From 7bad653c2a16f24de241f14b973b988af909b437 Mon Sep 17 00:00:00 2001 From: Andrei Maslennikov Date: Tue, 6 Jan 2026 12:19:58 +0100 Subject: [PATCH 01/13] Fully migrate from MD to RST for documentation --- doc/DEV.md | 86 --- doc/DEV.rst | 91 +++ doc/USER_GUIDE.md | 635 ------------------ doc/USER_GUIDE.rst | 736 +++++++++++++++++++++ doc/conf.py | 20 +- doc/index.md | 137 ---- doc/index.rst | 179 +++++ doc/reporting.md | 61 -- doc/reporting.rst | 77 +++ doc/workloads/bash_cmd.rst | 2 +- doc/workloads/chakra_replay.rst | 2 +- doc/workloads/ddlb.rst | 2 +- doc/workloads/index.rst | 2 +- doc/workloads/megatron_bridge.rst | 16 +- doc/workloads/nemo_run.rst | 2 +- doc/workloads/nixl_bench.rst | 2 +- doc/workloads/nixl_kvbench.rst | 2 +- doc/workloads/nixl_perftest.rst | 2 +- doc/workloads/sleep.rst | 2 +- doc/workloads/slurm_container.rst | 2 +- doc/workloads/ucc.rst | 2 +- pyproject.toml | 1 - uv.lock | 1023 +++++++++++++++++++++-------- 23 files changed, 1848 insertions(+), 1236 deletions(-) delete mode 100644 doc/DEV.md create mode 100644 doc/DEV.rst delete mode 100644 doc/USER_GUIDE.md create mode 100644 doc/USER_GUIDE.rst delete mode 100644 doc/index.md create mode 100644 doc/index.rst delete mode 100644 doc/reporting.md create mode 100644 doc/reporting.rst diff --git a/doc/DEV.md b/doc/DEV.md deleted file mode 100644 index 3e4d4da2f..000000000 --- a/doc/DEV.md +++ /dev/null @@ -1,86 +0,0 @@ -# Development -This document targets developers who want to contribute to the project's core. - - -```mermaid -graph TD - subgraph _core - base_modules - core_implementations - registry - end - - subgraph runners - SlurmRunner - StandaloneRunner - end - - subgraph installers - SlurmInstaller - StandaloneInstaller - end - - subgraph systems - SlurmSystem - StandaloneSystem - end - - installers --> _core - runners --> _core - systems --> _core -``` - -## Core Modules -We use [import-linter](https://github.com/seddonym/import-linter) to ensure no core modules import higher level modules. - -`Registry` object is a singleton that holds implementation mappings. Users can register their own implementations to the registry or replace the default implementations. - -## Cache -Some prerequisites can be installed. For example: Docker images, git repos with executable scripts, etc. -All such "installables" are kept under System's `install_path`. - -Installables are shared among all tests. So if any number of tests use the same installable, it is installed only once for a particular System TOML. - -```mermaid -classDiagram - class Installable { - <> - + __eq__(other: object) - + __hash__() - } - - class DockerImage { - + url: str - + install_path: str | Path - } - - class GitRepo { - + git_url: str - + commit_hash: str - + install_path: Path - } - - class PythonExecutable { - + git_repo: GitRepo - + venv_path: Path - } - - Installable <|-- DockerImage - Installable <|-- GitRepo - Installable <|-- PythonExecutable - PythonExecutable --> GitRepo - - class BaseInstaller { - <> - + install(items: Iterable[Installable]) - + uninstall(items: Iterable[Installable]) - + is_installed(items: Iterable[Installable]) -> bool - - * install_one(item: Installable) - * uninstall_one(item: Installable) - * is_installed_one(item: Installable) -> bool - } - - BaseInstaller <|-- SlurmInstaller - BaseInstaller <|-- StandaloneInstaller -``` diff --git a/doc/DEV.rst b/doc/DEV.rst new file mode 100644 index 000000000..35a45f311 --- /dev/null +++ b/doc/DEV.rst @@ -0,0 +1,91 @@ +Development +=========== + +This document targets developers who want to contribute to the project's core. + +.. mermaid:: + + graph TD + subgraph _core + base_modules + core_implementations + registry + end + + subgraph runners + SlurmRunner + StandaloneRunner + end + + subgraph installers + SlurmInstaller + StandaloneInstaller + end + + subgraph systems + SlurmSystem + StandaloneSystem + end + + installers --> _core + runners --> _core + systems --> _core + +Core Modules +------------ + +We use `import-linter `_ to ensure no core modules import higher level modules. + +``Registry`` object is a singleton that holds implementation mappings. Users can register their own implementations to the registry or replace the default implementations. + +Cache +----- + +Some prerequisites can be installed. For example: Docker images, git repos with executable scripts, etc. All such "installables" are kept under system ``install_path``. + +Installables are shared among all tests. So if any number of tests use the same installable, it is installed only once for a particular system TOML. + +.. mermaid:: + + classDiagram + class Installable { + <> + + __eq__(other: object) + + __hash__() + } + + class DockerImage { + + url: str + + install_path: str | Path + } + + class GitRepo { + + git_url: str + + commit_hash: str + + install_path: Path + } + + class PythonExecutable { + + git_repo: GitRepo + + venv_path: Path + } + + Installable <|-- DockerImage + Installable <|-- GitRepo + Installable <|-- PythonExecutable + PythonExecutable --> GitRepo + + class BaseInstaller { + <> + + install(items: Iterable[Installable]) + + uninstall(items: Iterable[Installable]) + + is_installed(items: Iterable[Installable]) -> bool + + * install_one(item: Installable) + * uninstall_one(item: Installable) + * is_installed_one(item: Installable) -> bool + } + + BaseInstaller <|-- SlurmInstaller + BaseInstaller <|-- StandaloneInstaller + diff --git a/doc/USER_GUIDE.md b/doc/USER_GUIDE.md deleted file mode 100644 index c43b74161..000000000 --- a/doc/USER_GUIDE.md +++ /dev/null @@ -1,635 +0,0 @@ -# CloudAI User Guide -The purpose of this guide is to help users use CloudAI. The user guide covers topics such as adding new tests and downloading datasets for running NeMo-launcher. - -## Step 1: Create a Docker Image -1. **Set Up the GitLab Repository:** - Start by setting up a repository on GitLab to host your docker image. For this example, use `gitlab-url.com/cloudai/nccl-test`. - -2. **Write the Dockerfile:** - The Dockerfile needs to specify the base image and detail the steps: - ```dockerfile - FROM nvcr.io/nvidia/pytorch:24.02-py3 - ``` - -3. **Build and Push the Docker Image:** - Build the docker image with the Dockerfile and upload it to the designated repository: - ```bash - docker build -t gitlab-url.com/cloudai/nccl-test . - docker push gitlab-url.com/cloudai/nccl-test - ``` - -4. **Verify the Docker Image:** - Test the docker image by running it with `srun` to verify that the docker image runs correctly: - ```bash - srun \ - --mpi=pmix \ - --container-image=gitlab-url.com/cloudai/nccl-test \ - all_reduce_perf_mpi \ - --nthreads 1 \ - --ngpus 1 \ - --minbytes 128 \ - --maxbytes 16G \ - --stepbytes 1M \ - --op sum \ - --datatype float \ - --root 0 \ - --iters 100 \ - --warmup_iters 50 \ - --agg_iters 1 \ - --average 1 \ - --parallel_init 0 \ - --check 1 \ - --blocking 0 \ - --cudagraph 0 \ - --stepfactor 2 - ``` - -## Step 2: Prepare Configuration Files -CloudAI is fully configurable via set of TOML configuration files. You can find examples of these files under `conf/common`. In this guide, we will use the following configuration files: -1. `myconfig/system.toml` - Describes the system configuration. -1. `myconfig/tests/nccl_test.toml` - Describes the test to run. -1. `myconfig/scenario.toml` - Describes the test scenario configuration. - - -## Step 3: Test Definition -Test definition is a Pydantic model that describes the arguments of a test. Such models should be inherited from the `TestDefinition` class: -```py -class MyTestCmdArgs(CmdArgs): - an_arg: str | list[str] - docker_image_url: str = "nvcr.io/nvidia/pytorch:24.02-py3" - -class MyTestDefinition(TestDefinition): - cmd_args: MyTestCmdArgs -``` -Notice that `cmd_args.docker_image_url` uses `nvcr.io/nvidia/pytorch:24.02-py3`, but you can use Docker image from Step 1. - -`an_arg` has mixed type of `str | list[str]`, so in a TOML config it can be defined as either: -```toml -an_arg = "a single string" -``` -or -```toml -an_arg = ["list", "of", "strings"] -``` -When a list is used, CloudAI will automatically generate multiple test cases for each value in the list. - -A custom test definition should be registered to handle relevant Test Configs. For this, `Registry()` object is used: -```py -Registry().add_test_definition("MyTest", MyTestDefinition) -Registry().add_test_template("MyTest", MyTest) -``` -Relevant Test Configs should specify `test_template_name = MyTest` to use the custom test definition. - -## Step 4: System Configuration -System configuration describes the system configuration. You can find more examples of system configs under `conf/common/system/`. Our example will be small for demonstration purposes. Below is the `myconfig/system.toml` file: -```toml -name = "my-cluster" -scheduler = "slurm" - -install_path = "./install" -output_path = "./results" -cache_docker_images_locally = true -default_partition = "" - -mpi = "pmix" -gpus_per_node = 8 -ntasks_per_node = 8 - -[[partitions]] -name = "partition_1" -``` -Replace `` with the name of the partition you want to use. You can find the partition name by running `sinfo` on the cluster. - -## Step 5: Test Configuration -Test Configuration describes a particular test configuration to be run. It is based on Test definition and will be used in Test Sceanrio. Below is the `myconfig/tests/nccl_test.toml` file, definition is based on built-in `NcclTest` definition: -```toml -name = "nccl_test_all_reduce_single_node" -description = "all_reduce" -test_template_name = "NcclTest" - -[cmd_args] -subtest_name = "all_reduce_perf_mpi" -ngpus = 1 -minbytes = "8M" -maxbytes = "16G" -iters = 5 -warmup_iters = 3 -stepfactor = 2 -``` -You can find more examples under `conf/common/test`. In a test schema file, you can adjust arguments as shown above. In the `cmd_args` section, you can provide different values other than the default values for each argument. In `extra_cmd_args`, you can provide additional arguments that will be appended after the NCCL test command. You can specify additional environment variables in the `extra_env_vars` section. - - -## Step 6: Run Experiments -Test Scenario uses Test description from step 5. Below is the `myconfig/scenario.toml` file: -```toml -name = "nccl-test" - -[[Tests]] -id = "allreduce.1" -num_nodes = 1 -test_name = "nccl_test_all_reduce_single_node" -time_limit = "00:20:00" - -[[Tests]] -id = "allreduce.2" -num_nodes = 1 -test_name = "nccl_test_all_reduce_single_node" -time_limit = "00:20:00" - [[Tests.dependencies]] - type = "start_post_comp" - id = "Tests.1" -``` - -Notes on the test scenario: -1. `id` is a mandatory filed and must be unique for each test. -1. The `test_name` specifies test definition from one of the Test TOML files. Node lists and time limits are optional. -1. If needed, `nodes` should be described as a list of node names as shown in a Slurm system. Alternatively, if groups are defined in the system schema, you can ask CloudAI to allocate a specific number of nodes from a specified partition and group. For example, `nodes = ['PARTITION:GROUP:16']`: 16 nodes are allocated from a group `GROUP`, from a partition `PARTITION`. -1. There are three types of dependencies: `start_post_comp`, `start_post_init` and `end_post_comp`. - 1. `start_post_comp` means that the current test should be started after a specific delay of the completion of the depending test. - 1. `start_post_init` means that the current test should start after the start of the depending test. - 1. `end_post_comp` means that the current test should be completed after the completion of the depending test. - - All dependencies are described as a pair of the depending test name and a delay. The name should be taken from the test name as set in the test scenario. The delay is described in the number of seconds. - - -To generate NCCL test commands without actual execution, use the `dry-run` mode. You can review `debug.log` (or other file specified with `--log-file`) to see the generated commands from CloudAI. Please note that group node allocations are not currently supported in the `dry-run` mode. -```bash -cloudai dry-run \ - --test-scenario myconfig/scenario.toml \ - --system-config myconfig/system.toml \ - --tests-dir myconfig/tests/ -``` - -You can run NCCL test experiments with the following command. Whenever you run CloudAI in the `run` mode, a new directory will be created under the results directory with the timestamp. In the directory, you can find the results from the test scenario including stdout and stderr. Once completed successfully, you can find generated reports under the directories as well. -```bash -cloudai run \ - --test-scenario myconfig/scenario.toml \ - --system-config myconfig/system.toml \ - --tests-dir myconfig/tests/ -``` - -### Test-in-Scenario -One can override some args or even fully define a workload inside a scenario file: -```toml -name = "nccl-test" - -[[Tests]] -id = "allreduce.in.scenario" -num_nodes = 1 -time_limit = "00:20:00" - -name = "nccl_test_all_reduce_single_node" -description = "all_reduce" -test_template_name = "NcclTest" - - [Tests.cmd_args] - subtest_name = "all_reduce_perf_mpi" - ngpus = 1 - minbytes = "8M" - maxbytes = "16G" - iters = 5 - warmup_iters = 3 - stepfactor = 2 - -[[Tests]] -id = "allreduce.override" -num_nodes = 1 -test_name = "nccl_test_all_reduce_single_node" -time_limit = "00:20:00" - - [Tests.cmd_args] - stepfactor = 4 -``` - -`allreduce.in.scenario` fully defines a workload, in this case `test_name` must not be set, while `name`, `description` and `test_template_name` must be set. - -`allreduce.override` overrides only `stepfactor` arg from the test defined in the tests dir. - -If a scenario contains only fully defined tests, `--tests-dir` arg is not required. - -## Step 7: Generate Reports -Once the test scenario is completed, you can generate reports using the following command: -```bash -cloudai generate-report \ - --test-scenario myconfig/scenario.toml \ - --system-config myconfig/system.toml \ - --tests-dir myconfig/tests/ \ - --result-dir results/2024-06-18_17-40-13/ -``` - -`--result-dir` accepts one scenario run result directory. - -# Describing a System in the System Schema -In this section, we introduce the concept of the system schema, explain the meaning of each field, and describe how the fields should be used. The system schema is a TOML file that allows users to define a system's configuration. - -```toml -name = "example-cluster" -scheduler = "slurm" - -install_path = "./install" -output_path = "./results" -default_partition = "partition_1" - -mpi = "pmix" -gpus_per_node = 8 -ntasks_per_node = 8 - -cache_docker_images_locally = true - -[[partitions]] -name = "partition_1" - - [[partitions.groups]] - name = "group_a" - nodes = ["node-[001-025]"] - - [[partitions.groups]] - name = "group_b" - nodes = ["node-[026-050]"] - -[[partitions]] -name = "partition_2" - -[global_env_vars] -# NCCL Specific Configurations -NCCL_IB_GID_INDEX = "3" -NCCL_IB_TIMEOUT = "20" -NCCL_IB_QPS_PER_CONNECTION = "4" - -# Device Visibility Configuration -MELLANOX_VISIBLE_DEVICES = "0,3,4,5,6,9,10,11" -CUDA_VISIBLE_DEVICES = "0,1,2,3,4,5,6,7" -``` - -## Field Descriptions -- **name**: Specifies the name of the system. Users can choose any name that is convenient for them. -- **scheduler**: Indicates the type of system. It should be one of the supported types, currently `slurm` or `standalone`. `slurm` refers to a system with the Slurm scheduler, while `standalone` refers to a single-node system without any slave nodes. Other values are possible depending on the available schedulers supported by CloudAI. -- **install_path**: Specifies the path where test prerequisites are installed. Docker images are downloaded to this path if the user chooses to cache Docker images. -- **output_path**: Defines the default path where outputs are stored. Whenever a user runs a test scenario, a new subdirectory will be created under this path. -- **default_partition**: Specifies the default partition where jobs are scheduled. -- **partitions**: Describes the available partitions and nodes within those partitions. - - **[optional] groups**: Within the same partition, users can define groups of nodes. The group concept can be used to allocate nodes from specific groups in a test scenario schema. For instance, this feature is useful for specifying topology awareness. Groups represents logical partitioning of nodes and users are responsible for ensuring no overlap across groups. -- **mpi**: Indicates the Process Management Interface (PMI) implementation to be used for inter-process communication. -- **gpus_per_node** and **ntasks_per_node**: These are Slurm arguments passed to the `sbatch` script and `srun`. -- **cache_docker_images_locally**: Specifies whether CloudAI should cache remote Docker images locally during installation. If set to `true`, CloudAI will cache the Docker images, enabling local access without needing to download them each time a test is run. This approach saves network bandwidth but requires more disk capacity. If set to `false`, CloudAI will allow Slurm to download the Docker images as needed when they are not cached locally by Slurm. -- **global_env_vars**: Lists all global environment variables that will be applied globally whenever tests are run. - -## Describing a System for RunAI Scheduler -When using RunAI as the scheduler, you need to specify additional fields in the system schema TOML file. Below is the list of required fields and how to set them: - -```toml -name = "runai-cluster" -scheduler = "runai" - -install_path = "./install" -output_path = "./results" - -base_url = "http://runai.example.com" # The URL of your RunAI system, typically the same as used for the web interface. -user_email = "your_email" # The email address used to log into the RunAI system. -app_id = "your_app_id" # Obtained by creating an application in the RunAI web interface. -app_secret = "your_app_secret" # Obtained together with the app_id. -project_id = "your_project_id" # Project ID assigned or created in the RunAI system (usually an integer). -cluster_id = "your_cluster_id" # Cluster ID in UUID format (e.g., a69928cc-ccaa-48be-bda9-482440f4d855). -``` -* After logging into the RunAI web interface, navigate to Access → Applications and create a new application to obtain app_id and app_secret. -* Use your assigned project and cluster IDs. Contact your administrator if they are not available. -* All other fields follow the same semantics as in the Slurm system schema (e.g., install_path, output_path). - -# Describing a Test Scenario in the Test Scenario Schema -A test scenario is a set of tests with specific dependencies between them. A test scenario is described in a TOML schema file. This is an example of a test scenario file: -```toml -name = "nccl-test" - -[[Tests]] -id = "Tests.1" -test_name = "nccl_test_all_reduce" -num_nodes = "2" -time_limit = "00:20:00" - -[[Tests]] -id = "Tests.2" -test_name = "nccl_test_all_gather" -num_nodes = "2" -time_limit = "00:20:00" - [[Tests.dependencies]] - type = "start_post_comp" - id = "Tests.1" - -[[Tests]] -id = "Tests.3" -templat_test = "nccl_test_reduce_scatter" -num_nodes = "2" -time_limit = "00:20:00" - [[Tests.dependencies]] - type = "start_post_comp" - id = "Tests.2" -``` - -The `name` field is the test scenario name, which can be any unique identifier for the scenario. Each test has a section name, following the convention `Tests.1`, `Tests.2`, etc., with an increasing index. The `name` of a test should be specified in this section and must correspond to an entry in the test schema. If a test in a test scenario is not present in the test schema, CloudAI will not be able to identify it. - -There are two ways to specify nodes: -- Using the `num_nodes` field as shown in the example. -- Specifying nodes explicitly like `nodes = ["node-001", "node-002"]` - -**Note:** When an explicit node list is provided (e.g., `nodes = ["node-001", "node-002"]`), CloudAI lets Slurm apply the arbitrary distribution policy for task placement. - - Alternatively, you can utilize the groups feature in the system schema to specify nodes like `nodes = ['PARTITION_NAME:GROUP_NAME:NUM_NODES']`, which allocates `num_nodes` from the group name in the specified partition. You can also use `nodes = ['PARTITION_NAME:GROUP_NAME:max_avail']`, which allocates all the available nodes from the group name in the specified partition. - -You can optionally specify a time limit in the Slurm format. Tests can have dependencies. If no dependencies are specified, all tests will run in parallel. - -CloudAI supports three types of dependencies: -- `start_post_init` -- `start_post_comp` -- `end_post_comp` - -Dependencies of a test can be described as a subsection of the test. It requires other tests' `id` and dependency `type`. - -- `start_post_init` means the test starts after the prior test begins, with a specified delay -- `start_post_comp` means the test starts after the prior test completes -- `end_post_comp` means the test ends when the prior test completes - - -# Configuring HTTP Data Repository -The HTTP Data Repository is currently supported for Slurm systems only. To enable access, you must update your system schema file and create a credential file in your CloudAI project's root directory. - -## Step 1: Update the System Schema File -Add the following section to your system schema TOML file (e.g., `system_schema.toml`): - -```toml -[data_repository] -endpoint = "https://my-data-endpoint.com" -``` - -Replace the endpoint with your actual data repository URL. - -## Step 2: Create the Credential File -In the root of your CloudAI project (i.e., the current working directory), create a file named `.cloudai.toml` with the following content: - -```toml -[data_repository] -token = "" -``` - -Replace `` with your actual token. - -## Step 3: Usage -Both the endpoint and token must be valid for the HTTP Data Repository to function correctly. If either is missing or incorrect, data will not be posted. - - -# Using Test Hooks in CloudAI - -A test hook in CloudAI is a specialized test that runs either before or after each main test in a scenario, providing flexibility to prepare the environment or clean up resources. Hooks are defined as pre-test or post-test and referenced in the test scenario’s TOML file using `pre_test` and `post_test` fields. -``` -name = "nccl-test" - -pre_test = "nccl_test_pre" -post_test = "nccl_test_post" - -[[Tests]] -id = "Tests.1" -test_name = "nccl_test_all_reduce" -num_nodes = "2" -time_limit = "00:20:00" -``` - -CloudAI organizes hooks in a dedicated directory structure: - -- Hook directory: All hook configurations reside in `conf/hook/` -- Hook test scenarios: Place pre-test hook and post-test hook scenario files in `conf/hook/` -- Hook tests: Place individual tests referenced in hooks within `conf/hook/test/` - -In the execution flow, pre-test hooks run before the main test, which only executes if the pre-test completes successfully. Post-test hooks follow the main test, provided the prior steps succeed. If a pre-test hook fails, the main test and its post-test hook are skipped. -``` -name = "nccl_test_pre" - -[[Tests]] -id = "Tests.1" -test_name = "nccl_test_all_reduce" -time_limit = "00:20:00" -``` - -# Downloading DeepSeek Weights -To run DeepSeek R1 tests in CloudAI, you must download the model weights in advance. These weights are distributed via the NVIDIA NGC Registry and must be manually downloaded using the NGC CLI. - -## Step 1: Install NGC CLI -Download and install the NGC CLI using the following commands: - -```bash -wget --content-disposition https://api.ngc.nvidia.com/v2/resources/nvidia/ngc-apps/ngc_cli/versions/3.64.2/files/ngccli_linux.zip -O ngccli_linux.zip -unzip ngccli_linux.zip -chmod u+x ngc-cli/ngc -echo "export PATH=\"$PATH:$(pwd)/ngc-cli\"" >> ~/.bash_profile && source ~/.bash_profile -``` - -This will make the `ngc` command available in your terminal. - -## Step 2: Configure NGC CLI -Authenticate your CLI with your NGC API key by running: - -```bash -ngc config set -``` - -When prompted, paste your API key, which you can obtain from [https://org.ngc.nvidia.com/setup](https://org.ngc.nvidia.com/setup). - -## Step 3: Download the Weights -Navigate to the directory where you want the DeepSeek model weights to be stored, then run: - -```bash -ngc registry model download-version nim/deepseek-ai/deepseek-r1-instruct:hf-5dde110-nim-fp8 --dest . -``` - -This command will create a folder named: - -``` -deepseek-r1-instruct_vhf-5dde110-nim-fp8/ -``` - -inside your current directory. - -## Step 4: Verify the Download -Ensure the full model has been downloaded by checking the folder size: - -```bash -du -sh deepseek-r1-instruct_vhf-5dde110-nim-fp8 -``` - -The expected size is approximately 642 GB. If it’s significantly smaller, remove the folder and re-run the download. - - -# Slurm specifics - -## Single sbatch vs per-case sbatch -CloudAI supports two modes for submitting Slurm jobs: - -1. (default) Per-case sbatch mode: each case is submitted as a separate sbatch job, allows flexible scheduling and dependency management. - - Suites best when cases can run in parallel or there are no dependencies between cases. -2. Single sbatch mode: all cases are submitted together in a single sbatch job and share the same nodes. Each next case starts after the previous one completes. To enable it one needs to pass `--single-sbatch` flag to `cloudai run` command (works only for Slurm systems). - - Suites best for