Merge branch 'master' into valgrind

ankane · Nov 11, 2024 · 63efb2a · 63efb2a
2 parents e7c7f1e + 0f1832f
commit 63efb2a
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diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml
@@ -8,9 +8,9 @@ jobs:
       matrix:
         include:
           - ruby: 3.3
-            os: ubuntu-22.04
+            os: ubuntu-24.04
     env:
-      LIBTORCH_VERSION: 2.2.1
+      LIBTORCH_VERSION: 2.5.1
     steps:
       - uses: actions/checkout@v4
       - uses: ruby/setup-ruby@v1
@@ -28,6 +28,6 @@ jobs:
           cd ~
           wget -q -O libtorch.zip https://download.pytorch.org/libtorch/cpu/libtorch-cxx11-abi-shared-with-deps-$LIBTORCH_VERSION%2Bcpu.zip
           unzip -q libtorch.zip
-      - run: MAKE="make -j$(nproc)" bundle exec rake compile -- --with-torch-dir=$HOME/libtorch
+      - run: MAKE="make -j$(getconf _NPROCESSORS_ONLN)" bundle exec rake compile -- --with-torch-dir=$HOME/libtorch
       - run: sudo apt-get update && sudo apt-get install valgrind
       - run: bundle exec rake test:valgrind
diff --git a/CHANGELOG.md b/CHANGELOG.md
@@ -1,3 +1,30 @@
+## 0.18.1 (unreleased)
+
+- Improved `inspect` for `Device`
+- Fixed equality for `Device`
+- Fixed `index` method for `Device` when no index
+
+## 0.18.0 (2024-10-22)
+
+- Updated LibTorch to 2.5.0
+
+## 0.17.1 (2024-08-19)
+
+- Added `persistent` option to `register_buffer` method
+- Added `prefix` and `recurse` options to `named_buffers` method
+
+## 0.17.0 (2024-07-26)
+
+- Updated LibTorch to 2.4.0
+- Added `normalize` method
+- Added support for tensor indexing with arrays
+
+## 0.16.0 (2024-06-12)
+
+- Updated LibTorch to 2.3.0
+- Added `ELU` and `GELU` classes
+- Dropped support for Ruby < 3.1
+
 ## 0.15.0 (2024-02-28)
 
 - Updated LibTorch to 2.2.0

diff --git a/Gemfile b/Gemfile
@@ -7,6 +7,3 @@ gem "rake-compiler"
 gem "minitest", ">= 5"
 gem "numo-narray"
 gem "ruby_memcheck"
-
-# for examples
-gem "torchvision", ">= 0.2", require: false
diff --git a/README.md b/README.md
@@ -14,19 +14,28 @@ Check out:
 
 ## Installation
 
-First, [install LibTorch](#libtorch-installation). With Homebrew, it’s part of the PyTorch package:
+First, [download LibTorch](https://pytorch.org/get-started/locally/). For Mac arm64, use:
 
 ```sh
-brew install pytorch
+curl -L https://download.pytorch.org/libtorch/cpu/libtorch-macos-arm64-2.5.1.zip > libtorch.zip
+unzip -q libtorch.zip
 ```
 
-Add this line to your application’s Gemfile:
+For Linux x86-64, use the `cxx11 ABI` version. For other platforms, build LibTorch from source.
+
+Then run:
+
+```sh
+bundle config build.torch-rb --with-torch-dir=/path/to/libtorch
+```
+
+And add this line to your application’s Gemfile:
 
 ```ruby
 gem "torch-rb"
 ```
 
-It can take 5-10 minutes to compile the extension.
+It can take 5-10 minutes to compile the extension. Windows is not currently supported.
 
 ## Getting Started
 
@@ -398,31 +407,20 @@ Here’s a list of functions to create tensors (descriptions from the [C++ docs]
   Torch.zeros(3) # tensor([0, 0, 0])
   ```
 
-## LibTorch Installation
-
-[Download LibTorch](https://pytorch.org/) (for Linux, use the `cxx11 ABI` version). Then run:
-
-```sh
-bundle config build.torch-rb --with-torch-dir=/path/to/libtorch
-```
+## LibTorch Compatibility
 
 Here’s the list of compatible versions.
 
 Torch.rb | LibTorch
 --- | ---
+0.18.x | 2.5.x
+0.17.x | 2.4.x
+0.16.x | 2.3.x
 0.15.x | 2.2.x
 0.14.x | 2.1.x
 0.13.x | 2.0.x
 0.12.x | 1.13.x
 
-### Homebrew
-
-You can also use Homebrew.
-
-```sh
-brew install pytorch
-```
-
 ## Performance
 
 Deep learning is significantly faster on a GPU.

diff --git a/codegen/generate_functions.rb b/codegen/generate_functions.rb
@@ -155,10 +155,10 @@ def generate_attach_def(name, type, def_method)
     end
 
   ruby_name = "_#{ruby_name}" if ["size", "stride", "random!"].include?(ruby_name)
-  ruby_name = ruby_name.sub(/\Afft_/, "") if type == "fft"
-  ruby_name = ruby_name.sub(/\Alinalg_/, "") if type == "linalg"
-  ruby_name = ruby_name.sub(/\Aspecial_/, "") if type == "special"
-  ruby_name = ruby_name.sub(/\Asparse_/, "") if type == "sparse"
+  ruby_name = ruby_name.delete_prefix("fft_") if type == "fft"
+  ruby_name = ruby_name.delete_prefix("linalg_") if type == "linalg"
+  ruby_name = ruby_name.delete_prefix("special_") if type == "special"
+  ruby_name = ruby_name.delete_prefix("sparse_") if type == "sparse"
   ruby_name = name if name.start_with?("__")
 
   "rb_#{def_method}(m, \"#{ruby_name}\", #{full_name(name, type)}, -1);"
@@ -216,7 +216,7 @@ def add_dispatch(function, def_method)
     out_code = generate_dispatch(function["out"], def_method)
     out_index = function["out"].out_index
 
-    return "if (_r.isNone(#{out_index})) {
+    "if (_r.isNone(#{out_index})) {
     #{indent(base_code)}
   } else {
     #{indent(out_code)}
@@ -439,7 +439,7 @@ def generate_function_params(function, params, remove_self)
         else
           "#{func}Optional"
         end
-      end
+    end
 
     "_r.#{func}(#{param[:position]})"
   end