From 03365e4de76cc5c442fba5bc6b50b2363619df62 Mon Sep 17 00:00:00 2001
From: Jacob Gordon <jacob.gordon@amd.com>
Date: Mon, 23 Dec 2024 20:04:42 +0000
Subject: [PATCH 1/5] style(docs/development.md): ensures fenced code blocks
 are surrounded by blank lines

- enforced by markdown linter
---
 docs/development.md | 23 +++++++++++++++++++++++
 1 file changed, 23 insertions(+)

diff --git a/docs/development.md b/docs/development.md
index 61c60a646a5c..717e9fd9e4f2 100644
--- a/docs/development.md
+++ b/docs/development.md
@@ -139,6 +139,7 @@ Be aware that the installed version of LLVM needs in general to match the commit
 ### Build commands
 
 After either cmake run (in-tree/out-of-tree), use one of the following commands to build the project:
+
 ```shell
 # Build just torch-mlir (not all of LLVM)
 cmake --build build --target tools/torch-mlir/all
@@ -173,6 +174,7 @@ To test the MLIR output to torch dialect, you can use `test/python/fx_importer/b
 
 Make sure you have activated the virtualenv and set the `PYTHONPATH` above
 (if running on Windows, modify the environment variable as shown above):
+
 ```shell
 source mlir_venv/bin/activate
 export PYTHONPATH=`pwd`/build/tools/torch-mlir/python_packages/torch_mlir:`pwd`/test/python/fx_importer
@@ -187,6 +189,7 @@ This path doesn't give access to the current generation work that is being drive
 and may lead to errors.
 
 Same as above, but with different python path and example:
+
 ```shell
 export PYTHONPATH=`pwd`/build/tools/torch-mlir/python_packages/torch_mlir:`pwd`/projects/pt1/examples
 python projects/pt1/examples/torchscript_resnet18_all_output_types.py
@@ -197,6 +200,7 @@ This will display the Resnet18 network example in three dialects: TORCH, LINALG
 The main functionality is on `torch_mlir.torchscript.compile()`'s `output_type`.
 
 Ex:
+
 ```python
 module = torch_mlir.torchscript.compile(resnet18, torch.ones(1, 3, 224, 224), output_type="torch")
 ```
@@ -206,6 +210,7 @@ module = torch_mlir.torchscript.compile(resnet18, torch.ones(1, 3, 224, 224), ou
 ## Jupyter
 
 Jupyter notebook:
+
 ```shell
 python -m ipykernel install --user --name=torch-mlir --env PYTHONPATH "$PYTHONPATH"
 # Open in jupyter, and then navigate to
@@ -237,17 +242,21 @@ manually `source`'d in a shell.
 Torch-MLIR can also be built using Bazel (apart from the official CMake build) for users that depend on Bazel in their workflows. To build `torch-mlir-opt` using Bazel, follow these steps:
 
 1. Launch an interactive docker container with the required deps installed:
+
 ```shell
 ./utils/bazel/docker/run_docker.sh
 ```
 
 2. Build torch-mlir:
+
 ```shell
 bazel build @torch-mlir//:torch-mlir-opt
 ```
+
 The built binary should be at `bazel-bin/external/torch-mlir/torch-mlir-opt`.
 
 3. Test torch-mlir (lit test only):
+
 ```shell
 bazel test @torch-mlir//test/...
 ```
@@ -255,6 +264,7 @@ bazel test @torch-mlir//test/...
 We welcome patches to torch-mlir's Bazel build. If you do contribute,
 please complete your PR with an invocation of buildifier to ensure
 the BUILD files are formatted consistently:
+
 ```shell
 bazel run @torch-mlir//:buildifier
 ```
@@ -287,6 +297,7 @@ TM_PACKAGES="in-tree" ./build_tools/python_deploy/build_linux_packages.sh
 ### Out-of-Tree builds
 
 Build LLVM/MLIR first and then build Torch-MLIR referencing that build
+
 ```shell
 TM_PACKAGES="out-of-tree" ./build_tools/python_deploy/build_linux_packages.sh
 ```
@@ -339,38 +350,48 @@ The following additional environmental variables can be used to customize your d
 
