[Doc] Fix some MkDocs snippets used in the installation docs (vllm-project#20572)

Signed-off-by: Harry Mellor <19981378+hmellor@users.noreply.github.com>

Author: hmellor

docs/getting_started/installation/cpu/apple.inc.md

@@ -54,9 +54,6 @@ If the build has error like the following snippet where standard C++ headers can
 ```
 
 # --8<-- [end:build-wheel-from-source]
-# --8<-- [start:set-up-using-docker]
-
-# --8<-- [end:set-up-using-docker]
 # --8<-- [start:pre-built-images]
 
 # --8<-- [end:pre-built-images]

docs/getting_started/installation/cpu/arm.inc.md

@@ -28,9 +28,6 @@ ARM CPU backend currently supports Float32, FP16 and BFloat16 datatypes.
 Testing has been conducted on AWS Graviton3 instances for compatibility.
 
 # --8<-- [end:build-wheel-from-source]
-# --8<-- [start:set-up-using-docker]
-
-# --8<-- [end:set-up-using-docker]
 # --8<-- [start:pre-built-images]
 
 # --8<-- [end:pre-built-images]

docs/getting_started/installation/cpu/s390x.inc.md

@@ -56,9 +56,6 @@ Execute the following commands to build and install vLLM from the source.
 ```
 
 # --8<-- [end:build-wheel-from-source]
-# --8<-- [start:set-up-using-docker]
-
-# --8<-- [end:set-up-using-docker]
 # --8<-- [start:pre-built-images]
 
 # --8<-- [end:pre-built-images]

docs/getting_started/installation/cpu/x86.inc.md

@@ -31,9 +31,6 @@ vLLM initially supports basic model inferencing and serving on x86 CPU platform,
     - If you want to force enable AVX512_BF16 for the cross-compilation, please set environment variable `VLLM_CPU_AVX512BF16=1` before the building.
 
 # --8<-- [end:build-wheel-from-source]
-# --8<-- [start:set-up-using-docker]
-
-# --8<-- [end:set-up-using-docker]
 # --8<-- [start:pre-built-images]
 
 See [https://gallery.ecr.aws/q9t5s3a7/vllm-cpu-release-repo](https://gallery.ecr.aws/q9t5s3a7/vllm-cpu-release-repo)

docs/getting_started/installation/gpu.md

@@ -46,11 +46,11 @@ vLLM is a Python library that supports the following GPU variants. Select your G
 
 === "AMD ROCm"
 
-    There is no extra information on creating a new Python environment for this device.
+    --8<-- "docs/getting_started/installation/gpu/rocm.inc.md:set-up-using-python"
 
 === "Intel XPU"
 
-    There is no extra information on creating a new Python environment for this device.
+    --8<-- "docs/getting_started/installation/gpu/xpu.inc.md:set-up-using-python"
 
 ### Pre-built wheels
 

docs/getting_started/installation/gpu/cuda.inc.md

@@ -232,9 +232,6 @@ pip install -e .
 ```
 
 # --8<-- [end:build-wheel-from-source]
-# --8<-- [start:set-up-using-docker]
-
-# --8<-- [end:set-up-using-docker]
 # --8<-- [start:pre-built-images]
 
 See [deployment-docker-pre-built-image][deployment-docker-pre-built-image] for instructions on using the official Docker image.
@@ -261,4 +258,3 @@ See [deployment-docker-build-image-from-source][deployment-docker-build-image-fr
 See [feature-x-hardware][feature-x-hardware] compatibility matrix for feature support information.
 
 # --8<-- [end:supported-features]
-# --8<-- [end:extra-information]

docs/getting_started/installation/gpu/rocm.inc.md

@@ -2,6 +2,9 @@
 
 vLLM supports AMD GPUs with ROCm 6.3.
 
+!!! tip
+    [Docker](#set-up-using-docker) is the recommended way to use vLLM on ROCm.
+
 !!! warning
     There are no pre-built wheels for this device, so you must either use the pre-built Docker image or build vLLM from source.
 
@@ -14,6 +17,8 @@ vLLM supports AMD GPUs with ROCm 6.3.
 # --8<-- [end:requirements]
 # --8<-- [start:set-up-using-python]
 
+There is no extra information on creating a new Python environment for this device.
+
 # --8<-- [end:set-up-using-python]
 # --8<-- [start:pre-built-wheels]
 
@@ -123,9 +128,7 @@ Currently, there are no pre-built ROCm wheels.
     - For MI300x (gfx942) users, to achieve optimal performance, please refer to [MI300x tuning guide](https://rocm.docs.amd.com/en/latest/how-to/tuning-guides/mi300x/index.html) for performance optimization and tuning tips on system and workflow level.
       For vLLM, please refer to [vLLM performance optimization](https://rocm.docs.amd.com/en/latest/how-to/tuning-guides/mi300x/workload.html#vllm-performance-optimization).
 
-## Set up using Docker (Recommended)
-
-# --8<-- [end:set-up-using-docker]
+# --8<-- [end:build-wheel-from-source]
 # --8<-- [start:pre-built-images]
 
 The [AMD Infinity hub for vLLM](https://hub.docker.com/r/rocm/vllm/tags) offers a prebuilt, optimized
@@ -227,4 +230,3 @@ Where the `<path/to/model>` is the location where the model is stored, for examp
 See [feature-x-hardware][feature-x-hardware] compatibility matrix for feature support information.
 
 # --8<-- [end:supported-features]
-# --8<-- [end:extra-information]

docs/getting_started/installation/gpu/xpu.inc.md

@@ -14,6 +14,8 @@ vLLM initially supports basic model inference and serving on Intel GPU platform.
 # --8<-- [end:requirements]
 # --8<-- [start:set-up-using-python]
 
+There is no extra information on creating a new Python environment for this device.
+
 # --8<-- [end:set-up-using-python]
 # --8<-- [start:pre-built-wheels]
 
@@ -43,9 +45,6 @@ VLLM_TARGET_DEVICE=xpu python setup.py install
       type is supported on Intel Data Center GPU, not supported on Intel Arc GPU yet.
 
 # --8<-- [end:build-wheel-from-source]
-# --8<-- [start:set-up-using-docker]
-
-# --8<-- [end:set-up-using-docker]
 # --8<-- [start:pre-built-images]
 
 Currently, there are no pre-built XPU images.
@@ -86,4 +85,3 @@ By default, a ray instance will be launched automatically if no existing one is
 XPU platform uses **torch-ccl** for torch<2.8 and **xccl** for torch>=2.8 as distributed backend, since torch 2.8 supports **xccl** as built-in backend for XPU.
 
 # --8<-- [end:distributed-backend]
-# --8<-- [end:extra-information]