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Merged
skryl merged 3 commits into from
Feb 20, 2026
Merged

Migrate to Ruby 4: rename it variables to iter to avoid keyword conflict #4

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67e8547
Migrate to Ruby 4: rename `it` variables to `iter` to avoid keyword c…
claude Feb 20, 2026
4592c8b
Add CI status badge to README
claude Feb 20, 2026
af53d70
Fix CI: trigger on all pull requests, not just those targeting main
claude Feb 20, 2026
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3 changes: 0 additions & 3 deletions .github/workflows/ci.yml
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Original file line number Diff line number Diff line change
Expand Up @@ -6,9 +6,6 @@ on:
- main
- master
pull_request:
branches:
- main
- master

jobs:
test:
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2 changes: 2 additions & 0 deletions README.md
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@@ -1,5 +1,7 @@
# MLX Ruby Examples

[![CI](https://github.com/skryl/mlx-ruby-examples/actions/workflows/ci.yml/badge.svg)](https://github.com/skryl/mlx-ruby-examples/actions/workflows/ci.yml)

Ruby/MLX example ports that depend on Apple Metal when building the `mlx` gem.

## Prerequisites (macOS)
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14 changes: 7 additions & 7 deletions lora/lora.rb
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Original file line number Diff line number Diff line change
Expand Up @@ -155,7 +155,7 @@ def train(model, train_set, valid_set, optimizer, tokenizer, options)
seed: options[:seed]
)

options[:iters].times do |it|
options[:iters].times do |iter|
inputs, targets, lengths = batches.next
(lvalue, toks), grad = loss_value_and_grad.call(inputs, targets, lengths)
optimizer.update(model, grad)
Expand All @@ -164,12 +164,12 @@ def train(model, train_set, valid_set, optimizer, tokenizer, options)
losses << lvalue.item.to_f
n_tokens += toks.item.to_f

if ((it + 1) % options[:steps_per_report]).zero?
if ((iter + 1) % options[:steps_per_report]).zero?
stop = Process.clock_gettime(Process::CLOCK_MONOTONIC)
train_loss = losses.sum / [losses.length, 1].max.to_f
puts format(
"Iter %d: Train loss %.3f, It/sec %.3f, Tokens/sec %.3f",
it + 1,
iter + 1,
train_loss,
options[:steps_per_report] / [stop - start, 1e-9].max,
n_tokens / [stop - start, 1e-9].max
Expand All @@ -179,7 +179,7 @@ def train(model, train_set, valid_set, optimizer, tokenizer, options)
start = Process.clock_gettime(Process::CLOCK_MONOTONIC)
end

if it.zero? || ((it + 1) % options[:steps_per_eval]).zero?
if iter.zero? || ((iter + 1) % options[:steps_per_eval]).zero?
eval_start = Process.clock_gettime(Process::CLOCK_MONOTONIC)
val_loss = evaluate(
model,
Expand All @@ -191,16 +191,16 @@ def train(model, train_set, valid_set, optimizer, tokenizer, options)
)
puts format(
"Iter %d: Val loss %.3f, Val took %.3fs",
it + 1,
iter + 1,
val_loss,
Process.clock_gettime(Process::CLOCK_MONOTONIC) - eval_start
)
start = Process.clock_gettime(Process::CLOCK_MONOTONIC)
end

if ((it + 1) % options[:save_every]).zero?
if ((iter + 1) % options[:save_every]).zero?
save_trainable_adapters(options[:adapter_file], model)
puts "Iter #{it + 1}: Saved adapter weights to #{options[:adapter_file]}."
puts "Iter #{iter + 1}: Saved adapter weights to #{options[:adapter_file]}."
end
end
end
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14 changes: 7 additions & 7 deletions no_dsl/lora/lora.rb
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Original file line number Diff line number Diff line change
Expand Up @@ -155,7 +155,7 @@ def train(model, train_set, valid_set, optimizer, tokenizer, options)
seed: options[:seed]
)

options[:iters].times do |it|
options[:iters].times do |iter|
inputs, targets, lengths = batches.next
(lvalue, toks), grad = loss_value_and_grad.call(inputs, targets, lengths)
optimizer.update(model, grad)
Expand All @@ -164,12 +164,12 @@ def train(model, train_set, valid_set, optimizer, tokenizer, options)
losses << lvalue.item.to_f
n_tokens += toks.item.to_f

if ((it + 1) % options[:steps_per_report]).zero?
if ((iter + 1) % options[:steps_per_report]).zero?
stop = Process.clock_gettime(Process::CLOCK_MONOTONIC)
train_loss = losses.sum / [losses.length, 1].max.to_f
puts format(
"Iter %d: Train loss %.3f, It/sec %.3f, Tokens/sec %.3f",
it + 1,
iter + 1,
train_loss,
options[:steps_per_report] / [stop - start, 1e-9].max,
n_tokens / [stop - start, 1e-9].max
Expand All @@ -179,7 +179,7 @@ def train(model, train_set, valid_set, optimizer, tokenizer, options)
start = Process.clock_gettime(Process::CLOCK_MONOTONIC)
end

if it.zero? || ((it + 1) % options[:steps_per_eval]).zero?
if iter.zero? || ((iter + 1) % options[:steps_per_eval]).zero?
eval_start = Process.clock_gettime(Process::CLOCK_MONOTONIC)
val_loss = evaluate(
model,
Expand All @@ -191,16 +191,16 @@ def train(model, train_set, valid_set, optimizer, tokenizer, options)
)
puts format(
"Iter %d: Val loss %.3f, Val took %.3fs",
it + 1,
iter + 1,
val_loss,
Process.clock_gettime(Process::CLOCK_MONOTONIC) - eval_start
)
start = Process.clock_gettime(Process::CLOCK_MONOTONIC)
end