jobs when cases need to run on the same nodes for performance reasons. - - There is not support for dependency management between cases yet, all jobs run one after another. - -Assuming two cases in a scenario like this: -```toml -[[Tests]] -id = "nccl.all_reduce" -test_name = "nccl-all_reduce" -num_nodes = 2 -time_limit = "00:20:00" - -[[Tests]] -id = "nccl.all_gather" -test_name = "nccl-all_gather" -num_nodes = 2 -time_limit = "00:20:00" -``` - -Regular output directory structure (some files are omitted for clarity): -```bash -$ tree results/scenario -results/scenario -├── nccl.all_gather -│ └── 0 -│ ├── cloudai_sbatch_script.sh -│ ├── env_vars.sh -│ ├── metadata/ -│ ├── stderr.txt -│ ├── stdout.txt -│ └── test-run.toml -└── nccl.all_reduce - └── 0 - ├── cloudai_sbatch_script.sh - ├── env_vars.sh - ├── metadata/ - ├── stderr.txt - ├── stdout.txt - └── test-run.toml -``` - -Single sbatch mode output directory structure: -```bash -tree results/scenario -results/scenario -├── cloudai_sbatch_script.sh -├── common.err -├── common.out -├── metadata/ -├── nccl.all_gather -│   └── 0 -│   ├── env_vars.sh -│   ├── stderr.txt -│   ├── stdout.txt -│   └── test-run.toml -├── nccl.all_reduce -│   └── 0 -│   ├── env_vars.sh -│   ├── stderr.txt -│   ├── stdout.txt -│   └── test-run.toml -└── slurm-job.toml -``` - -Most of the files are the same: output files, env vars script, test run metadata. Difference for single sbatch mode is that `slurm-job.toml` is created for entires job as well as `cloudai_sbatch_script.sh`. Plus extra `common.err`/`common.out` files are created for general sbatch outputs. - - -## Extra srun and sbatch arguments -CloudAI forms sbatch script and srun commands following internal rules. Users can affect the generation but setting special arguments in System TOML file. - -For example (in a System TOML file):, -```toml -extra_sbatch_args = [ - "--section=4", - "--other-arg val" -] -``` -will result in sbatch file content like this: -```bash -... # CloudAI set sbatch arguments -#SBATCH --section=4 -#SBATCH --other-arg val -... -``` - -Another example (in a System TOML file): -```toml -extra_srun_args = "--arg=val --other-arg=other-val" -``` -will result in srun command inside sbatch script like this: -```bash -srun ... --arg=val --other-arg=other-val ... -``` - -## Container mounts -CloudAI runs all slurm jobs using containers. To simplify file system related tasks, CloudAI mounts the following directories into the container: -1. Test output directory (`///`, like `results/scenario_2024-06-18_17-40-13/Tests.1/0`) is mounted as `/cloudai_run_results`. -1. Test specific mounts can be specified in TOML files: - ```toml - extra_container_mounts = [ - "/path/to/mount1:/path/in/container1", - "/path/to/mount2:/path/in/container2" - ] - - [cmd_args] - ... - ``` - These mounts are not verified for validity and do not override default mounts. -1. Test specific mounts can be mounted in-code. - -## Head node without shared storage available on compute nodes -When compute nodes don't share file system with head node, `--enable-cache-without-check` for `run` and `dry-run` skips real check for cache existence, but still builds all paths correctly. The flow is like this: - -1. _[on the head node]_ run `cloudai install` -1. _[on the head node]_ copy cache to compute nodes -1. Modify system.toml to set compute nodes' installation root -1. Run `cloudai run --enable-cache-without-check ...` - -# Dev details -`SlurmCommandGenStrategy` defines abstract method `_container_mounts(tr: TestRun)` that must be implemented by every subclass. This method is used in `SlurmCommandGenStrategy.container_mounts(tr: TestRun)` (defined as `@final`) where mounts like `/cloudai_run_results` (default mount), `TestDefinition.extra_container_mounts` (from Test TOML) and test specific mounts (defined in-code) are added. - -# Nsys tracing -Users can enable Nsys tracing for any workload when running via Slurm. Note, that `nsys` should be available on the compute nodes, CloudAI doesn't manage it. - -Configuration fields are: -```py -enable: bool = True -nsys_binary: str = "nsys" -task: str = "profile" -output: Optional[str] = None -sample: Optional[str] = None -trace: Optional[str] = None -force_overwrite: Optional[bool] = None -capture_range: Optional[str] = None -capture_range_end: Optional[str] = None -cuda_graph_trace: Optional[str] = None -gpu_metrics_devices: Optional[str] = None -extra_args: list[str] = [] -``` -Fields with `None` value are not passed to `nsys` command. - -# Troubleshooting -In this section, we will guide you through identifying the root cause of issues, determining whether they stem from system infrastructure or a bug in CloudAI. - -## Identifying the Root Cause -If you encounter issues running a command, start by reading the error message to understand the root cause. We strive to make our error messages and exception messages as readable and interpretable as possible. - -## System Infrastructure vs. CloudAI Bugs -To determine whether an issue is due to system infrastructure or a CloudAI bug, follow these steps: - -1. **Check stdout Messages:** - If CloudAI fails to run a test successfully, it will be indicated in the stdout messages that a test has failed. - -2. **Review Log Files:** - - Navigate to the output directory and review `debug.log`, stdout, and stderr files - - `debug.log` contains detailed steps executed by CloudAI, including generated commands, executed commands, and error messages - -3. **Analyze Error Messages:** - By examining the error messages in the log files, you can understand the type of errors CloudAI encountered. - -4. **Examine Output Directory:** - If a test fails without explicit error messages, review the output directory of the failed test. Look for `stdout.txt`, `stderr.txt`, or any generated files to understand the failure reason. - -5. **Manual Rerun of Tests:** - - To manually rerun the test, consult the `debug.log` for the command CloudAI executed - - Look for an `sbatch` command with a generated `sbatch` script - - Execute the command manually to debug further - -If the problem persists, please report the issue at [https://github.com/NVIDIA/cloudai/issues/new/choose](https://github.com/NVIDIA/cloudai/issues/new/choose). When you report an issue, ensure it is reproducible. Follow the issue template and provide any necessary details, such as the hash commit used, system settings, any changes in the schema files, and the command. diff --git a/doc/USER_GUIDE.rst b/doc/USER_GUIDE.rst new file mode 100644 index 000000000..09e11b8c1 --- /dev/null +++ b/doc/USER_GUIDE.rst @@ -0,0 +1,736 @@ +CloudAI User Guide +================== + +The purpose of this guide is to help users use CloudAI. The guide covers topics such as adding new tests and downloading datasets for running NeMo-launcher. + +Step 1: Create a Docker Image +----------------------------- + +#. **Set Up the GitLab Repository:** Start by setting up a repository on GitLab to host your docker image. For this example, use ``gitlab-url.com/cloudai/nccl-test``. + +#. **Write the Dockerfile:** + + .. code-block:: dockerfile + + FROM nvcr.io/nvidia/pytorch:24.02-py3 + +#. **Build and Push the Docker Image:** Build the docker image with the Dockerfile and upload it to the designated repository: + + .. code-block:: bash + + docker build -t gitlab-url.com/cloudai/nccl-test . + docker push gitlab-url.com/cloudai/nccl-test + +#. **Verify the Docker Image:** Test the docker image by running it with ``srun`` to verify that the docker image runs correctly: + + .. code-block:: bash + + srun \ + --mpi=pmix \ + --container-image=gitlab-url.com/cloudai/nccl-test \ + all_reduce_perf_mpi \ + --nthreads 1 \ + --ngpus 1 \ + --minbytes 128 \ + --maxbytes 16G \ + --stepbytes 1M \ + --op sum \ + --datatype float \ + --root 0 \ + --iters 100 \ + --warmup_iters 50 \ + --agg_iters 1 \ + --average 1 \ + --parallel_init 0 \ + --check 1 \ + --blocking 0 \ + --cudagraph 0 \ + --stepfactor 2 + +Step 2: Prepare Configuration Files +----------------------------------- + +CloudAI is fully configurable via a set of TOML configuration files. You can find examples of these files under ``conf/common``. In this guide, we will use the following configuration files: + +#. ``myconfig/system.toml`` - Describes the system configuration. +#. ``myconfig/tests/nccl_test.toml`` - Describes the test to run. +#. ``myconfig/scenario.toml`` - Describes the test scenario configuration. + +Step 3: Test Definition +----------------------- + +Test definition is a Pydantic model that describes the arguments of a test. Such models should be inherited from the ``TestDefinition`` class: + +.. code-block:: python + + class MyTestCmdArgs(CmdArgs): + an_arg: str | list[str] + docker_image_url: str = "nvcr.io/nvidia/pytorch:24.02-py3" + + class MyTestDefinition(TestDefinition): + cmd_args: MyTestCmdArgs + +Notice that ``cmd_args.docker_image_url`` uses ``nvcr.io/nvidia/pytorch:24.02-py3``, but you can use the Docker image from Step 1. + +``an_arg`` has mixed type of ``str | list[str]``, so in a TOML config it can be defined as either: + +.. code-block:: toml + + an_arg = "a single string" + +or + +.. code-block:: toml + + an_arg = ["list", "of", "strings"] + +When a list is used, CloudAI will automatically generate multiple test cases for each value in the list. + +A custom test definition should be registered to handle relevant Test Configs. For this, ``Registry()`` object is used: + +.. code-block:: python + + Registry().add_test_definition("MyTest", MyTestDefinition) + Registry().add_test_template("MyTest", MyTest) + +Relevant Test Configs should specify ``test_template_name = MyTest`` to use the custom test definition. + +Step 4: System Configuration +---------------------------- + +System configuration describes the system configuration. You can find more examples of system configs under ``conf/common/system/``. Our example will be small for demonstration purposes. Below is the ``myconfig/system.toml`` file: + +.. code-block:: toml + + name = "my-cluster" + scheduler = "slurm" + + install_path = "./install" + output_path = "./results" + cache_docker_images_locally = true + default_partition = "" + + mpi = "pmix" + gpus_per_node = 8 + ntasks_per_node = 8 + + [[partitions]] + name = "partition_1" + +Replace ```` with the name of the partition you want to use. You can find the partition name by running ``sinfo`` on the cluster. + +Step 5: Test Configuration +-------------------------- + +Test configuration describes a particular test configuration to be run. It is based on test definition and will be used in a test scenario. Below is the ``myconfig/tests/nccl_test.toml`` file, definition is based on the built-in ``NcclTest`` definition: + +.. code-block:: toml + + name = "nccl_test_all_reduce_single_node" + description = "all_reduce" + test_template_name = "NcclTest" + + [cmd_args] + subtest_name = "all_reduce_perf_mpi" + ngpus = 1 + minbytes = "8M" + maxbytes = "16G" + iters = 5 + warmup_iters = 3 + stepfactor = 2 + +You can find more examples under ``conf/common/test``. In a test schema file, you can adjust arguments as shown above. In the ``cmd_args`` section, you can provide different values other than the default values for each argument. In ``extra_cmd_args``, you can provide additional arguments that will be appended after the NCCL test command. You can specify additional environment variables in the ``extra_env_vars`` section. + +Step 6: Run Experiments +----------------------- + +Test Scenario uses test description from Step 5. Below is the ``myconfig/scenario.toml`` file: + +.. code-block:: toml + + name = "nccl-test" + + [[Tests]] + id = "allreduce.1" + num_nodes = 1 + test_name = "nccl_test_all_reduce_single_node" + time_limit = "00:20:00" + + [[Tests]] + id = "allreduce.2" + num_nodes = 1 + test_name = "nccl_test_all_reduce_single_node" + time_limit = "00:20:00" + [[Tests.dependencies]] + type = "start_post_comp" + id = "Tests.1" + +Notes on the test scenario: + +#. ``id`` is a mandatory field and must be unique for each test. +#. The ``test_name`` specifies test definition from one of the Test TOML files. Node lists and time limits are optional. +#. If needed, ``nodes`` should be described as a list of node names as shown in a Slurm system. Alternatively, if groups are defined in the system schema, you can ask CloudAI to allocate a specific number of nodes from a specified partition and group. For example, ``nodes = ['PARTITION:GROUP:16']`` allocates 16 nodes from group ``GROUP`` and partition ``PARTITION``. +#. There are three types of dependencies: ``start_post_comp``, ``start_post_init`` and ``end_post_comp``. + + - ``start_post_comp`` means that the current test should be started after a specific delay of the completion