 * Custom Release Docker image:
   Defaults to `stellaraccident/manylinux2014_x86_64-bazel-5.1.0:latest`
+
 ```shell
   TM_RELEASE_DOCKER_IMAGE="stellaraccident/manylinux2014_x86_64-bazel-5.1.0:latest"
 ```
+
 * Custom CI Docker image:
   Defaults to `powderluv/torch-mlir-ci:latest`. This assumes an Ubuntu LTS like image. You can build your own with `./build_tools/docker/Dockerfile`
+
 ```shell
   TM_CI_DOCKER_IMAGE="powderluv/torch-mlir-ci:latest"
 ```
 
 * Custom Python Versions for Release builds:
   Version of Python to use in Release builds. Ignored in CIs. Defaults to `cp39-cp39 cp310-cp310 cp312-cp312`
+
 ```shell
   TM_PYTHON_VERSIONS="cp39-cp39 cp310-cp310 cp312-cp312"
 ```
 
 * Location to store Release build wheels
+
 ```shell
   TM_OUTPUT_DIR="./build_tools/python_deploy/wheelhouse"
 ```
 
 * What "packages" to build:
   Defaults to torch-mlir. Options are `torch-mlir out-of-tree in-tree`
+
 ```shell
   TM_PACKAGES="torch-mlir out-of-tree in-tree"
 ```
+
 * Use pre-built Pytorch:
   Defaults to using pre-built Pytorch. Setting it to `OFF` builds from source
+
 ```shell
   TM_USE_PYTORCH_BINARY="OFF"
 ```
+
 * Skip running tests
   Skip running tests if you want quick build only iteration. Default set to `OFF`
+
 ```shell
   TM_SKIP_TESTS="OFF"
 ```
@@ -389,6 +410,7 @@ CMAKE_GENERATOR=Ninja python setup.py bdist_wheel
 
 To package a completed CMake build directory,
 you can use the `TORCH_MLIR_CMAKE_BUILD_DIR` and `TORCH_MLIR_CMAKE_ALREADY_BUILT` environment variables:
+
 ```shell
 TORCH_MLIR_CMAKE_BUILD_DIR=build/ TORCH_MLIR_CMAKE_ALREADY_BUILT=1 python setup.py bdist_wheel
 ```
@@ -490,6 +512,7 @@ Most of the unit tests use the [`FileCheck` tool](https://llvm.org/docs/CommandG
 # PyTorch source builds and custom PyTorch versions
 
 Torch-MLIR by default builds with the latest nightly PyTorch version. This can be toggled to build from latest PyTorch source with
+
 ```
 -DTORCH_MLIR_USE_INSTALLED_PYTORCH=OFF
 -DTORCH_MLIR_SRC_PYTORCH_REPO=vivekkhandelwal1/pytorch # Optional. Github path. Defaults to pytorch/pytorch

From e435a2254eb5223774254592ad6fa1c8dca74e21 Mon Sep 17 00:00:00 2001
From: Jacob Gordon <jacob.gordon@amd.com>
Date: Tue, 17 Dec 2024 17:37:41 +0000
Subject: [PATCH 2/5] docs(development.md): clarifies header structure

---
 docs/development.md | 28 ++++++++++++++++------------
 1 file changed, 16 insertions(+), 12 deletions(-)

diff --git a/docs/development.md b/docs/development.md
index 717e9fd9e4f2..a3e20fbacc33 100644
--- a/docs/development.md
+++ b/docs/development.md
@@ -1,4 +1,4 @@
-# Checkout and build from source
+# Environment
 
 ## Check out the code
 
@@ -31,7 +31,6 @@ it with the following `apt` command on Ubuntu/Debian.
 sudo apt install python3-dev
 ```
 