if ((it + 1) % options[:save_every]).zero?
if ((iter + 1) % options[:save_every]).zero?
save_trainable_adapters(options[:adapter_file], model)
puts "Iter #{it + 1}: Saved adapter weights to #{options[:adapter_file]}."
puts "Iter #{iter + 1}: Saved adapter weights to #{options[:adapter_file]}."
end
end
end
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6 changes: 3 additions & 3 deletions no_dsl/normalizing_flow/main.rb
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Expand Up @@ -74,19 +74,19 @@ def run(options)
rng = Random.new(options[:seed] + 1)
all_indices = (0...x.shape[0]).to_a
tic = Process.clock_gettime(Process::CLOCK_MONOTONIC)
options[:n_steps].times do |it|
options[:n_steps].times do |iter|
ids = all_indices.sample(options[:n_batch], random: rng)
batch = MLX::Core.take(x, MLX::Core.array(ids, MLX::Core.int32), 0)
loss, grads = loss_and_grad_fn.call(batch)
optimizer.update(model, grads)
MLX::Core.eval(loss, model.parameters, optimizer.state)

next unless ((it + 1) % options[:report_every]).zero?
next unless ((iter + 1) % options[:report_every]).zero?

toc = Process.clock_gettime(Process::CLOCK_MONOTONIC)
puts format(
"Step %d: Loss %.4f | It/sec %.2f",
it + 1,
iter + 1,
loss.item.to_f,
options[:report_every] / [toc - tic, 1e-9].max
)
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12 changes: 6 additions & 6 deletions no_dsl/transformer_lm/main.rb
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Original file line number Diff line number Diff line change
Expand Up @@ -146,11 +146,11 @@ def run(options)

losses = []
tic = Process.clock_gettime(Process::CLOCK_MONOTONIC)
options[:num_iters].times do |it|
options[:num_iters].times do |iter|
warmup = if options[:lr_warmup] <= 0
1.0
else
[1.0, it.to_f / options[:lr_warmup].to_f].min
[1.0, iter.to_f / options[:lr_warmup].to_f].min
end
optimizer.learning_rate = warmup * options[:learning_rate]

Expand All @@ -160,20 +160,20 @@ def run(options)
MLX::Core.eval(loss, model.parameters, optimizer.state)
losses << loss.item.to_f

if ((it + 1) % options[:steps_per_report]).zero?
if ((iter + 1) % options[:steps_per_report]).zero?
toc = Process.clock_gettime(Process::CLOCK_MONOTONIC)
train_loss = losses.sum / [losses.length, 1].max.to_f
puts format(
"Iter %d: Train loss %.3f, It/sec %.3f",
it + 1,
iter + 1,
train_loss,
options[:steps_per_report] / [toc - tic, 1e-9].max
)
losses = []
tic = Process.clock_gettime(Process::CLOCK_MONOTONIC)
end

next unless ((it + 1) % options[:steps_per_eval]).zero?
next unless ((iter + 1) % options[:steps_per_eval]).zero?

eval_tic = Process.clock_gettime(Process::CLOCK_MONOTONIC)
val_loss = eval_fn(
Expand All @@ -186,7 +186,7 @@ def run(options)
val_ppl = Math.exp(val_loss)
puts format(
"Iter %d: Val loss %.3f, Val ppl %.3f, Val took %.3fs",
it + 1,
iter + 1,
val_loss,
val_ppl,
eval_toc - eval_tic
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14 changes: 7 additions & 7 deletions transformer_lm/main.rb
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Expand Up @@ -153,35 +153,35 @@ def run(options)
end

trainer.before_epoch do |ctx|
it = ctx.fetch(:epoch).to_i
iter = ctx.fetch(:epoch).to_i
warmup = if options[:lr_warmup] <= 0
1.0
else
[1.0, it.to_f / options[:lr_warmup].to_f].min
[1.0, iter.to_f / options[:lr_warmup].to_f].min
end
optimizer.learning_rate = warmup * options[:learning_rate]
end

losses = []
tic = Process.clock_gettime(Process::CLOCK_MONOTONIC)
trainer.after_epoch do |ctx|
it = ctx.fetch(:epoch).to_i + 1
iter = ctx.fetch(:epoch).to_i + 1
losses << ctx.fetch(:epoch_loss).to_f

if (it % options[:steps_per_report]).zero?
if (iter % options[:steps_per_report]).zero?
toc = Process.clock_gettime(Process::CLOCK_MONOTONIC)
train_loss = losses.sum / [losses.length, 1].max.to_f
puts format(
"Iter %d: Train loss %.3f, It/sec %.3f",
it,
iter,
train_loss,
options[:steps_per_report] / [toc - tic, 1e-9].max
)
losses = []
tic = Process.clock_gettime(Process::CLOCK_MONOTONIC)
end

next unless (it % options[:steps_per_eval]).zero?
next unless (iter % options[:steps_per_eval]).zero?

eval_tic = Process.clock_gettime(Process::CLOCK_MONOTONIC)
val_loss = eval_fn(
Expand All @@ -194,7 +194,7 @@ def run(options)
val_ppl = Math.exp(val_loss)
puts format(
"Iter %d: Val loss %.3f, Val ppl %.3f, Val took %.3fs",
it,
iter,
val_loss,
val_ppl,
eval_toc - eval_tic
Expand Down