of the depending test. + - ``start_post_init`` means that the current test should start after the start of the depending test. + - ``end_post_comp`` means that the current test should be completed after the completion of the depending test. + + All dependencies are described as a pair of the depending test name and a delay. The name should be taken from the test name as set in the test scenario. The delay is described in seconds. + +To generate NCCL test commands without actual execution, use the ``dry-run`` mode. You can review ``debug.log`` (or other file specified with ``--log-file``) to see the generated commands from CloudAI. Please note that group node allocations are not currently supported in the ``dry-run`` mode. + +.. code-block:: bash + + cloudai dry-run \ + --test-scenario myconfig/scenario.toml \ + --system-config myconfig/system.toml \ + --tests-dir myconfig/tests/ + +You can run NCCL test experiments with the following command. Whenever you run CloudAI in the ``run`` mode, a new directory will be created under the results directory with the timestamp. In the directory, you can find the results from the test scenario including stdout and stderr. Once completed successfully, you can find generated reports under the directories as well. + +.. code-block:: bash + + cloudai run \ + --test-scenario myconfig/scenario.toml \ + --system-config myconfig/system.toml \ + --tests-dir myconfig/tests/ + +Test-in-Scenario +---------------- + +One can override some args or even fully define a workload inside a scenario file: + +.. code-block:: toml + + name = "nccl-test" + + [[Tests]] + id = "allreduce.in.scenario" + num_nodes = 1 + time_limit = "00:20:00" + + name = "nccl_test_all_reduce_single_node" + description = "all_reduce" + test_template_name = "NcclTest" + + [Tests.cmd_args] + subtest_name = "all_reduce_perf_mpi" + ngpus = 1 + minbytes = "8M" + maxbytes = "16G" + iters = 5 + warmup_iters = 3 + stepfactor = 2 + + [[Tests]] + id = "allreduce.override" + num_nodes = 1 + test_name = "nccl_test_all_reduce_single_node" + time_limit = "00:20:00" + + [Tests.cmd_args] + stepfactor = 4 + +``allreduce.in.scenario`` fully defines a workload; in this case ``test_name`` must not be set, while ``name``, ``description`` and ``test_template_name`` must be set. + +``allreduce.override`` overrides only ``stepfactor`` arg from the test defined in the tests directory. + +If a scenario contains only fully defined tests, ``--tests-dir`` arg is not required. + +Step 7: Generate Reports +------------------------ + +Once the test scenario is completed, you can generate reports using the following command: + +.. code-block:: bash + + cloudai generate-report \ + --test-scenario myconfig/scenario.toml \ + --system-config myconfig/system.toml \ + --tests-dir myconfig/tests/ \ + --result-dir results/2024-06-18_17-40-13/ + +``--result-dir`` accepts one scenario run result directory. + +Describing a System in the System Schema +---------------------------------------- + +In this section, we introduce the concept of the system schema, explain the meaning of each field, and describe how the fields should be used. The system schema is a TOML file that allows users to define a system's configuration. + +.. code-block:: toml + + name = "example-cluster" + scheduler = "slurm" + + install_path = "./install" + output_path = "./results" + default_partition = "partition_1" + + mpi = "pmix" + gpus_per_node = 8 + ntasks_per_node = 8 + + cache_docker_images_locally = true + + [[partitions]] + name = "partition_1" + + [[partitions.groups]] + name = "group_a" + nodes = ["node-[001-025]"] + + [[partitions.groups]] + name = "group_b" + nodes = ["node-[026-050]"] + + [[partitions]] + name = "partition_2" + + [global_env_vars] + # NCCL Specific Configurations + NCCL_IB_GID_INDEX = "3" + NCCL_IB_TIMEOUT = "20" + NCCL_IB_QPS_PER_CONNECTION = "4" + + # Device Visibility Configuration + MELLANOX_VISIBLE_DEVICES = "0,3,4,5,6,9,10,11" + CUDA_VISIBLE_DEVICES = "0,1,2,3,4,5,6,7" + +Field Descriptions +------------------ + +- **name**: Specifies the name of the system. Users can choose any name that is convenient for them. +- **scheduler**: Indicates the type of system. It should be one of the supported types, currently ``slurm`` or ``standalone``. ``slurm`` refers to a system with the Slurm scheduler, while ``standalone`` refers to a single-node system without any slave nodes. Other values are possible depending on the available schedulers supported by CloudAI. +- **install_path**: Specifies the path where test prerequisites are installed. Docker images are downloaded to this path if the user chooses to cache Docker images. +- **output_path**: Defines the default path where outputs are stored. Whenever a user runs a test scenario, a new subdirectory will be created under this path. +- **default_partition**: Specifies the default partition where jobs are scheduled. +- **partitions**: Describes the available partitions and nodes within those partitions. + + - **[optional] groups**: Within the same partition, users can define groups of nodes. The group concept can be used to allocate nodes from specific groups in a test scenario schema. For instance, this feature is useful for specifying topology awareness. Groups represent logical partitioning of nodes and users are responsible for ensuring no overlap across groups. + +- **mpi**: Indicates the Process Management Interface (PMI) implementation to be used for inter-process communication. +- **gpus_per_node** and **ntasks_per_node**: These are Slurm arguments passed to the ``sbatch`` script and ``srun``. +- **cache_docker_images_locally**: Specifies whether CloudAI should cache remote Docker images locally during installation. If set to ``true``, CloudAI will cache the Docker images, enabling local access without needing to download them each time a test is run. This approach saves network bandwidth but requires more disk capacity. If set to ``false``, CloudAI will allow Slurm to download the Docker images as needed when they are not cached locally by Slurm. +- **global_env_vars**: Lists all global environment variables that will be applied globally whenever tests are run. + +Describing a System for RunAI Scheduler +--------------------------------------- + +When using RunAI as the scheduler, you need to specify additional fields in the system schema TOML file. Below is the list of required fields and how to set them: + +.. code-block:: toml + + name = "runai-cluster" + scheduler = "runai" + + install_path = "./install" + output_path = "./results" + + base_url = "http://runai.example.com" # The URL of your RunAI system, typically the same as used for the web interface. + user_email = "your_email" # The email address used to log into the RunAI system. + app_id = "your_app_id" # Obtained by creating an application in the RunAI web interface. + app_secret = "your_app_secret" # Obtained together with the app_id. + project_id = "your_project_id" # Project ID assigned or created in the RunAI system (usually an integer). + cluster_id = "your_cluster_id" # Cluster ID in UUID format (e.g., a69928cc-ccaa-48be-bda9-482440f4d855). + +* After logging into the RunAI web interface, navigate to Access → Applications and create a new application to obtain ``app_id`` and ``app_secret``. +* Use your assigned project and cluster IDs. Contact your administrator if they are not available. +* All other fields follow the same semantics as in the Slurm system schema (e.g., ``install_path``, ``output_path``). + +Describing a Test Scenario in the Test Scenario Schema +------------------------------------------------------ + +A test scenario is a set of tests with specific dependencies between them. A test scenario is described in a TOML schema file. This is an example of a test scenario file: + +.. code-block:: toml + + name = "nccl-test" + + [[Tests]] + id = "Tests.1" + test_name = "nccl_test_all_reduce" + num_nodes = "2" + time_limit = "00:20:00" + + [[Tests]] + id = "Tests.2" + test_name = "nccl_test_all_gather" + num_nodes = "2" + time_limit = "00:20:00" + [[Tests.dependencies]] + type = "start_post_comp" + id = "Tests.1" + + [[Tests]] + id = "Tests.3" + templat_test = "nccl_test_reduce_scatter" + num_nodes = "2" + time_limit = "00:20:00" + [[Tests.dependencies]] + type = "start_post_comp" + id = "Tests.2" + +The ``name`` field is the test scenario name, which can be any unique identifier for the scenario. Each test has a section name, following the convention ``Tests.1``, ``Tests.2``, etc., with an increasing index. The ``name`` of a test should be specified in this section and must correspond to an entry in the test schema. If a test in a test scenario is not present in the test schema, CloudAI will not be able to identify it. + +There are two ways to specify nodes: + +- Using the ``num_nodes`` field as shown in the example. +- Specifying nodes explicitly like ``nodes = ["node-001", "node-002"]`` + +**Note:** When an explicit node list is provided (e.g., ``nodes = ["node-001", "node-002"]``), CloudAI lets Slurm apply the arbitrary distribution policy for task placement. + +Alternatively, you can utilize the groups feature in the system schema to specify nodes like ``nodes = ['PARTITION_NAME:GROUP_NAME:NUM_NODES']``, which allocates ``num_nodes`` from the group name in the specified partition. You can also use ``nodes = ['PARTITION_NAME:GROUP_NAME:max_avail']``, which allocates all the available nodes from the group name in the specified partition. + +You can optionally specify a time limit in the Slurm format. Tests can have dependencies. If no dependencies are specified, all tests will run in parallel. + +CloudAI supports three types of dependencies: + +- ``start_post_init`` +- ``start_post_comp`` +- ``end_post_comp`` + +Dependencies of a test can be described as a subsection of the test. It requires other tests' ``id`` and dependency ``type``. + +- ``start_post_init`` means the test starts after the prior test begins, with a specified delay. +- ``start_post_comp`` means the test starts after the prior test completes. +- ``end_post_comp`` means the test ends when the prior test completes. + +Configuring HTTP Data Repository +-------------------------------- + +The HTTP Data Repository is currently supported for Slurm systems only. To enable access, you must update your system schema file and create a credential file in your CloudAI project's root directory. + +Step 1: Update the System Schema File +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +Add the following section to your system schema TOML file (e.g., ``system_schema.toml``): + +.. code-block:: toml + + [data_repository] + endpoint = "https://my-data-endpoint.com" + +Replace the endpoint with your actual data repository URL. + +Step 2: Create the Credential File +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +In the root of your CloudAI project (i.e., the current working directory), create a file named ``.cloudai.toml`` with the following content: + +.. code-block:: toml + + [data_repository] + token = "" + +Replace ```` with your actual token. + +Step 3: Usage +~~~~~~~~~~~~~ + +Both the endpoint and token must be valid for the HTTP Data Repository to function correctly. If either is missing or incorrect, data will not be posted. + +Using Test Hooks in CloudAI +--------------------------- + +A test hook in CloudAI is a specialized test that runs either before or after each main test in a scenario, providing flexibility to prepare the environment or clean up resources. Hooks are defined as pre-test or post-test and referenced in the test scenario’s TOML file using ``pre_test`` and ``post_test`` fields. + +.. code-block:: toml + + name = "nccl-test" + + pre_test = "nccl_test_pre" + post_test = "nccl_test_post" + + [[Tests]] + id = "Tests.1" + test_name = "nccl_test_all_reduce" + time_limit = "00:20:00" + +CloudAI organizes hooks in a dedicated directory structure: + +- Hook directory: All hook configurations reside in ``conf/hook/``. +- Hook test scenarios: Place pre-test hook and post-test hook scenario files in ``conf/hook/``. +- Hook tests: Place individual tests referenced in hooks within ``conf/hook/test/``. + +In the execution flow, pre-test hooks run before the main test, which only executes if the pre-test completes successfully. Post-test hooks follow the main test, provided the prior steps succeed. If a pre-test hook fails, the main test and its post-test hook are skipped. + +.. code-block:: toml + + name = "nccl_test_pre" + + [[Tests]] + id = "Tests.1" + test_name = "nccl_test_all_reduce" + time_limit = "00:20:00" + +Downloading DeepSeek Weights +---------------------------- + +To run DeepSeek R1 tests in CloudAI, you must download the model weights in advance. These weights are distributed