-
 ## (Optional) Set up pre-commit
 
 This project uses [pre-commit](https://pre-commit.com/) in its CI. You can
@@ -45,15 +44,21 @@ pip install pre-commit
 pre-commit install
 ```
 
-## CMake Build
+# Building
+
+## With CMake
+
+### Configure for Building...
 
 Two setups are possible to build: in-tree and out-of-tree. The in-tree setup is the most straightforward, as it will build LLVM dependencies as well.
 
-### Building torch-mlir in-tree
+#### ...with LLVM "in-tree" using...
 
-The following command generates configuration files to build the project *in-tree*, that is, using llvm/llvm-project as the main build. This will build LLVM as well as torch-mlir and its subprojects.  On Windows, use the "Developer PowerShell for Visual Studio" to ensure that the compiler and linker binaries are in the `PATH` variable.
+The following commands generate configuration files to build the project *in-tree*, that is, using llvm/llvm-project as the main build. This will build LLVM as well as torch-mlir and its subprojects.  On Windows, use the "Developer PowerShell for Visual Studio" to ensure that the compiler and linker binaries are in the `PATH` variable.
 
-This requires `lld`, `clang`, `ccache`, and other dependencies for building `libtorch` / `PyTorch` wheels from source. If you run into issues because of these, try the [simplified build command](#simplified-build).
+##### ...Base + Optimization Options
+
+This requires `lld`, `clang`, `ccache`, and other dependencies for building `libtorch` / `PyTorch` wheels from source. If you run into issues because of these, try the [simplified build command](#base-options).
 
 ```shell
 cmake -GNinja -Bbuild \
@@ -85,7 +90,7 @@ cmake -GNinja -Bbuild \
   -DLIBTORCH_VARIANT=shared
 ```
 
-# Simplified build
+##### ...Base Options
 
 If you're running into issues with the above build command, consider using the following:
 
@@ -101,7 +106,7 @@ cmake -GNinja -Bbuild \
   externals/llvm-project/llvm
 ```
 
-#### Flags to enable MLIR debugging:
+#### Options to enable MLIR debugging
 
 * Enabling `--debug` and `--debug-only` flags (see [MLIR docs](https://mlir.llvm.org/getting_started/Debugging/)) for the `torch-mlir-opt` tool
 ```shell
@@ -109,7 +114,7 @@ cmake -GNinja -Bbuild \
   -DLLVM_ENABLE_ASSERTIONS=ON \
 ```
 
-#### Flags to run end-to-end tests:
+#### Options to run end-to-end tests
 
 Running the end-to-end execution tests locally requires enabling the native PyTorch extension features and the JIT IR importer, which depends on the
 former and defaults to `ON` if not changed:
@@ -118,7 +123,7 @@ former and defaults to `ON` if not changed:
   -DTORCH_MLIR_ENABLE_JIT_IR_IMPORTER=ON \
 ```
 
-### Building against a pre-built LLVM
+#### ...with LLVM "out-of-tree"
 
 If you have built llvm-project separately in the directory `$LLVM_INSTALL_DIR`, you can also build the project *out-of-tree* using the following command as template:
 ```shell
@@ -135,8 +140,7 @@ The same QoL CMake flags can be used to enable clang, ccache, and lld. Be sure t
 
 Be aware that the installed version of LLVM needs in general to match the committed version in `externals/llvm-project`. Using a different version may or may not work.
 
-
-### Build commands
+### Initiate Build
 
 After either cmake run (in-tree/out-of-tree), use one of the following commands to build the project:
 

From 6c707ee100f340d4691ad6f5ee76368bd291fd45 Mon Sep 17 00:00:00 2001
From: Jacob Gordon <jacob.gordon@amd.com>
Date: Tue, 25 Feb 2025 14:23:59 +0000
Subject: [PATCH 3/5] docs(development.md): adds proper <h1> title

---
 docs/development.md | 80 +++++++++++++++++++++++----------------------
 1 file changed, 41 insertions(+), 39 deletions(-)

diff --git a/docs/development.md b/docs/development.md
index a3e20fbacc33..17ddd88f4c0e 100644
--- a/docs/development.md
+++ b/docs/development.md
@@ -1,6 +1,8 @@
-# Environment
+# Development Guide
 
-## Check out the code
+## Environment
+
+### Check out the code
 
 ```shell
 git clone https://github.com/llvm/torch-mlir
@@ -11,7 +13,7 @@ git submodule update --init --progress
 Optionally, use `--depth=1` to make a shallow clone of the submodules.
 While this is running, you can already setup the Python venv and dependencies in the next step.
 
-## Setup your Python VirtualEnvironment and Dependencies
+### Setup your Python VirtualEnvironment and Dependencies
 
 ```shell
 python3 -m venv mlir_venv
@@ -31,7 +33,7 @@ it with the following `apt` command on Ubuntu/Debian.
 sudo apt install python3-dev
 ```
 
-## (Optional) Set up pre-commit
+### (Optional) Set up pre-commit
 
 This project uses [pre-commit](https://pre-commit.com/) in its CI. You can
 install it locally too in order to lint and fix your code prior to the CI
@@ -44,19 +46,19 @@ pip install pre-commit
 pre-commit install
 ```
 
-# Building
+## Building
 
-## With CMake
+### With CMake
 
-### Configure for Building...
+#### Configure for Building...
 
