Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

Fix Fashion MNIST autoencoder example #439

Merged
merged 6 commits into from
Jan 16, 2023
Merged

Fix Fashion MNIST autoencoder example #439

Changes from all commits
Commits
Show all changes
6 commits
Select commit Hold shift + click to select a range
f32047f
Update dependencies in Fashion MNIST autoencoder
nskins Jan 4, 2023
513bc1f
Include placeholder for dynamic batch sizes
nskins Jan 4, 2023
e9abcce
Fix spelling of MNIST in Fashion MNIST autoencoder module name
nskins Jan 4, 2023
197a499
Remove unused alias for Axon.Loop.State
nskins Jan 4, 2023
fb1926e
Update deprecated Nx function: to_batched_list/3 -> to_batched/3
nskins Jan 4, 2023
e4702a9
Grab sample image with a stream-compatible function
nskins Jan 4, 2023
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
19 changes: 9 additions & 10 deletions examples/generative/fashionmnist_autoencoder.exs
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -1,16 +1,15 @@
Mix.install([
{:axon, "~> 0.1.0"},
{:exla, "~> 0.2.2"},
{:nx, "~> 0.2.1"},
{:scidata, "~> 0.1.6"}
{:axon, "~> 0.3.0"},
{:exla, "~> 0.4.1"},
{:nx, "~> 0.4.1"},
{:scidata, "~> 0.1.9"}
])

# Configure default platform with accelerator precedence as tpu > cuda > rocm > host
EXLA.set_as_nx_default([:tpu, :cuda, :rocm, :host])

defmodule Fashionmist do
defmodule FashionMNIST do
require Axon
alias Axon.Loop.State

defmodule Autoencoder do
defp encoder(x, latent_dim) do
Expand All @@ -22,7 +21,7 @@ defmodule Fashionmist do
defp decoder(x) do
x
|> Axon.dense(784, activation: :sigmoid)
|> Axon.reshape({1, 28, 28})
|> Axon.reshape({:batch, 1, 28, 28})
end

def build_model(input_shape, latent_dim) do
Expand All @@ -37,7 +36,7 @@ defmodule Fashionmist do
|> Nx.from_binary(type)
|> Nx.reshape({elem(shape, 0), 1, 28, 28})
|> Nx.divide(255.0)
|> Nx.to_batched_list(32)
|> Nx.to_batched(32)
end

defp train_model(model, train_images, epochs) do
Expand All @@ -58,7 +57,7 @@ defmodule Fashionmist do

sample_image =
train_images
|> hd()
|> Enum.fetch!(0)
|> Nx.slice_along_axis(0, 1)
|> Nx.reshape({1, 1, 28, 28})

Expand All @@ -71,4 +70,4 @@ defmodule Fashionmist do
end
end

Fashionmist.run()
FashionMNIST.run()