via the NVIDIA NGC Registry and must be manually downloaded using the NGC CLI. + +Step 1: Install NGC CLI +~~~~~~~~~~~~~~~~~~~~~~~ + +Download and install the NGC CLI using the following commands: + +.. code-block:: bash + + wget --content-disposition https://api.ngc.nvidia.com/v2/resources/nvidia/ngc-apps/ngc_cli/versions/3.64.2/files/ngccli_linux.zip -O ngccli_linux.zip + unzip ngccli_linux.zip + chmod u+x ngc-cli/ngc + echo "export PATH=\"$PATH:$(pwd)/ngc-cli\"" >> ~/.bash_profile && source ~/.bash_profile + +This will make the ``ngc`` command available in your terminal. + +Step 2: Configure NGC CLI +~~~~~~~~~~~~~~~~~~~~~~~~~ + +Authenticate your CLI with your NGC API key by running: + +.. code-block:: bash + + ngc config set + +When prompted, paste your API key, which you can obtain from https://org.ngc.nvidia.com/setup. + +Step 3: Download the Weights +~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +Navigate to the directory where you want the DeepSeek model weights to be stored, then run: + +.. code-block:: bash + + ngc registry model download-version nim/deepseek-ai/deepseek-r1-instruct:hf-5dde110-nim-fp8 --dest . + +This command will create a folder named: + +.. code-block:: text + + deepseek-r1-instruct_vhf-5dde110-nim-fp8/ + +inside your current directory. + +Step 4: Verify the Download +~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +Ensure the full model has been downloaded by checking the folder size: + +.. code-block:: bash + + du -sh deepseek-r1-instruct_vhf-5dde110-nim-fp8 + +The expected size is approximately 642 GB. If it’s significantly smaller, remove the folder and re-run the download. + +Slurm specifics +--------------- + +Single sbatch vs per-case sbatch +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +CloudAI supports two modes for submitting Slurm jobs: + +1. (default) Per-case sbatch mode: each case is submitted as a separate sbatch job, allowing flexible scheduling and dependency management. + + - Suits best when cases can run in parallel or there are no dependencies between cases. + +2. Single sbatch mode: all cases are submitted together in a single sbatch job and share the same nodes. Each next case starts after the previous one completes. To enable it one needs to pass ``--single-sbatch`` flag to ``cloudai run`` command (works only for Slurm systems). + + - Suits best for jobs when cases need to run on the same nodes for performance reasons. + - There is no support for dependency management between cases yet; all jobs run one after another. + +Assuming two cases in a scenario like this: + +.. code-block:: toml + + [[Tests]] + id = "nccl.all_reduce" + test_name = "nccl-all_reduce" + num_nodes = 2 + time_limit = "00:20:00" + + [[Tests]] + id = "nccl.all_gather" + test_name = "nccl-all_gather" + num_nodes = 2 + time_limit = "00:20:00" + +Regular output directory structure (some files are omitted for clarity): + +.. code-block:: bash + + $ tree results/scenario + results/scenario + ├── nccl.all_gather + │ └── 0 + │ ├── cloudai_sbatch_script.sh + │ ├── env_vars.sh + │ ├── metadata/ + │ ├── stderr.txt + │ ├── stdout.txt + │ └── test-run.toml + └── nccl.all_reduce + └── 0 + ├── cloudai_sbatch_script.sh + ├── env_vars.sh + ├── metadata/ + ├── stderr.txt + ├── stdout.txt + └── test-run.toml + +Single sbatch mode output directory structure: + +.. code-block:: bash + + $ tree results/scenario + results/scenario + ├── cloudai_sbatch_script.sh + ├── common.err + ├── common.out + ├── metadata/ + ├── nccl.all_gather + │ └── 0 + │ ├── env_vars.sh + │ ├── stderr.txt + │ ├── stdout.txt + │ └── test-run.toml + ├── nccl.all_reduce + │ └── 0 + │ ├── env_vars.sh + │ ├── stderr.txt + │ ├── stdout.txt + │ └── test-run.toml + └── slurm-job.toml + +Most of the files are the same: output files, env vars script, test run metadata. The difference for single sbatch mode is that ``slurm-job.toml`` is created for the entire job as well as ``cloudai_sbatch_script.sh``. Extra ``common.err``/``common.out`` files are created for general sbatch outputs. + +Extra srun and sbatch arguments +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +CloudAI forms sbatch script and srun commands following internal rules. Users can affect the generation by setting special arguments in the system TOML file. + +For example (in a system TOML file): + +.. code-block:: toml + + extra_sbatch_args = [ + "--section=4", + "--other-arg val" + ] + +will result in sbatch file content like this: + +.. code-block:: bash + + ... # CloudAI set sbatch arguments + #SBATCH --section=4 + #SBATCH --other-arg val + ... + +Another example (in a system TOML file): + +.. code-block:: toml + + extra_srun_args = "--arg=val --other-arg=other-val" + +will result in srun command inside sbatch script like this: + +.. code-block:: bash + + srun ... --arg=val --other-arg=other-val ... + +Container mounts +~~~~~~~~~~~~~~~~ + +CloudAI runs all slurm jobs using containers. To simplify file system related tasks, CloudAI mounts the following directories into the container: + +1. Test output directory (``///``, like ``results/scenario_2024-06-18_17-40-13/Tests.1/0``) is mounted as ``/cloudai_run_results``. +2. Test specific mounts can be specified in TOML files: + + .. code-block:: toml + + extra_container_mounts = [ + "/path/to/mount1:/path/in/container1", + "/path/to/mount2:/path/in/container2" + ] + + [cmd_args] + ... + + These mounts are not verified for validity and do not override default mounts. + +3. Test specific mounts can be mounted in-code. + +Head node without shared storage available on compute nodes +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +When compute nodes don't share file system with head node, ``--enable-cache-without-check`` for ``run`` and ``dry-run`` skips the real check for cache existence, but still builds all paths correctly. The flow is like this: + +1. *[on the head node]* run ``cloudai install``. +2. *[on the head node]* copy cache to compute nodes. +3. Modify ``system.toml`` to set compute nodes' installation root. +4. Run ``cloudai run --enable-cache-without-check ...``. + +Dev details +----------- + +``SlurmCommandGenStrategy`` defines abstract method ``_container_mounts(tr: TestRun)`` that must be implemented by every subclass. This method is used in ``SlurmCommandGenStrategy.container_mounts(tr: TestRun)`` (defined as ``@final``) where mounts like ``/cloudai_run_results`` (default mount), ``TestDefinition.extra_container_mounts`` (from Test TOML) and test specific mounts (defined in-code) are added. + +Nsys tracing +------------ + +Users can enable Nsys tracing for any workload when running via Slurm. Note that ``nsys`` should be available on the compute nodes; CloudAI doesn't manage it. + +Configuration fields are: + +.. code-block:: python + + enable: bool = True + nsys_binary: str = "nsys" + task: str = "profile" + output: Optional[str] = None + sample: Optional[str] = None + trace: Optional[str] = None + force_overwrite: Optional[bool] = None + capture_range: Optional[str] = None + capture_range_end: Optional[str] = None + cuda_graph_trace: Optional[str] = None + gpu_metrics_devices: Optional[str] = None + extra_args: list[str] = [] + +Fields with ``None`` value are not passed to ``nsys`` command. + +Troubleshooting +--------------- + +In this section, we will guide you through identifying the root cause of issues, determining whether they stem from system infrastructure or a bug in CloudAI. + +Identifying the Root Cause +~~~~~~~~~~~~~~~~~~~~~~~~~~ + +If you encounter issues running a command, start by reading the error message to understand the root cause. We strive to make our error messages and exception messages as readable and interpretable as possible. + +System Infrastructure vs. CloudAI Bugs +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +To determine whether an issue is due to system infrastructure or a CloudAI bug, follow these steps: + +1. **Check stdout Messages:** If CloudAI fails to run a test successfully, it will be indicated in the stdout messages that a test has failed. + +2. **Review Log Files:** + + - Navigate to the output directory and review ``debug.log``, stdout, and stderr files. + - ``debug.log`` contains detailed steps executed by CloudAI, including generated commands, executed commands, and error messages. + +3. **Analyze Error Messages:** By examining the error messages in the log files, you can understand the type of errors CloudAI encountered. + +4. **Examine Output Directory:** If a test fails without explicit error messages, review the output directory of the failed test. Look for ``stdout.txt``, ``stderr.txt``, or any generated files to understand the failure reason. + +5. **Manual Rerun of Tests:** + + - To manually rerun the test, consult the ``debug.log`` for the command CloudAI executed. + - Look for an ``sbatch`` command with a generated ``sbatch`` script. + - Execute the command manually to debug further. + +If the problem persists, please report the issue at https://github.com/NVIDIA/cloudai/issues/new/choose. When you report an issue, ensure it is reproducible. Follow the issue template and provide any necessary details, such as the hash commit used, system settings, any changes in the schema files, and the command. + diff --git a/doc/conf.py b/doc/conf.py index 3638a1760..b5e3a57f6 100644 --- a/doc/conf.py +++ b/doc/conf.py @@ -48,10 +48,10 @@ def setup(app): # https://www.sphinx-doc.org/en/master/usage/configuration.html#project-information project = "CloudAI" -copyright = "2025, NVIDIA CORPORATION & AFFILIATES" +copyright = "2026, NVIDIA CORPORATION & AFFILIATES" author = "NVIDIA CORPORATION & AFFILIATES" -version = "1.4.0-beta" -release = "1.4.0-beta" +version = "1.5.0-beta" +release = "1.5.0-beta" # -- General configuration --------------------------------------------------- # https://www.sphinx-doc.org/en/master/usage/configuration.html#general-configuration @@ -61,7 +61,6 @@ def setup(app): "sphinx.ext.viewcode", "sphinx.ext.napoleon", "sphinx.ext.autosummary", - "myst_parser", "sphinxcontrib.mermaid", "sphinx_copybutton", ] @@ -84,21 +83,12 @@ def setup(app): html_theme = "nvidia_sphinx_theme" -# MyST parser configuration -myst_enable_extensions = [ - "deflist", - "colon_fence", - "html_image", -] - -# Configure MyST to handle code blocks as directives -myst_fence_as_directive = ["mermaid"] - # Mermaid configuration mermaid_version = "latest" mermaid_init_js = "mermaid.initialize({startOnLoad:true});" +mermaid_output_format = "raw" # render in-browser without mermaid-cli # Set the root document to index root_doc = "index" -source_suffix = [".rst", ".md"] +source_suffix = [".rst"] diff --git a/doc/index.md b/doc/index.md deleted file mode 100644 index 904b9226f..000000000 --- a/doc/index.md +++ /dev/null @@ -1,137 +0,0 @@ -# CloudAI Benchmark Framework - -CloudAI benchmark framework aims to develop an industry standard benchmark focused on grading Data Center (DC) scale AI systems in the Cloud. The primary motivation is to provide automated benchmarking on various systems. - -## Get Started -```bash -git clone git@github.com:NVIDIA/cloudai.git -cd cloudai -uv run cloudai --help -``` - -**Note**: For instructions for setting up access for `enroot`, see [installation guide](./workloads_requirements_installation.rst). - -### `pip`-based Installation -See required Python version in the `.python-version` file and make sure you have it installed (For Installation, see [Custom Python version](#install-custom-python-version)). Follow these steps: -```bash -git clone git@github.com:NVIDIA/cloudai.git -cd cloudai -python -m venv venv -source venv/bin/activate -pip install -e . -``` - -(install-custom-python-version)= -### Install Custom Python Version -If your system python version is not supported, you can install a custom version using [uv](https://docs.astral.sh/uv/getting-started/installation/) tool: -```bash -curl -LsSf https://astral.sh/uv/install.sh | sh -source $HOME/.local/bin/env -uv venv --seed # this will pick up the python version from .python-version file - # --seed will install pip and setuptools -source .venv/bin/activate -``` - - -## Key Concepts -CloudAI operates on three main schemas: - -- **System Schema**: Describes the system, including the scheduler type, node list, and global environment variables -- **Test Schema**: An instance of a test template with custom arguments and environment variables -- **Test Scenario Schema**: A set of tests with dependencies and additional descriptions about the test scenario - -These schemas enable CloudAI to be flexible and compatible with different systems and configurations. - -## CloudAI Modes Usage Examples - -Global options for `cloudai` command: -- `--log-file `: specify a file to log output, by default `debug.log` in the current directory is used. Contains log entries of level `DEBUG` and higher. -- `--log-level `: specify logging level for standard output, default is `INFO`. - -(run)= -### run -This mode runs workloads. It automatically installs prerequisites if they are not met. - -```bash -cloudai run\ - --system-config conf/common/system/example_slurm_cluster.toml\ - --tests-dir conf/common/test\ - --test-scenario conf/common/test_scenario/sleep.toml -``` - -(dry-run)= -### dry-run -This mode simulates running experiments without actually executing them. This is useful for verifying configurations and testing experiment setups. - -```bash -cloudai dry-run\ - --system-config conf/common/system/example_slurm_cluster.toml\ - --tests-dir conf/common/test\ - --test-scenario conf/common/test_scenario/sleep.toml -``` - -(generate-report)= -### generate-report -This mode generates reports under the scenario directory. It automatically runs as part of the `run` mode after experiments are completed. - -```bash -cloudai generate-report\ - --system-config conf/common/system/example_slurm_cluster.toml\ - --tests-dir conf/common/test\ - --test-scenario conf/common/test_scenario/sleep.toml\ - --result-dir /path/to/result_directory -``` - -(install)= -### install -This mode installs test prerequisites. For more details, please refer to the [installation guide](https://nvidia.github.io/cloudai/workloads_requirements_installation.html). It automatically runs as part of the `run` mode if prerequisites are not met. - -```bash -cloudai install\ - --system-config conf/common/system/example_slurm_cluster.toml\ - --tests-dir conf/common/test\ - --test-scenario conf/common/test_scenario/sleep.toml -``` - -(uninstall)= -### uninstall -The opposite to the install mode, this mode removes installed test prerequisites. - -```bash -cloudai uninstall\ - --system-config conf/common/system/example_slurm_cluster.toml\ - --tests-dir conf/common/test\ - --test-scenario conf/common/test_scenario/sleep.toml -``` - -(list)= -### list -This mode lists internal components available within CloudAI. -```bash -cloudai list -``` - -(verify-configs)= -### verify-configs -This mode verifies the correctness of system, test and test scenario configuration files. - -```bash -# verify all at once -cloudai verify-configs conf - -# verify a single file -cloudai verify-configs conf/common/system/example_slurm_cluster.toml - -# verify all scenarios using specific folder with Test TOMLs -cloudai verify-configs --tests-dir conf/release/spcx/l40s/test conf/release/spcx/l40s/test_scenario -``` - - -```{toctree} -:maxdepth: 1 -:caption: Contents: -:glob: - -* -workloads/index -``` diff --git a/doc/index.rst b/doc/index.rst new file mode 100644 index 000000000..2d92770c7 --- /dev/null +++ b/doc/index.rst @@ -0,0 +1,179 @@ +CloudAI Benchmark Framework +=========================== + +CloudAI benchmark framework aims to develop an industry standard benchmark focused on grading Data Center (DC) scale AI systems in the cloud. The primary motivation is to provide automated benchmarking on various systems. + +Get Started +----------- + +.. code-block:: bash + + git clone git@github.com:NVIDIA/cloudai.git + cd cloudai + uv run cloudai --help + +.. note:: + + For instructions for setting up access for ``enroot``, see :doc:`workloads_requirements_installation`. + +``pip``-based Installation +-------------------------- + +See the required Python version in the ``.python-version`` file and make sure you have it installed (for installation, see :ref:`install-custom-python-version`). Follow these steps: + +.. code-block:: bash + + git clone git@github.com:NVIDIA/cloudai.git + cd cloudai + python -m venv venv + source venv/bin/activate + pip install -e . + + +.. _install-custom-python-version: + +Install Custom Python Version +----------------------------- + +If your system Python version is not supported, you can install a custom version using the `uv `_ tool: + +.. code-block:: bash + + curl -LsSf https://astral.sh/uv/install.sh | sh + source $HOME/.local/bin/env + uv venv --seed # picks the python version from .python-version + # --seed installs pip and setuptools + source .venv/bin/activate + +Key Concepts +------------ + +CloudAI operates on three main schemas: + +- **System Schema**: Describes the system, including the scheduler type, node list, and global environment variables. +- **Test Schema**: An instance of a test template with custom arguments and environment variables. +- **Test Scenario Schema**: A set of tests with dependencies and additional descriptions about the test scenario. + +These schemas enable CloudAI to be flexible and compatible with different systems and configurations. + +CloudAI Modes Usage Examples +---------------------------- + +Global options for ``cloudai`` command: + +- ``--log-file ``: specify a file to log output; by default ``debug.log`` in the current directory is used. Contains log entries of level ``DEBUG`` and higher. +- ``--log-level ``: specify logging level for standard output; default is ``INFO``. + +.. _run: + +run +~~~ + +This mode runs workloads. It automatically installs prerequisites if they are not met. + +.. code-block:: bash + + cloudai run\ + --system-config conf/common/system/example_slurm_cluster.toml\ + --tests-dir conf/common/test\ + --test-scenario conf/common/test_scenario/sleep.toml + +.. _dry-run: + +dry-run +~~~~~~~ + +This mode simulates running experiments without actually executing them. This is useful for verifying configurations and testing experiment setups. + +.. code-block:: bash + + cloudai dry-run\ + --system-config conf/common/system/example_slurm_cluster.toml\ + --tests-dir conf/common/test\ + --test-scenario conf/common/test_scenario/sleep.toml + +.. _generate-report: + +generate-report +~~~~~~~~~~~~~~~ + +This mode generates reports under the scenario directory. It automatically runs as part of the ``run`` mode after experiments are completed. + +.. code-block:: bash + + cloudai generate-report\ + --system-config conf/common/system/example_slurm_cluster.toml\ + --tests-dir conf/common/test\ + --test-scenario conf/common/test_scenario/sleep.toml\ + --result-dir /path/to/result_directory + +.. _install: + +install +~~~~~~~ + +This mode installs test prerequisites. For more details, refer to the :doc:`workloads_requirements_installation` guide. It automatically runs as part of the ``run`` mode if prerequisites are not met. + +.. code-block:: bash + + cloudai install\ + --system-config conf/common/system/example_slurm_cluster.toml\ + --tests-dir conf/common/test\ + --test-scenario conf/common/test_scenario/sleep.toml + +.. _uninstall: + +uninstall +~~~~~~~~~ + +The opposite to the install mode, this mode removes installed test prerequisites. + +.. code-block:: bash + + cloudai uninstall\ + --system-config conf/common/system/example_slurm_cluster.toml\ + --tests-dir conf/common/test\ + --test-scenario conf/common/test_scenario/sleep.toml + +.. _list: + +list +~~~~ + +This mode lists internal components available within CloudAI. + +.. code-block:: bash + + cloudai list + +.. _verify-configs: + +verify-configs +~~~~~~~~~~~~~~ + +This mode verifies the correctness of system, test, and test scenario configuration files. + +.. code-block:: bash + + # verify all at once + cloudai verify-configs conf + + # verify a single file + cloudai verify-configs conf/common/system/example_slurm_cluster.toml + + # verify all scenarios using specific folder with Test TOMLs + cloudai verify-configs --tests-dir conf/release/spcx/l40s/test conf/release/spcx/l40s/test_scenario + +Contents +-------- + +.. toctree:: + :maxdepth: 1 + :caption: Contents: + + USER_GUIDE + reporting + DEV + workloads/index + workloads_requirements_installation + diff --git a/doc/reporting.md b/doc/reporting.md deleted file mode 100644 index 055f2b5c7..000000000 --- a/doc/reporting.md +++ /dev/null @@ -1,61 +0,0 @@ -# Reporting -This document describes the reporting system in CloudAI. - - -## Overview -CloudAI has two reporting levels: -- per-test (per each case in a test scenario) -- per-scenario (per each test scenario) - -All reports are generated after the test scenario is completed as part of main CloudAI process. For Slurm this means that login node is used to generate reports. - -Per-test reports are linked to a particular workload type (e.g. `NcclTest`). All per-test reports are implemented as part of `per_test` scenario report and can be enabled/disabled via single configuration option, see [Enable, disable and configure reports](enable-disable-and-configure-reports) section. - -To list all available reports, users can use `cloudai list-reports` command. Use verbose output to also print report configurations. - - -## Notes and General Flow -1. All reports should be registered via `Registry()` (`.add_report()` or `.add_scenario_report()`). -1. Scenario reports are configurable via system config (Slurm-only for now) and scenario config. -1. Configuration in a scenario config has the highest priority. Next, system config is checked. Then it defaults to report config from the registry. -1. Then report is generated (or not) according to this final config. - - -(enable-disable-and-configure-reports)= -## Enable, Disable and Configure Reports -**NOTE** Only scenario-level reports can be configured. - -To enable or disable a report, users need to do it via system configuration: -```toml -[reports] -per_test = { enable = false } -status = { enable = true } -``` - - -## Report Registration -Report registration is done via `Registry` class: - -```python -Registry().add_scenario_report("per_test", PerTestReporter, ReportConfig(enable=True)) -``` - - -## Report Configuration Implementation -Each report can define its own configuration, which is constructed and passed as an argument to `Registry.add_scenario_report` method. `reports` field is parsed during TOMLs reading and respective Pydantic model is created. - -For example, we can define a custom report configuration: -```python -class CustomReportConfig(ReportConfig): - greeting: str -``` - -```python -Registry().add_scenario_report("custom", CustomReport, CustomReportConfig(greeting="default value")) -``` - -And use it in a test scenario: -```toml -[reports] -custom = { enable = true, greeting = "Hello, world!" } -``` diff --git a/doc/reporting.rst b/doc/reporting.rst new file mode 100644 index 000000000..ef52c58e8 --- /dev/null +++ b/doc/reporting.rst @@ -0,0 +1,77 @@ +Reporting +========= + +This document describes the reporting system in CloudAI. + +Overview +-------- + +CloudAI has two reporting levels: + +- per-test (per each case in a test scenario) +- per-scenario (per each test scenario) + +All reports are generated after the test scenario is completed as part of the main CloudAI process. For Slurm this means that the login node is used to generate reports. + +Per-test reports are linked to a particular workload type (e.g. ``NcclTest``). All per-test reports are implemented as part of the ``per_test`` scenario report and can be enabled or disabled via a single configuration option; see :ref:`enable-disable-and-configure-reports`. + +To list all available reports, users can use ``cloudai list-reports``. Use verbose output to also print report configurations. + +Notes and General Flow +---------------------- + +1. All reports should be registered via ``Registry()`` (``.add_report()`` or ``.add_scenario_report()``). +2. Scenario reports are configurable via system config (Slurm-only for now) and scenario config. +3. Configuration in a scenario config has the highest priority. Next, system config is checked. Then it defaults to report config from the registry. +4. Then the report is generated (or not) according to this final config. + + +.. _enable-disable-and-configure-reports: + +Enable, Disable and Configure Reports +------------------------------------- + +.. note:: + + Only scenario-level reports can be configured. + +To enable or disable a report, users need to do it via system configuration: + +.. code-block:: toml + + [reports] + per_test = { enable = false } + status = { enable = true } + +Report Registration +------------------- + +Report registration is done via ``Registry`` class: + +.. code-block:: python + + Registry().add_scenario_report("per_test", PerTestReporter, ReportConfig(enable=True)) + +Report Configuration Implementation +----------------------------------- + +Each report can define its own configuration, which is constructed and passed as an argument to ``Registry.add_scenario_report``. The ``reports`` field is parsed during TOML reading and the respective Pydantic model is created. + +For example, we can define a custom report configuration: + +.. code-block:: python + + class CustomReportConfig(ReportConfig): + greeting: str + +.. code-block:: python + + Registry().add_scenario_report("custom", CustomReport, CustomReportConfig(greeting="default value")) + +And use it in a test scenario: + +.. code-block:: toml + + [reports] + custom = { enable = true, greeting = "Hello, world!" } + diff --git a/doc/workloads/bash_cmd.rst b/doc/workloads/bash_cmd.rst index 16f4408bc..069d801d0 100644 --- a/doc/workloads/bash_cmd.rst +++ b/doc/workloads/bash_cmd.rst @@ -6,7 +6,7 @@ This workload (`test_template_name` is ``BashCmd``) allows users to execute arbi ``cmd`` specified in the ``cmd_args`` section will be added as-is into generated sbatch script. Usage Examples -------------- +-------------- Test TOML example: diff --git a/doc/workloads/chakra_replay.rst b/doc/workloads/chakra_replay.rst index eababe998..603a9dcec 100644 --- a/doc/workloads/chakra_replay.rst +++ b/doc/workloads/chakra_replay.rst @@ -4,7 +4,7 @@ Chakra Replay This workload (`test_template_name` is ``ChakraReplay``) replays execution traces from the Chakra execution trace format for performance analysis and debugging. Usage Examples -------------- +-------------- Test TOML example: diff --git a/doc/workloads/ddlb.rst b/doc/workloads/ddlb.rst index 7c3df0e2c..ad0ea6767 100644 --- a/doc/workloads/ddlb.rst +++ b/doc/workloads/ddlb.rst @@ -4,7 +4,7 @@ DDLB This workload (`test_template_name` is ``DDLB``) allows users to execute DDLB (Distributed Deep Learning Benchmarks) within the CloudAI framework. Please find the DDLB README at https://github.com/samnordmann/ddlb. Usage Examples -------------- +-------------- Test TOML example: diff --git a/doc/workloads/index.rst b/doc/workloads/index.rst index 38e68c092..b8d23ddad 100644 --- a/doc/workloads/index.rst +++ b/doc/workloads/index.rst @@ -42,7 +42,7 @@ Adding New Workloads To add documentation for a new workload: 1. Add docstrings to your Python classes and methods. -2. Create a markdown file in ``doc/workloads/`` (e.g., ``my_workload.md``). +2. Create a reStructuredText file in ``doc/workloads/`` (e.g., ``my_workload.rst``). 3. Add it to the table above. The documentation will be automatically generated during the build process. diff --git a/doc/workloads/megatron_bridge.rst b/doc/workloads/megatron_bridge.rst index d5d467e7b..8cbb18a78 100644 --- a/doc/workloads/megatron_bridge.rst +++ b/doc/workloads/megatron_bridge.rst @@ -5,7 +5,7 @@ This workload (`test_template_name` is ``MegatronBridge``) submits training and Usage Examples -------------- +-------------- Test TOML example: @@ -14,17 +14,17 @@ Test TOML example: name = "megatron_bridge_qwen_30b" description = "Megatron-Bridge run via CloudAI SlurmSystem for Qwen3 30B A3B" test_template_name = "MegatronBridge" - + [cmd_args] # Container can be an NGC/enroot URL (nvcr.io#...) or a local .sqsh path. container_image = "nvcr.io#nvidia/nemo:25.11.01" - + model_name = "qwen3" model_size = "30b_a3b" task = "pretrain" domain = "llm" compute_dtype = "fp8_mx" - + hf_token = "hf_xxx" Test Scenario example: @@ -32,7 +32,7 @@ Test Scenario example: .. code-block:: toml name = "megatron_bridge_qwen_30b" - + [[Tests]] id = "megatron_bridge_qwen_30b" test_name = "megatron_bridge_qwen_30b" @@ -43,16 +43,16 @@ Test-in-Scenario example: .. code-block:: toml name = "megatron-bridge-test" - + [[Tests]] id = "mbridge.1" num_nodes = 2 time_limit = "00:30:00" - + name = "megatron_bridge_qwen_30b" description = "Megatron-Bridge run via CloudAI SlurmSystem for Qwen3 30B A3B" test_template_name = "MegatronBridge" - + [Tests.cmd_args] container_image = "nvcr.io#nvidia/nemo:25.11.01" model_name = "qwen3" diff --git a/doc/workloads/nemo_run.rst b/doc/workloads/nemo_run.rst index f979fcc94..0eb0eace7 100644 --- a/doc/workloads/nemo_run.rst +++ b/doc/workloads/nemo_run.rst @@ -4,7 +4,7 @@ Nemo Run This workload (`test_template_name` is ``NemoRun``) executes NeMo training and fine-tuning tasks using the NeMo Run framework. Usage Examples -------------- +-------------- Test TOML example: diff --git a/doc/workloads/nixl_bench.rst b/doc/workloads/nixl_bench.rst index 48146ab65..6520cee8a 100644 --- a/doc/workloads/nixl_bench.rst +++ b/doc/workloads/nixl_bench.rst @@ -4,7 +4,7 @@ NIXL Bench This workload (`test_template_name` is ``NIXLBench``) runs NIXL benchmarking suite for network and interconnect performance testing. Usage Examples -------------- +-------------- Test TOML example: diff --git a/doc/workloads/nixl_kvbench.rst b/doc/workloads/nixl_kvbench.rst index ca625e38c..f97ccbabe 100644 --- a/doc/workloads/nixl_kvbench.rst +++ b/doc/workloads/nixl_kvbench.rst @@ -4,7 +4,7 @@ NIXL KVBench This workload (`test_template_name` is ``NIXLKVBench``) runs NIXL KV-cache benchmarking for key-value store performance testing. Usage Examples -------------- +-------------- Test TOML example: diff --git a/doc/workloads/nixl_perftest.rst b/doc/workloads/nixl_perftest.rst index 183b1e208..1f372613d 100644 --- a/doc/workloads/nixl_perftest.rst +++ b/doc/workloads/nixl_perftest.rst @@ -4,7 +4,7 @@ NIXL CTPerf This workload (`test_template_name` is ``NixlPerftest``) runs NIXL performance testing suite for comprehensive network performance evaluation. Usage Examples -------------- +-------------- Test TOML example: diff --git a/doc/workloads/sleep.rst b/doc/workloads/sleep.rst index 7e815d92e..1cfbd67b8 100644 --- a/doc/workloads/sleep.rst +++ b/doc/workloads/sleep.rst @@ -4,7 +4,7 @@ Sleep This workload (`test_template_name` is ``Sleep``) executes a simple sleep command for testing and timing purposes. Useful for testing schedulers and system behavior. Usage Examples -------------- +-------------- Test TOML example: diff --git a/doc/workloads/slurm_container.rst b/doc/workloads/slurm_container.rst index 6df5a56ae..718329139 100644 --- a/doc/workloads/slurm_container.rst +++ b/doc/workloads/slurm_container.rst @@ -4,7 +4,7 @@ Slurm Container This workload (`test_template_name` is ``SlurmContainer``) executes containerized workloads using Slurm with custom container configurations. Usage Examples -------------- +-------------- Test TOML example: diff --git a/doc/workloads/ucc.rst b/doc/workloads/ucc.rst index 1ad4bf651..2d559ddc6 100644 --- a/doc/workloads/ucc.rst +++ b/doc/workloads/ucc.rst @@ -4,7 +4,7 @@ UCC This workload (`test_template_name` is ``UCCTest``) allows users to execute UCC benchmarks within the CloudAI framework. Usage Examples -------------- +-------------- Test TOML example: diff --git a/pyproject.toml b/pyproject.toml index 2f2c8241e..295e29897 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -53,7 +53,6 @@ requires-python = ">=3.10" docs = [ "sphinx~=8.1", "nvidia-sphinx-theme~=0.0.8", - "myst-parser~=4.0", "sphinxext-opengraph~=0.13", "sphinx-design~=0.6", "sphinxcontrib-mermaid~=1.0", diff --git a/uv.lock b/uv.lock index 013c24e9e..2fe9cba63 100644 --- a/uv.lock +++ b/uv.lock @@ -28,6 +28,34 @@ wheels = [ { url = "https://files.pythonhosted.org/packages/8d/3f/95338030883d8c8b91223b4e21744b04d11b161a3ef117295d8241f50ab4/accessible_pygments-0.0.5-py3-none-any.whl", hash = "sha256:88ae3211e68a1d0b011504b2ffc1691feafce124b845bd072ab6f9f66f34d4b7", size = 1395903, upload-time = "2024-05-10T11:23:08.421Z" }, ] +[[package]] +name = "aiconfigurator" +version = "0.4.0" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "bokeh" }, + { name = "fastapi" }, + { name = 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All rights reserved. +# Copyright (c) 2024-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved. # SPDX-License-Identifier: Apache-2.0 # # Licensed under the Apache License, Version 2.0 (the "License"); From e004bbbda477997a4887b669ce930eb3a289f35d Mon Sep 17 00:00:00 2001 From: Andrei Maslennikov Date: Wed, 7 Jan 2026 14:57:53 +0100 Subject: [PATCH 03/13] Build CMS-friendly documentation --- .github/workflows/docs.yml | 47 ++++++++++++++++++++++++-------------- doc/Makefile | 42 ++++++++++++++++++++++++++++------ doc/conf.py | 17 +++++++++----- doc/index.rst | 5 ++-- pyproject.toml | 6 +++++ 5 files changed, 84 insertions(+), 33 deletions(-) diff --git a/.github/workflows/docs.yml b/.github/workflows/docs.yml index a932733a9..24c5cabba 100644 --- a/.github/workflows/docs.yml +++ b/.github/workflows/docs.yml @@ -23,30 +23,43 @@ jobs: with: enable-cache: true - - name: Set up environment - run: | - set -eE - set -o pipefail - - uv sync --extra docs - - name: Build documentation - run: | - set -eE - set -o pipefail - - source .venv/bin/activate - cd doc - make html - - - name: Add .nojekyll file - run: touch doc/_build/html/.nojekyll + run: make -C doc/ html - name: Upload artifact uses: actions/upload-pages-artifact@v3 with: path: ./doc/_build/html + build-cms: + name: Build CMS Documentation + runs-on: ubuntu-latest + steps: + - name: Checkout + uses: actions/checkout@v4 + + - name: Install uv + uses: astral-sh/setup-uv@v5 + with: + enable-cache: true + + - name: Set up Node.js + uses: actions/setup-node@v6 + + - name: Build CMS documentation + run: make -C doc/ cms-html + + - name: Create zip archive + run: | + cd doc/_build-cms/html + zip -r ../../../cloudai-docs-cms.zip . + + - name: Upload CMS docs artifact + uses: actions/upload-artifact@v4 + with: + name: cloudai-docs-cms + path: cloudai-docs-cms.zip + deploy: name: Deploy to GitHub Pages needs: build diff --git a/doc/Makefile b/doc/Makefile index 2d23d047a..c176bf767 100644 --- a/doc/Makefile +++ b/doc/Makefile @@ -15,14 +15,42 @@ # limitations under the License. SPHINXOPTS ?= -SPHINXBUILD ?= sphinx-build -SOURCEDIR = . -BUILDDIR = _build +SOURCEDIR = . +BUILDDIR = _build +BUILDDIR_CMS = _build-cms + +NODE_MODULES = $(BUILDDIR_CMS)/node_modules +MMDC = $(NODE_MODULES)/.bin/mmdc + +.PHONY: help html cms-html install-mermaid clean-mermaid clean help: - @$(SPHINXBUILD) -M help "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O) + @echo "Available targets:" + @echo " html - Build documentation for GitHub Pages (nvidia_sphinx_theme) -> $(BUILDDIR)/" + @echo " cms-html - Build documentation for BrightSpot CMS (sphinx_rtd_theme, PNG mermaid) -> $(BUILDDIR_CMS)/" + @echo " clean - Remove all build directories" + +# Default html target (GitHub Pages) +html: + @echo "Setting up environment for GitHub Pages build..." + @uv sync --extra docs + @echo "Building documentation..." + @cd .. && uv run sphinx-build -M html "doc" "doc/$(BUILDDIR)" $(SPHINXOPTS) + @touch $(BUILDDIR)/html/.nojekyll + +cms-html: install-mermaid + @echo "Setting up environment for CMS build..." + @uv sync --extra docs-cms + @echo "Building documentation..." + @cd .. && CLOUDAI_DOC_TARGET=cms uv run sphinx-build -M html "doc" "doc/$(BUILDDIR_CMS)" $(SPHINXOPTS) + +install-mermaid: $(MMDC) -.PHONY: help Makefile +$(MMDC): + @echo "Installing @mermaid-js/mermaid-cli via npm..." + @mkdir -p $(BUILDDIR_CMS) + @cd $(BUILDDIR_CMS) && npm install @mermaid-js/mermaid-cli + @echo "mermaid-cli installed successfully." -%: Makefile - @$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O) +clean: + @rm -rf $(BUILDDIR) $(BUILDDIR_CMS) diff --git a/doc/conf.py b/doc/conf.py index b5e3a57f6..9c30e0c15 100644 --- a/doc/conf.py +++ b/doc/conf.py @@ -20,6 +20,7 @@ import os import re import sys +from pathlib import Path # Add the project source to Python path for autodoc sys.path.insert(0, os.path.abspath("../src")) @@ -56,6 +57,7 @@ def setup(app): # -- General configuration --------------------------------------------------- # https://www.sphinx-doc.org/en/master/usage/configuration.html#general-configuration + extensions = [ "sphinx.ext.autodoc", "sphinx.ext.viewcode", @@ -81,12 +83,15 @@ def setup(app): # -- Options for HTML output ------------------------------------------------- # https://www.sphinx-doc.org/en/master/usage/configuration.html#options-for-html-output -html_theme = "nvidia_sphinx_theme" - -# Mermaid configuration -mermaid_version = "latest" -mermaid_init_js = "mermaid.initialize({startOnLoad:true});" -mermaid_output_format = "raw" # render in-browser without mermaid-cli +is_cms_build = os.environ.get("CLOUDAI_DOC_TARGET") == "cms" +if is_cms_build: + html_theme = "sphinx_rtd_theme" + mermaid_output_format = "png" + mermaid_cmd = str(Path.cwd() / "_build-cms/node_modules/.bin/mmdc") +else: + # Default build: nvidia_sphinx_theme with raw mermaid (client-side JS) + html_theme = "nvidia_sphinx_theme" + mermaid_output_format = "raw" # Set the root document to index root_doc = "index" diff --git a/doc/index.rst b/doc/index.rst index 2d92770c7..461eb6670 100644 --- a/doc/index.rst +++ b/doc/index.rst @@ -164,12 +164,11 @@ This mode verifies the correctness of system, test, and test scenario configurat # verify all scenarios using specific folder with Test TOMLs cloudai verify-configs --tests-dir conf/release/spcx/l40s/test conf/release/spcx/l40s/test_scenario -Contents --------- +CloudAI +------- .. toctree:: :maxdepth: 1 - :caption: Contents: USER_GUIDE reporting diff --git a/pyproject.toml b/pyproject.toml index 39a4363f9..1f443fdba 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -58,6 +58,12 @@ requires-python = ">=3.10" "sphinxcontrib-mermaid~=1.0", "sphinx-copybutton~=0.5", ] + docs-cms = [ + "sphinx~=8.1", + "sphinx-rtd-theme~=3.0", + "sphinx-copybutton~=0.5", + "sphinxcontrib-mermaid~=1.0", + ] [build-system] requires = ["pdm-backend"] From 984b0f806db21655c2ac91eed814da1cbb254946 Mon Sep 17 00:00:00 2001 From: Andrei Maslennikov Date: Wed, 7 Jan 2026 15:00:14 +0100 Subject: [PATCH 04/13] Add missing uv lock sync --- doc/Makefile | 4 +-- uv.lock | 81 ++++++++++++++++++++++++++++++++++++++++++---------- 2 files changed, 68 insertions(+), 17 deletions(-) diff --git a/doc/Makefile b/doc/Makefile index c176bf767..ed0c015d3 100644 --- a/doc/Makefile +++ b/doc/Makefile @@ -33,14 +33,14 @@ help: # Default html target (GitHub Pages) html: @echo "Setting up environment for GitHub Pages build..." - @uv sync --extra docs + @cd .. && uv sync --extra docs @echo "Building documentation..." @cd .. && uv run sphinx-build -M html "doc" "doc/$(BUILDDIR)" $(SPHINXOPTS) @touch $(BUILDDIR)/html/.nojekyll cms-html: install-mermaid @echo "Setting up environment for CMS build..." - 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name: Build CMS documentation run: make -C doc/ cms-html - - name: Create zip archive - run: | - cd doc/_build-cms/html - zip -r ../../../cloudai-docs-cms.zip . - - name: Upload CMS docs artifact uses: actions/upload-artifact@v4 with: name: cloudai-docs-cms - path: cloudai-docs-cms.zip + path: doc/_build-cms/html deploy: name: Deploy to GitHub Pages From 5e31183baac3dff3d221607e032ba651d333e289 Mon Sep 17 00:00:00 2001 From: Andrei Maslennikov Date: Wed, 7 Jan 2026 15:18:00 +0100 Subject: [PATCH 06/13] Address review comments --- doc/conf.py | 5 +---- 1 file changed, 1 insertion(+), 4 deletions(-) diff --git a/doc/conf.py b/doc/conf.py index 9c30e0c15..c78ef74d5 100644 --- a/doc/conf.py +++ b/doc/conf.py @@ -84,14 +84,11 @@ def setup(app): # https://www.sphinx-doc.org/en/master/usage/configuration.html#options-for-html-output is_cms_build = os.environ.get("CLOUDAI_DOC_TARGET") == "cms" +html_theme, mermaid_output_format, mermaid_cmd = "nvidia_sphinx_theme", "raw", None if is_cms_build: html_theme = "sphinx_rtd_theme" mermaid_output_format = "png" mermaid_cmd = str(Path.cwd() / "_build-cms/node_modules/.bin/mmdc") -else: - # Default build: nvidia_sphinx_theme with raw mermaid (client-side JS) - html_theme = "nvidia_sphinx_theme" - mermaid_output_format = "raw" # Set the root document to index root_doc = "index" From 0df23799f16b78fc067b87178d8b2a698e2d9287 Mon Sep 17 00:00:00 2001 From: Andrei Maslennikov Date: Wed, 7 Jan 2026 15:19:44 +0100 Subject: [PATCH 07/13] Avoid sphinx warning --- doc/conf.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/doc/conf.py b/doc/conf.py index c78ef74d5..57609c761 100644 --- a/doc/conf.py +++ b/doc/conf.py @@ -84,7 +84,7 @@ def setup(app): # https://www.sphinx-doc.org/en/master/usage/configuration.html#options-for-html-output is_cms_build = os.environ.get("CLOUDAI_DOC_TARGET") == "cms" -html_theme, mermaid_output_format, mermaid_cmd = "nvidia_sphinx_theme", "raw", None +html_theme, mermaid_output_format, mermaid_cmd = "nvidia_sphinx_theme", "raw", "" if is_cms_build: html_theme = "sphinx_rtd_theme" mermaid_output_format = "png" From a54a3751c60e97ba302328b3a3b27ee3f2576b35 Mon Sep 17 00:00:00 2001 From: Andrei Maslennikov Date: Wed, 7 Jan 2026 15:35:23 +0100 Subject: [PATCH 08/13] Fix CMS doc build --- doc/Makefile | 4 +++- doc/conf.py | 3 ++- 2 files changed, 5 insertions(+), 2 deletions(-) diff --git a/doc/Makefile b/doc/Makefile index ed0c015d3..922b40360 100644 --- a/doc/Makefile +++ b/doc/Makefile @@ -21,8 +21,9 @@ BUILDDIR_CMS = _build-cms NODE_MODULES = $(BUILDDIR_CMS)/node_modules MMDC = $(NODE_MODULES)/.bin/mmdc +PUPPETEER_CFG = $(BUILDDIR_CMS)/puppeteer-config.json -.PHONY: help html cms-html install-mermaid clean-mermaid clean +.PHONY: help html cms-html install-mermaid clean help: @echo "Available targets:" @@ -50,6 +51,7 @@ $(MMDC): @echo "Installing @mermaid-js/mermaid-cli via npm..." @mkdir -p $(BUILDDIR_CMS) @cd $(BUILDDIR_CMS) && npm install @mermaid-js/mermaid-cli + @echo '{"args": ["--no-sandbox"]}' > $(PUPPETEER_CFG) @echo "mermaid-cli installed successfully." clean: diff --git a/doc/conf.py b/doc/conf.py index 57609c761..6f71eb4cb 100644 --- a/doc/conf.py +++ b/doc/conf.py @@ -84,11 +84,12 @@ def setup(app): # https://www.sphinx-doc.org/en/master/usage/configuration.html#options-for-html-output is_cms_build = os.environ.get("CLOUDAI_DOC_TARGET") == "cms" -html_theme, mermaid_output_format, mermaid_cmd = "nvidia_sphinx_theme", "raw", "" +html_theme, mermaid_output_format, mermaid_cmd, mermaid_params = "nvidia_sphinx_theme", "raw", "", [] if is_cms_build: html_theme = "sphinx_rtd_theme" mermaid_output_format = "png" mermaid_cmd = str(Path.cwd() / "_build-cms/node_modules/.bin/mmdc") + mermaid_params = ["-p", str(Path.cwd() / "_build-cms/puppeteer-config.json")] # Set the root document to index root_doc = "index" From a8aa36df545b071824e8964e4f9c3247736e7550 Mon Sep 17 00:00:00 2001 From: Andrei Maslennikov Date: Wed, 7 Jan 2026 15:44:09 +0100 Subject: [PATCH 09/13] Address review comments --- .github/workflows/docs.yml | 2 ++ doc/USER_GUIDE.rst | 2 +- pyproject.toml | 4 ++-- uv.lock | 10 +++++----- 4 files changed, 10 insertions(+), 8 deletions(-) diff --git a/.github/workflows/docs.yml b/.github/workflows/docs.yml index b064263a6..a45612c60 100644 --- a/.github/workflows/docs.yml +++ b/.github/workflows/docs.yml @@ -45,6 +45,8 @@ jobs: - name: Set up Node.js uses: actions/setup-node@v6 + with: + node-version: '24' - name: Build CMS documentation run: make -C doc/ cms-html diff --git a/doc/USER_GUIDE.rst b/doc/USER_GUIDE.rst index 09e11b8c1..67ad6bb6a 100644 --- a/doc/USER_GUIDE.rst +++ b/doc/USER_GUIDE.rst @@ -364,7 +364,7 @@ A test scenario is a set of tests with specific dependencies between them. A tes [[Tests]] id = "Tests.3" - templat_test = "nccl_test_reduce_scatter" + test_name = "nccl_test_reduce_scatter" num_nodes = "2" time_limit = "00:20:00" [[Tests.dependencies]] diff --git a/pyproject.toml b/pyproject.toml index 1f443fdba..de4aaf2cd 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -55,14 +55,14 @@ requires-python = ">=3.10" "nvidia-sphinx-theme~=0.0.8", "sphinxext-opengraph~=0.13", "sphinx-design~=0.6", - "sphinxcontrib-mermaid~=1.0", + "sphinxcontrib-mermaid~=1.2", "sphinx-copybutton~=0.5", ] docs-cms = [ "sphinx~=8.1", "sphinx-rtd-theme~=3.0", "sphinx-copybutton~=0.5", - "sphinxcontrib-mermaid~=1.0", + "sphinxcontrib-mermaid~=1.2", ] [build-system] diff --git a/uv.lock b/uv.lock index b77f6cc7e..22a38320e 100644 --- a/uv.lock +++ b/uv.lock @@ -361,8 +361,8 @@ requires-dist = [ { name = "sphinx-copybutton", marker = "extra == 'docs-cms'", specifier = "~=0.5" }, { name = "sphinx-design", marker = "extra == 'docs'", specifier = "~=0.6" }, { name = "sphinx-rtd-theme", marker = "extra == 'docs-cms'", specifier = "~=3.0" }, - { name = "sphinxcontrib-mermaid", marker = "extra == 'docs'", specifier = "~=1.0" }, - { name = "sphinxcontrib-mermaid", marker = "extra == 'docs-cms'", specifier = "~=1.0" }, + { name = "sphinxcontrib-mermaid", marker = "extra == 'docs'", specifier = "~=1.2" }, + { name = "sphinxcontrib-mermaid", marker = "extra == 'docs-cms'", specifier = "~=1.2" }, { name = "sphinxext-opengraph", marker = "extra == 'docs'", specifier = "~=0.13" }, { name = "taplo", marker = "extra == 'dev'", specifier = "~=0.9.3" }, { name = "tbparse", specifier = "~=0.0.9" }, @@ -2584,16 +2584,16 @@ wheels = [ [[package]] name = "sphinxcontrib-mermaid" -version = "1.0.0" +version = "1.2.3" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "pyyaml" }, { name = "sphinx", version = "8.1.3", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.11'" }, { name = "sphinx", version = "8.2.3", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.11'" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/97/69/bf039237ad260073e8c02f820b3e00dc34f3a2de20aff7861e6b19d2f8c5/sphinxcontrib_mermaid-1.0.0.tar.gz", hash = "sha256:2e8ab67d3e1e2816663f9347d026a8dee4a858acdd4ad32dd1c808893db88146", size = 15153, upload-time = "2024-10-12T16:33:03.863Z" } +sdist = { url = "https://files.pythonhosted.org/packages/f5/49/c6ddfe709a4ab76ac6e5a00e696f73626b2c189dc1e1965a361ec102e6cc/sphinxcontrib_mermaid-1.2.3.tar.gz", hash = "sha256:358699d0ec924ef679b41873d9edd97d0773446daf9760c75e18dc0adfd91371", size = 18885, upload-time = "2025-11-26T04:18:32.43Z" } wheels = [ - { url = "https://files.pythonhosted.org/packages/cd/c8/784b9ac6ea08aa594c1a4becbd0dbe77186785362e31fd633b8c6ae0197a/sphinxcontrib_mermaid-1.0.0-py3-none-any.whl", hash = "sha256:60b72710ea02087f212028feb09711225fbc2e343a10d34822fe787510e1caa3", size = 9597, upload-time = "2024-10-12T16:33:02.303Z" }, + { url = "https://files.pythonhosted.org/packages/d1/39/8b54299ffa00e597d3b0b4d042241a0a0b22cb429ad007ccfb9c1745b4d1/sphinxcontrib_mermaid-1.2.3-py3-none-any.whl", hash = "sha256:5be782b27026bef97bfb15ccb2f7868b674a1afc0982b54cb149702cfc25aa02", size = 13413, upload-time = "2025-11-26T04:18:31.269Z" }, ] [[package]] From 07b1bc83c5138ef531f67bc81092dfbfad034e16 Mon Sep 17 00:00:00 2001 From: Andrei Maslennikov Date: Wed, 7 Jan 2026 15:59:44 +0100 Subject: [PATCH 10/13] Address review comments --- doc/Makefile | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/doc/Makefile b/doc/Makefile index 922b40360..e2c37d9eb 100644 --- a/doc/Makefile +++ b/doc/Makefile @@ -48,9 +48,10 @@ cms-html: install-mermaid install-mermaid: $(MMDC) $(MMDC): + @command -v npm >/dev/null 2>&1 || { echo "Error: npm is required for CMS build but not found. Please install Node.js/npm first."; exit 1; } @echo "Installing @mermaid-js/mermaid-cli via npm..." @mkdir -p $(BUILDDIR_CMS) - @cd $(BUILDDIR_CMS) && npm install @mermaid-js/mermaid-cli + @cd $(BUILDDIR_CMS) && npm install @mermaid-js/mermaid-cli@^11 @echo '{"args": ["--no-sandbox"]}' > $(PUPPETEER_CFG) @echo "mermaid-cli installed successfully." From 5d5ddb93a8e90ac44e06da5bcbb4c204dcc88f08 Mon Sep 17 00:00:00 2001 From: Andrei Maslennikov Date: Wed, 7 Jan 2026 16:09:30 +0100 Subject: [PATCH 11/13] Trigger docs deployment based on tags creation --- .github/workflows/docs.yml | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/.github/workflows/docs.yml b/.github/workflows/docs.yml index a45612c60..b5a1b41f3 100644 --- a/.github/workflows/docs.yml +++ b/.github/workflows/docs.yml @@ -3,6 +3,7 @@ name: Build and Deploy Documentation on: push: branches: [ main ] + tags: [ 'v*' ] workflow_dispatch: # Allow manual triggering # Allow only one concurrent deployment, skipping runs queued between the run in-progress and latest queued. @@ -54,7 +55,7 @@ jobs: - name: Upload CMS docs artifact uses: actions/upload-artifact@v4 with: - name: cloudai-docs-cms + name: cloudai-docs-cms-${{ github.ref_name }} path: doc/_build-cms/html deploy: From 0917b184762d253bc67876053a59035245384158 Mon Sep 17 00:00:00 2001 From: Andrei Maslennikov Date: Wed, 7 Jan 2026 16:18:23 +0100 Subject: [PATCH 12/13] Sanitize artifact name --- .github/workflows/docs.yml | 6 +++++- 1 file changed, 5 insertions(+), 1 deletion(-) diff --git a/.github/workflows/docs.yml b/.github/workflows/docs.yml index b5a1b41f3..8bf676731 100644 --- a/.github/workflows/docs.yml +++ b/.github/workflows/docs.yml @@ -52,10 +52,14 @@ jobs: - name: Build CMS documentation run: make -C doc/ cms-html + - name: Sanitize artifact name + id: artifact-name + run: echo "name=cloudai-docs-cms-$(echo '${{ github.ref_name }}' | tr '/' '-')" >> $GITHUB_OUTPUT + - name: Upload CMS docs artifact uses: actions/upload-artifact@v4 with: - name: cloudai-docs-cms-${{ github.ref_name }} + name: ${{ steps.artifact-name.outputs.name }} path: doc/_build-cms/html deploy: From 18f3d8c95fd109f25c31696f10be9f793d79b690 Mon Sep 17 00:00:00 2001 From: Andrei Maslennikov Date: Wed, 7 Jan 2026 16:26:16 +0100 Subject: [PATCH 13/13] Address review comments --- doc/conf.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/doc/conf.py b/doc/conf.py index 6f71eb4cb..c29789aa2 100644 --- a/doc/conf.py +++ b/doc/conf.py @@ -88,8 +88,8 @@ def setup(app): if is_cms_build: html_theme = "sphinx_rtd_theme" mermaid_output_format = "png" - mermaid_cmd = str(Path.cwd() / "_build-cms/node_modules/.bin/mmdc") - mermaid_params = ["-p", str(Path.cwd() / "_build-cms/puppeteer-config.json")] + mermaid_cmd = str(Path(__file__).parent / "_build-cms/node_modules/.bin/mmdc") + mermaid_params = ["-p", str(Path(__file__).parent / "_build-cms/puppeteer-config.json")] # Set the root document to index root_doc = "index"