down_face:
Perhaps if there’s enough peop...
New

Just done a fresh install of macOS Big Sur and on installing Erlang I am getting:
asdf install erlang 23.1.2
Configure failed.
checking ...
New

Tailwind CSS is an exciting new CSS framework that allows you to design your site by composing simple utility classes to create complex e...
New

In case anyone else is wondering why Ruby 3 doesn’t show when you do asdf list-all ruby :man_facepalming: do this first:
asdf plugin-upd...
New

API 4
Path:
/user/following/
Method:
GET
Description:
Returns the list of all names of people whom the user follows
Response
[
{ ...
New

Inside our android webview app, we are trying to paste the copied content from another app eg (notes) using navigator.clipboard.readtext ...
New

Author Spotlight:
Bruce Tate
@redrapids
Programming languages always emerge out of need, and if that’s not always true, they’re defin...
New
Categories:
Sub Categories:
Popular Portals
- /elixir
- /rust
- /ruby
- /wasm
- /erlang
- /phoenix
- /keyboards
- /rails
- /python
- /js
- /security
- /go
- /swift
- /vim
- /clojure
- /haskell
- /emacs
- /java
- /svelte
- /onivim
- /typescript
- /kotlin
- /c-plus-plus
- /crystal
- /tailwind
- /react
- /gleam
- /ocaml
- /elm
- /flutter
- /vscode
- /ash
- /html
- /opensuse
- /centos
- /php
- /deepseek
- /zig
- /scala
- /sublime-text
- /lisp
- /textmate
- /react-native
- /nixos
- /debian
- /agda
- /kubuntu
- /arch-linux
- /django
- /ubuntu
- /revery
- /deno
- /manjaro
- /spring
- /nodejs
- /diversity
- /lua
- /julia
- /slackware
- /c