 Two setups are possible to build: in-tree and out-of-tree. The in-tree setup is the most straightforward, as it will build LLVM dependencies as well.
 
-#### ...with LLVM "in-tree" using...
+##### ...with LLVM "in-tree" using...
 
 The following commands generate configuration files to build the project *in-tree*, that is, using llvm/llvm-project as the main build. This will build LLVM as well as torch-mlir and its subprojects.  On Windows, use the "Developer PowerShell for Visual Studio" to ensure that the compiler and linker binaries are in the `PATH` variable.
 
-##### ...Base + Optimization Options
+###### ...Base + Optimization Options
 
 This requires `lld`, `clang`, `ccache`, and other dependencies for building `libtorch` / `PyTorch` wheels from source. If you run into issues because of these, try the [simplified build command](#base-options).
 
@@ -90,7 +92,7 @@ cmake -GNinja -Bbuild \
   -DLIBTORCH_VARIANT=shared
 ```
 
-##### ...Base Options
+###### ...Base Options
 
 If you're running into issues with the above build command, consider using the following:
 
@@ -106,7 +108,7 @@ cmake -GNinja -Bbuild \
   externals/llvm-project/llvm
 ```
 
-#### Options to enable MLIR debugging
+##### Options to enable MLIR debugging
 
 * Enabling `--debug` and `--debug-only` flags (see [MLIR docs](https://mlir.llvm.org/getting_started/Debugging/)) for the `torch-mlir-opt` tool
 ```shell
@@ -114,7 +116,7 @@ cmake -GNinja -Bbuild \
   -DLLVM_ENABLE_ASSERTIONS=ON \
 ```
 
-#### Options to run end-to-end tests
+##### Options to run end-to-end tests
 
 Running the end-to-end execution tests locally requires enabling the native PyTorch extension features and the JIT IR importer, which depends on the
 former and defaults to `ON` if not changed:
@@ -123,7 +125,7 @@ former and defaults to `ON` if not changed:
   -DTORCH_MLIR_ENABLE_JIT_IR_IMPORTER=ON \
 ```
 
-#### ...with LLVM "out-of-tree"
+##### ...with LLVM "out-of-tree"
 
 If you have built llvm-project separately in the directory `$LLVM_INSTALL_DIR`, you can also build the project *out-of-tree* using the following command as template:
 ```shell
@@ -140,7 +142,7 @@ The same QoL CMake flags can be used to enable clang, ccache, and lld. Be sure t
 
 Be aware that the installed version of LLVM needs in general to match the committed version in `externals/llvm-project`. Using a different version may or may not work.
 
-### Initiate Build
+#### Initiate Build
 
 After either cmake run (in-tree/out-of-tree), use one of the following commands to build the project:
 
@@ -158,21 +160,21 @@ cmake --build build --target check-torch-mlir-python
 cmake --build build
 ```
 
-## Setup Python Environment to export the built Python packages
+### Setup Python Environment to export the built Python packages
 
-### Linux and macOS
+#### Linux and macOS
 
 ```shell
 export PYTHONPATH=`pwd`/build/tools/torch-mlir/python_packages/torch_mlir:`pwd`/test/python/fx_importer
 ```
 
-### Windows PowerShell
+#### Windows PowerShell
 
