add macros

Signed-off-by: sirutBuasai <sirutbuasai27@outlook.com>

Author: sirutBuasai

docs/.nav.yml

@@ -2,6 +2,7 @@ nav:
   - Home: index.md
   - Getting Started:
     - get_started/index.md
+    - Using Deep Learning Containers: get_started/using_dlcs.md
   - Tutorials: tutorials
   - Reference:
     - Available Images: reference/available_images.md

docs/get_started/index.md

@@ -46,7 +46,7 @@ Where:
 aws ecr get-login-password --region us-west-2 | docker login --username AWS --password-stdin 763104351884.dkr.ecr.us-west-2.amazonaws.com
 
 # Pull PyTorch training image
-docker pull 763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-training:2.9.0-gpu-py312-cu130-ubuntu22.04-sagemaker
+docker pull 763104351884.dkr.ecr.us-west-2.amazonaws.com/{{ images.latest_pytorch_training_ec2 }}
 ```
 
 ## Next Steps

docs/get_started/using_dlcs.md

@@ -0,0 +1,143 @@
+# Using Deep Learning Containers
+
+This guide covers how to run AWS Deep Learning Containers on AWS Platforms such as SageMaker and EC2.
+
+## Running on SageMaker
+
+### Using SageMaker Python SDK
+
+Deploy a vLLM inference endpoint:
+
+```python
+from sagemaker.model import Model
+
+model = Model(
+    image_uri="{{ images.latest_vllm_sagemaker }}",
+    role="arn:aws:iam::<account_id>:role/<role_name>",
+    env={
+        "SM_VLLM_MODEL": "meta-llama/Llama-3.1-8B-Instruct",
+        "HF_TOKEN": "<your_hf_token>",
+    },
+)
+
+predictor = model.deploy(
+    instance_type="ml.g5.2xlarge",
+    initial_instance_count=1,
+)
+```
+
+Deploy an SGLang inference endpoint:
+
+```python
+from sagemaker.model import Model
+
+model = Model(
+    image_uri="{{ images.latest_sglang_sagemaker }}",
+    role="arn:aws:iam::<account_id>:role/<role_name>",
+    env={
+        "SM_SGLANG_MODEL_PATH": "meta-llama/Llama-3.1-8B-Instruct",
+        "HF_TOKEN": "<your_hf_token>",
+    },
+)
+
+predictor = model.deploy(
+    instance_type="ml.g5.2xlarge",
+    initial_instance_count=1,
+)
+```
+
+### Using Boto3
+
+Deploy a vLLM inference endpoint:
+
+```python
+import boto3
+
+sagemaker = boto3.client("sagemaker")
+
+sagemaker.create_model(
+    ModelName="vllm-model",
+    PrimaryContainer={
+        "Image": "{{ images.latest_vllm_sagemaker }}",
+        "Environment": {
+            "SM_VLLM_MODEL": "meta-llama/Llama-3.1-8B-Instruct",
+            "HF_TOKEN": "<your_hf_token>",
+        },
+    },
+    ExecutionRoleArn="arn:aws:iam::<account_id>:role/<role_name>",
+)
+
+sagemaker.create_endpoint_config(
+    EndpointConfigName="vllm-endpoint-config",
+    ProductionVariants=[
+        {
+            "VariantName": "default",
+            "ModelName": "vllm-model",
+            "InstanceType": "ml.g5.2xlarge",
+            "InitialInstanceCount": 1,
+        }
+    ],
+)
+
+sagemaker.create_endpoint(
+    EndpointName="vllm-endpoint",
+    EndpointConfigName="vllm-endpoint-config",
+)
+```
+
+Deploy an SGLang inference endpoint:
+
+```python
+import boto3
+
+sagemaker = boto3.client("sagemaker")
+
+sagemaker.create_model(
+    ModelName="sglang-model",
+    PrimaryContainer={
+        "Image": "{{ images.latest_sglang_sagemaker }}",
+        "Environment": {
+            "SM_SGLANG_MODEL_PATH": "meta-llama/Llama-3.1-8B-Instruct",
+            "HF_TOKEN": "<your_hf_token>",
+        },
+    },
+    ExecutionRoleArn="arn:aws:iam::<account_id>:role/<role_name>",
+)
+
+sagemaker.create_endpoint_config(
+    EndpointConfigName="sglang-endpoint-config",
+    ProductionVariants=[
+        {
+            "VariantName": "default",
+            "ModelName": "sglang-model",
+            "InstanceType": "ml.g5.2xlarge",
+            "InitialInstanceCount": 1,
+        }
+    ],
+)
+
+sagemaker.create_endpoint(
+    EndpointName="sglang-endpoint",
+    EndpointConfigName="sglang-endpoint-config",
+)
+```
+
+## Running on EC2
+
+After pulling a DLC image, run it with Docker:
+
+```bash
+# Run interactively
+docker run -it --gpus all <account_id>.dkr.ecr.<region>.amazonaws.com/<repository>:<tag> bash
+
+# Example: Run PyTorch container
+docker run -it --gpus all {{ images.latest_pytorch_training_ec2 }} bash
+```
+
+Mount local directories to persist data:
+
+```bash
+docker run -it --gpus all -v /local/data:/data <image_uri> bash
+```
+
+For available image URIs, see [Available Images](../reference/available_images.md).

docs/requirements.txt

@@ -1,3 +1,4 @@
 mkdocs-autorefs
 mkdocs-awesome-nav
+mkdocs-macros-plugin
 mkdocs-material>=9.0

docs/src/macros.py

@@ -0,0 +1,41 @@
+# Copyright 2018-2020 Amazon.com, Inc. or its affiliates. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License"). You
+# may not use this file except in compliance with the License. A copy of
+# the License is located at
+#
+#     http://aws.amazon.com/apache2.0/
+#
+# or in the "license" file accompanying this file. This file is
+# distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF
+# ANY KIND, either express or implied. See the License for the specific
+# language governing permissions and limitations under the License.
+"""Documentation global variables for mkdocs-macros-plugin."""
+
+import os
+
+from utils import load_yaml
+
+SRC_DIR = os.path.dirname(os.path.abspath(__file__))
+DATA_FILE = os.path.join(SRC_DIR, "data", "images.yml")
+
+
+def get_latest_image(repo: str, platform: str) -> str:
+    """Get the latest image URI for a repository and platform."""
+    data = load_yaml(DATA_FILE)
+    tags = data.get("images", {}).get(repo, [])
+    for tag in tags:
+        if tag.endswith(platform):
+            return f"763104351884.dkr.ecr.us-west-2.amazonaws.com/{repo}:{tag}"
+    raise ValueError(
+        f"Image not found for {repo} with platform {platform}. Docs must be fixed to use a valid image."
+    )
+
+
+def define_env(env):
+    """Define variables for mkdocs-macros-plugin."""
+    env.variables["images"] = {
+        "latest_pytorch_training_ec2": get_latest_image("pytorch-training", "-ec2"),
+        "latest_vllm_sagemaker": get_latest_image("vllm", "-sagemaker"),
+        "latest_sglang_sagemaker": get_latest_image("sglang", "-sagemaker"),
+    }

mkdocs.yaml

@@ -80,6 +80,8 @@ plugins:
   - search                                                        # Built-in search
   - autorefs                                                      # Auto-link to other pages/headings
   - awesome-nav                                                   # .nav.yml file support
+  - macros:                                                       # Variable substitution in markdown
+      module_name: docs/src/macros
 
 # === Custom Assets ===
 extra_css: