Pin ML training example to x86_64-linux (#5)

It would be nice to support other platforms as well here, but the setup
is too complex for what we're trying to illustrate and without CI it's
also too hard to ensure that it's working as expected on all platforms.

Author: aaronmondal

finetuning_on_cpu/.bazelrc

@@ -25,8 +25,8 @@ build --experimental_profile_include_target_label
 build --noexperimental_profile_include_primary_output
 
 # Use the container image specified in `platforms/BUILD.bazel`.
-build:remote --extra_execution_platforms=@//platforms:python-remote
-build:remote --extra_toolchains=@zig_sdk//toolchain:linux_amd64_musl
+build --extra_execution_platforms=@//platforms:python-remote
+build --extra_toolchains=@zig_sdk//toolchain:linux_amd64_musl
 
 # Add user specific flags.
 try-import %workspace%/user.bazelrc

finetuning_on_cpu/BUILD.bazel

@@ -1,19 +1,7 @@
 load("@rules_python//python/uv:lock.bzl", "lock")
 
-exports_files(
-    ["python_provider.sh"],
-    visibility = ["//visibility:public"],
+lock(
+    name = "requirements",
+    srcs = ["pyproject.toml"],
+    out = "requirements.lock",
 )
-
-[
-    lock(
-        name = "requirements_{}".format(os),
-        srcs = ["pyproject.toml"],
-        out = "requirements_{}.lock".format(os),
-        build_constraints = ["@platforms//os:{}".format(os)],
-    )
-    for os in [
-        "linux",
-        "macos",
-    ]
-]

finetuning_on_cpu/MODULE.bazel

@@ -23,10 +23,8 @@ pip.parse(
     },
     hub_name = "pypi",
     python_version = "3.13",
-    # This file may be regenerated via `bazel run //:requirements_macos.update`.
-    requirements_darwin = "//:requirements_macos.lock",
-    # This file may be regenerated via `bazel run //:requirements_linux.update`.
-    requirements_linux = "//:requirements_linux.lock",
+    # This file may be regenerated via `bazel run //:requirements.update`.
+    requirements_linux = "//:requirements.lock",
 )
 use_repo(pip, "pypi")
 

finetuning_on_cpu/README.md

@@ -2,6 +2,9 @@
 
 An example project for training a machine learning model with Bazel.
 
+> [!NOTE]
+> This example only supports `x86_64-linux`.
+
 ## ❄️ Setup
 
 1. Either have Bazelisk installed or enter the nix flake from this repository.
@@ -31,7 +34,7 @@ Now run a remote invocation. The first time you do this it'll be slow (~15min)
 as the runner needs to spin up and fetch the various toolchains:
 
 ```bash
-bazel test training --config=remote --test_output=all
+bazel test training --test_output=all
 ```
 
 Run the above command a second time. Since the runner is now warm it'll
@@ -44,15 +47,9 @@ The dependencies for this project are tracked in `pyproject.toml` and locked in
 regenerate the lockfiles:
 
 ```bash
-# On linux
-bazel run //:requirements_linux.update
-
-# On macos
-bazel run //:requirements_macos.update
+bazel run //:requirements.update
 ```
 
-On darwin you might have to disable remote execution temporarily for this.
-
 ## 🧹 Fixing formatting and linting
 
 Use the flake if you develop on this code. Don't use local ruff installations as

finetuning_on_cpu/requirements_linux.lock finetuning_on_cpu/requirements.lockfinetuning_on_cpu/requirements_linux.lock renamed to finetuning_on_cpu/requirements.lock

@@ -1,5 +1,5 @@
 # This file was autogenerated by uv via the following command:
-#    bazel run //:requirements_linux.update
+#    bazel run //:requirements.update
 accelerate==1.6.0 \
     --hash=sha256:1aee717d3d3735ad6d09710a7c26990ee4652b79b4e93df46551551b5227c2aa \
     --hash=sha256:28c1ef1846e690944f98b68dc7b8bb6c51d032d45e85dcbb3adb0c8b99dffb32
@@ -1015,9 +1015,9 @@ safetensors==0.5.3 \
     # via
     #   accelerate
     #   transformers
-setuptools==80.4.0 \
-    --hash=sha256:5a78f61820bc088c8e4add52932ae6b8cf423da2aff268c23f813cfbb13b4006 \
-    --hash=sha256:6cdc8cb9a7d590b237dbe4493614a9b75d0559b888047c1f67d49ba50fc3edb2
+setuptools==80.7.0 \
+    --hash=sha256:d3b6ba519cc2b1e0b14195ef1a9560f675b1f873dc0d42969e139b2b58e763d6 \
+    --hash=sha256:e8fb83ffb2011d786ab2a38d63c33c261cc5862522a6b57ac8f7e7ffeff2336b
     # via torch
 six==1.17.0 \
     --hash=sha256:4721f391ed90541fddacab5acf947aa0d3dc7d27b2e1e8eda2be8970586c3274 \