 ```shell
 $env:PYTHONPATH = "$PWD/build/tools/torch-mlir/python_packages/torch_mlir;$PWD/test/python/fx_importer"
 ```
 
-## Testing MLIR output in various dialects
+### Testing MLIR output in various dialects
 
 To test the MLIR output to torch dialect, you can use `test/python/fx_importer/basic_test.py`.
 
@@ -211,7 +213,7 @@ module = torch_mlir.torchscript.compile(resnet18, torch.ones(1, 3, 224, 224), ou
 
 `output_type` can be: `TORCH`, `TOSA`, `LINALG_ON_TENSORS`, `RAW` and `STABLEHLO`.
 
-## Jupyter
+### Jupyter
 
 Jupyter notebook:
 
@@ -225,7 +227,7 @@ jupyter notebook
 [Example IR](https://gist.github.com/silvasean/e74780f8a8a449339aac05c51e8b0caa) for a simple 1 layer MLP to show the compilation steps from TorchScript.
 
 
-## Interactive Use
+### Interactive Use
 
 The `build_tools/write_env_file.sh` script will output a `.env`
 file in the workspace folder with the correct PYTHONPATH set. This allows
@@ -233,7 +235,7 @@ tools like VSCode to work by default for debugging. This file can also be
 manually `source`'d in a shell.
 
 
-## Bazel Build
+### Bazel Build
 
 > **NOTE** Our Bazel build follows LLVM's Bazel build policy: only the
 > subcommunity interested in Bazel is responsible for fixing it. Average
@@ -273,7 +275,7 @@ the BUILD files are formatted consistently:
 bazel run @torch-mlir//:buildifier
 ```
 
-## Docker Builds
+### Docker Builds
 
 We have preliminary support for building with Docker images. Currently this
 is not very convenient for day-to-day interactive development and
@@ -290,7 +292,7 @@ is built as part of the LLVM project along with MLIR.
 We mount a ccache and pip cache inside the docker container to speed up iterative builds. Iterative
 builds should be as fast as running without docker.
 
-### In-Tree builds
+#### In-Tree builds
 
 Build MLIR and Torch-MLIR together as part of the LLVM repo.
 
@@ -298,7 +300,7 @@ Build MLIR and Torch-MLIR together as part of the LLVM repo.
 TM_PACKAGES="in-tree" ./build_tools/python_deploy/build_linux_packages.sh
 ```
 
-### Out-of-Tree builds
+#### Out-of-Tree builds
 
 Build LLVM/MLIR first and then build Torch-MLIR referencing that build
 
@@ -306,7 +308,7 @@ Build LLVM/MLIR first and then build Torch-MLIR referencing that build
 TM_PACKAGES="out-of-tree" ./build_tools/python_deploy/build_linux_packages.sh
 ```
 
-### Release builds
+#### Release builds
 
 Build in a manylinux Docker image so we can upload artifacts to PyPI.
 
@@ -314,7 +316,7 @@ Build in a manylinux Docker image so we can upload artifacts to PyPI.
 TM_PACKAGES="torch-mlir" ./build_tools/python_deploy/build_linux_packages.sh
 ```
 
-### Mimicing CI+Release builds
+#### Mimicing CI+Release builds
 
 If you wanted to build all the CIs locally
 
@@ -330,7 +332,7 @@ TM_PACKAGES="torch-mlir out-of-tree in-tree" TM_PYTHON_VERSIONS="cp310-cp310" ./
 
 Note: The Release docker still runs as root so it may generate some files owned by root:root. We hope to move it to run as a user in the future.
 
-### Cleaning up
+#### Cleaning up
 
 Docker builds tend to leave a wide variety of files around. Luckily most are owned by the user but there are still some that need to be removed
 as superuser.
@@ -339,7 +341,7 @@ as superuser.
 rm -rf build build_oot llvm-build docker_venv externals/pytorch/build .ccache
 ```
 
-## Building your own Docker image
+### Building your own Docker image
 
 If you would like to build your own docker image (usually not necessary). You can run:
 
@@ -348,7 +350,7 @@ cd ./build_tools/docker
 docker build -t your-name/torch-mlir-ci --no-cache .
 ```
 
-### Other configurable environmental variables
+#### Other configurable environmental variables
 
 The following additional environmental variables can be used to customize your docker build:
 
@@ -401,7 +403,7 @@ The following additional environmental variables can be used to customize your d
 ```
 
 
-## Build Python Packages
+### Build Python Packages
 
 We have preliminary support for building Python packages. This can be done
 with the following commands:
@@ -422,7 +424,7 @@ TORCH_MLIR_CMAKE_BUILD_DIR=build/ TORCH_MLIR_CMAKE_ALREADY_BUILT=1 python setup.
 Note: The setup.py script is only used for building the Python packages,
 not support commands like `setup.py develop` to build the development environment.
 
-# Testing
+## Testing
 
 Torch-MLIR has two types of tests:
 
@@ -442,7 +444,7 @@ Torch-MLIR has two types of tests:
    [LLVM Testing Guide](https://llvm.org/docs/TestingGuide.html#regression-test-structure).
 
