format

docs/user-guide/gpu-support.md

@@ -31,6 +31,7 @@ You can install the GPU backend for Polars with a feature flag as part of a norm
 Having built a query using the lazy API [as normal](lazy/index.md), GPU-enabled execution is requested by running `.collect(engine="gpu")` instead of `.collect()`.
 
 {{ code_header("python", [], []) }}
+
 ```python
 --8<-- "python/user-guide/lazy/gpu.py:setup"
 
@@ -46,6 +47,7 @@ print(result)
 For more detailed control over the execution, for example to specify which GPU to use on a multi-GPU node, we can provide a `GPUEngine` object. By default, the GPU engine will use a configuration applicable to most use cases.
 
 {{ code_header("python", [], []) }}
+
 ```python
 --8<-- "python/user-guide/lazy/gpu.py:engine-setup"
 result = q.collect(engine=pl.GPUEngine(device=1))
@@ -99,6 +101,7 @@ The release of the GPU engine in Open Beta implies that we expect things to work
 When running in verbose mode, any queries that cannot execute on the GPU will issue a `PerformanceWarning`:
 
 {{ code_header("python", [], []) }}
+
 ```python
 --8<-- "python/user-guide/lazy/gpu.py:fallback-setup"
 
@@ -123,6 +126,7 @@ print(q.collect())
 To disable fallback, and have the GPU engine raise an exception if a query is unsupported, we can pass an appropriately configured `GPUEngine` object:
 
 {{ code_header("python", [], []) }}
+
 ```python
 q.collect(engine=pl.GPUEngine(raise_on_fail=True))
 ```

docs/user-guide/lazy/gpu.md

@@ -5,6 +5,7 @@ Polars provides an in-memory, GPU-accelerated execution engine for the Lazy API
 If you install Polars with the [GPU feature flag](../installation.md), you can trigger GPU-based execution by running `.collect(engine="gpu")` instead of `.collect()`.
 
 {{ code_header("python", [], []) }}
+
 ```python
 --8<-- "python/user-guide/lazy/gpu.py:setup"