 
-## Running execution (end-to-end) tests:
+### Running execution (end-to-end) tests:
 
 > **Note**
 > An `.env` file must be generated via `build_tools/write_env_file.sh` before these commands can be run.
@@ -480,7 +482,7 @@ vars like this makes it easy to set in GH action files, etc. Note that the
 verbose flags are very verbose. Basic sequential progress reports will be
 printed regardless when not running in parallel.
 
-## Running unit tests.
+### Running unit tests.
 
 To run all of the unit tests, run:
 
@@ -513,7 +515,7 @@ $TORCH_MLIR_BUILD_DIR/bin/llvm-lit $TORCH_MLIR_SRC_ROOT/test -v --filter=canonic
 
 Most of the unit tests use the [`FileCheck` tool](https://llvm.org/docs/CommandGuide/FileCheck.html) to verify expected outputs.
 
-# PyTorch source builds and custom PyTorch versions
+## PyTorch source builds and custom PyTorch versions
 
 Torch-MLIR by default builds with the latest nightly PyTorch version. This can be toggled to build from latest PyTorch source with
 
@@ -523,7 +525,7 @@ Torch-MLIR by default builds with the latest nightly PyTorch version. This can b
 -DTORCH_MLIR_SRC_PYTORCH_BRANCH=master # Optional. Defaults to PyTorch's main branch
 ```
 
-# Updating the LLVM and MLIR-HLO submodules
+## Updating the LLVM and MLIR-HLO submodules
 
 Torch-MLIR depends on `llvm-project` (which contains, among other things,
 upstream MLIR) and `stablehlo`, both of which are submodules in the `externals/`
@@ -531,7 +533,7 @@ directory. We aim to update these at least weekly to bring in the latest
 features and spread out over time the effort of updating our code for MLIR API
 breakages.
 
-## Which LLVM commit should I pick?
+### Which LLVM commit should I pick?
 
 NOTE: This section is in flux. Specifically, the `mlir-hlo` dep has been
 dropped and the project is running off of a `stablehlo` fork which can be
@@ -551,7 +553,7 @@ our submodule updates on these green commits also helps us stay in sync with
 LLVM updates in other projects like ONNX-MLIR and MLIR-HLO. The person
 responsible for the update each week is listed [here](https://github.com/llvm/torch-mlir/wiki/Weekly-LLVM-Update).
 
-## What is the update process?
+### What is the update process?
 
 1. **Lookup green commit hashes**: From the Github issue
    https://github.com/llvm/torch-mlir/issues/1178, find the LLVM and MLIR-HLO
@@ -583,7 +585,7 @@ Here are some examples of PRs updating the LLVM and MLIR-HLO submodules:
 - https://github.com/llvm/torch-mlir/pull/1180
 - https://github.com/llvm/torch-mlir/pull/1229
 
-# Enabling Address Sanitizer (ASan)
+## Enabling Address Sanitizer (ASan)
 
 To enable ASAN, pass `-DLLVM_USE_SANITIZER=Address` to CMake. This should "just
 work" with all C++ tools like `torch-mlir-opt`. When running a Python script
@@ -597,7 +599,7 @@ LD_PRELOAD="$(clang -print-file-name=libclang_rt.asan-x86_64.so)" ./projects/pt1
 
 TODO: Add ASan docs for LTC.
 
-# Other docs
+## Other docs
 
 - GitHub wiki: https://github.com/llvm/torch-mlir/wiki
 - Of particular interest in the [How to add end-to-end support for new Torch ops](https://github.com/llvm/torch-mlir/wiki/Torch-ops-E2E-implementation) doc.

From 811a78a7f97ff1983c07e7eddfee217c47bdcdf2 Mon Sep 17 00:00:00 2001
From: Jacob Gordon <jacob.gordon@amd.com>
Date: Tue, 25 Feb 2025 14:25:35 +0000
Subject: [PATCH 4/5] docs(development.md): renames h2 "Environment" to
 "Setting Up Environment"

---
 docs/development.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/development.md b/docs/development.md
index 17ddd88f4c0e..9efe1293b7c9 100644
--- a/docs/development.md
+++ b/docs/development.md
@@ -1,6 +1,6 @@
 # Development Guide
 
-## Environment
+## Setting Up Environment
 
 ### Check out the code
 

From 33298a7c35bca6a5df36811223a3197ca00a8c4b Mon Sep 17 00:00:00 2001
From: Jacob Gordon <jacob.gordon@amd.com>
Date: Tue, 25 Feb 2025 14:32:12 +0000
Subject: [PATCH 5/5] style(docs/development.md): nests code blocks for list
 items

---
 docs/development.md | 62 ++++++++++++++++++++++-----------------------
 1 file changed, 31 insertions(+), 31 deletions(-)

diff --git a/docs/development.md b/docs/development.md
index 9efe1293b7c9..ecce40707659 100644
--- a/docs/development.md
+++ b/docs/development.md
@@ -249,23 +249,23 @@ Torch-MLIR can also be built using Bazel (apart from the official CMake build) f
 
 1. Launch an interactive docker container with the required deps installed:
 
-```shell
-./utils/bazel/docker/run_docker.sh
-```
+    ```shell
+    ./utils/bazel/docker/run_docker.sh
+    ```
 
 2. Build torch-mlir:
 
-```shell
-bazel build @torch-mlir//:torch-mlir-opt
-```
+    ```shell
+    bazel build @torch-mlir//:torch-mlir-opt
+    ```
 
-The built binary should be at `bazel-bin/external/torch-mlir/torch-mlir-opt`.
+    The built binary should be at `bazel-bin/external/torch-mlir/torch-mlir-opt`.
 
 3. Test torch-mlir (lit test only):
 
-```shell
-bazel test @torch-mlir//test/...
-```
+    ```shell
+    bazel test @torch-mlir//test/...
+    ```
 
 We welcome patches to torch-mlir's Bazel build. If you do contribute,
 please complete your PR with an invocation of buildifier to ensure
@@ -357,50 +357,50 @@ The following additional environmental variables can be used to customize your d
 * Custom Release Docker image:
   Defaults to `stellaraccident/manylinux2014_x86_64-bazel-5.1.0:latest`
 
-```shell
-  TM_RELEASE_DOCKER_IMAGE="stellaraccident/manylinux2014_x86_64-bazel-5.1.0:latest"
-```
+    ```shell
+      TM_RELEASE_DOCKER_IMAGE="stellaraccident/manylinux2014_x86_64-bazel-5.1.0:latest"
+    ```
 
 * Custom CI Docker image:
   Defaults to `powderluv/torch-mlir-ci:latest`. This assumes an Ubuntu LTS like image. You can build your own with `./build_tools/docker/Dockerfile`
 
-```shell
-  TM_CI_DOCKER_IMAGE="powderluv/torch-mlir-ci:latest"
-```
+    ```shell
+      TM_CI_DOCKER_IMAGE="powderluv/torch-mlir-ci:latest"
+    ```
 
 * Custom Python Versions for Release builds:
   Version of Python to use in Release builds. Ignored in CIs. Defaults to `cp39-cp39 cp310-cp310 cp312-cp312`
 
-```shell
-  TM_PYTHON_VERSIONS="cp39-cp39 cp310-cp310 cp312-cp312"
-```
+    ```shell
+      TM_PYTHON_VERSIONS="cp39-cp39 cp310-cp310 cp312-cp312"
+    ```
 
 * Location to store Release build wheels
 
-```shell
-  TM_OUTPUT_DIR="./build_tools/python_deploy/wheelhouse"
-```
+    ```shell
+      TM_OUTPUT_DIR="./build_tools/python_deploy/wheelhouse"
+    ```
 
 * What "packages" to build:
   Defaults to torch-mlir. Options are `torch-mlir out-of-tree in-tree`
 
-```shell
-  TM_PACKAGES="torch-mlir out-of-tree in-tree"
-```
+    ```shell
+      TM_PACKAGES="torch-mlir out-of-tree in-tree"
+    ```
 
 * Use pre-built Pytorch:
   Defaults to using pre-built Pytorch. Setting it to `OFF` builds from source
 
-```shell
-  TM_USE_PYTORCH_BINARY="OFF"
-```
+    ```shell
+      TM_USE_PYTORCH_BINARY="OFF"
+    ```
 
 * Skip running tests
   Skip running tests if you want quick build only iteration. Default set to `OFF`
 
-```shell
-  TM_SKIP_TESTS="OFF"
-```
+    ```shell
+      TM_SKIP_TESTS="OFF"
+    ```
 
 
 ### Build Python Packages