diff --git a/docs/compatibility/ml-compatibility/pytorch-compatibility.rst b/docs/compatibility/ml-compatibility/pytorch-compatibility.rst index 2ca99886c..245296532 100644 --- a/docs/compatibility/ml-compatibility/pytorch-compatibility.rst +++ b/docs/compatibility/ml-compatibility/pytorch-compatibility.rst @@ -338,7 +338,7 @@ with ROCm. * - Library - Description - * - `torchaudio `_ + * - `torchaudio `_ - Audio and signal processing library for PyTorch. Provides utilities for audio I/O, signal and data processing functions, datasets, model implementations, and application components for audio and speech @@ -365,11 +365,11 @@ with ROCm. and popular datasets for natural language processing, including tokenization, vocabulary management, and text embeddings. - **Note:** ``torchtext`` does not implement ROCm-specific kernels. + **Note:** ``torchtext`` does not implement ROCm-specific kernels. ROCm acceleration is provided through the underlying PyTorch framework and ROCm library integration. Only official release exists. - * - `torchdata `_ + * - `torchdata `_ - Beta library of common modular data loading primitives for easily constructing flexible and performant data pipelines, with features still in prototype stage. @@ -471,7 +471,7 @@ Known issues and notes for PyTorch 2.7 with ROCm 7.0 ================================================================================ - The ``matmul.allow_fp16_reduced_precision_reduction`` and - ``matmul.allow_bf16_reduced_precision_reduction`` options under - ``torch.backends.cuda`` are not supported. As a result, + ``matmul.allow_bf16_reduced_precision_reduction`` options under + ``torch.backends.cuda`` are not supported. As a result, reduced-precision reductions using FP16 or BF16 accumulation types are not available. diff --git a/docs/how-to/rocm-for-ai/system-health-check.rst b/docs/how-to/rocm-for-ai/system-health-check.rst index 63a5274c6..2014556bc 100644 --- a/docs/how-to/rocm-for-ai/system-health-check.rst +++ b/docs/how-to/rocm-for-ai/system-health-check.rst @@ -75,8 +75,8 @@ This helps ensure optimal scaling for multi-accelerator tasks. make 2. Run the suggested RCCL tests -- see `RCCL benchmarking - `_ - in the Instinct performance benchmarking documentation for instructions. + `_ + in the AMD Instinct customer acceptance guide. TransferBench test ================== diff --git a/docs/how-to/rocm-for-ai/training/benchmark-docker/jax-maxtext.rst b/docs/how-to/rocm-for-ai/training/benchmark-docker/jax-maxtext.rst index 24a89d31e..49d8acdc0 100644 --- a/docs/how-to/rocm-for-ai/training/benchmark-docker/jax-maxtext.rst +++ b/docs/how-to/rocm-for-ai/training/benchmark-docker/jax-maxtext.rst @@ -369,7 +369,7 @@ benchmark results: benchmark. Run them outside of any Docker container. 1. Make sure ``$HF_HOME`` is set before running the test. See - `ROCm benchmarking `__ + `ROCm benchmarking `__ for more details on downloading the Llama models before running the benchmark. diff --git a/docs/how-to/rocm-for-ai/training/benchmark-docker/previous-versions/jax-maxtext-v25.4.rst b/docs/how-to/rocm-for-ai/training/benchmark-docker/previous-versions/jax-maxtext-v25.4.rst index 3fe728c35..8b8dd65bd 100644 --- a/docs/how-to/rocm-for-ai/training/benchmark-docker/previous-versions/jax-maxtext-v25.4.rst +++ b/docs/how-to/rocm-for-ai/training/benchmark-docker/previous-versions/jax-maxtext-v25.4.rst @@ -202,16 +202,14 @@ Getting started The following examples demonstrate how to get started with single node and multi-node training using the benchmarking scripts provided at -``__. +``__. .. important:: The provided scripts launch a Docker container and execute a benchmark. Ensure you run these commands outside of any existing Docker container. Before running any benchmarks, ensure the ``$HF_HOME`` environment variable is -set correctly and points to your Hugging Face cache directory. Refer to the -README at ``__ -for more detailed instructions. +set correctly and points to your Hugging Face cache directory. Single node training benchmarking examples ------------------------------------------ diff --git a/docs/how-to/rocm-for-ai/training/benchmark-docker/pytorch-training.rst b/docs/how-to/rocm-for-ai/training/benchmark-docker/pytorch-training.rst index f2e52fc65..59e86c4f9 100644 --- a/docs/how-to/rocm-for-ai/training/benchmark-docker/pytorch-training.rst +++ b/docs/how-to/rocm-for-ai/training/benchmark-docker/pytorch-training.rst @@ -299,28 +299,28 @@ Run training - `Hugging Face Datasets `_ 3.2.0 * - ``torchdata`` - - `TorchData `_ + - `TorchData `__ * - ``tomli`` - - `Tomli `_ + - `Tomli `__ * - ``tiktoken`` - - `tiktoken `_ + - `tiktoken `__ * - ``blobfile`` - - `blobfile `_ + - `blobfile `__ * - ``tabulate`` - - `tabulate `_ + - `tabulate `__ * - ``wandb`` - - `Weights & Biases `_ + - `Weights & Biases `__ * - ``sentencepiece`` - - `SentencePiece `_ 0.2.0 + - `SentencePiece `__ 0.2.0 * - ``tensorboard`` - - `TensorBoard `_ 2.18.0 + - `TensorBoard `__ 2.18.0 .. container:: model-doc pyt_train_flux @@ -336,50 +336,50 @@ Run training - `Hugging Face Accelerate `_ * - ``datasets`` - - `Hugging Face Datasets `_ 3.2.0 + - `Hugging Face Datasets `__ 3.2.0 * - ``sentencepiece`` - - `SentencePiece `_ 0.2.0 + - `SentencePiece `__ 0.2.0 * - ``tensorboard`` - - `TensorBoard `_ 2.18.0 + - `TensorBoard `__ 2.18.0 * - ``csvkit`` - - `csvkit `_ 2.0.1 + - `csvkit `__ 2.0.1 * - ``deepspeed`` - - `DeepSpeed `_ 0.16.2 + - `DeepSpeed `__ 0.16.2 * - ``diffusers`` - - `Hugging Face Diffusers `_ 0.31.0 + - `Hugging Face Diffusers `__ 0.31.0 * - ``GitPython`` - - `GitPython `_ 3.1.44 + - `GitPython `__ 3.1.44 * - ``opencv-python-headless`` - - `opencv-python-headless `_ 4.10.0.84 + - `opencv-python-headless `__ 4.10.0.84 * - ``peft`` - - `PEFT `_ 0.14.0 + - `PEFT `__ 0.14.0 * - ``protobuf`` - - `Protocol Buffers `_ 5.29.2 + - `Protocol Buffers `__ 5.29.2 * - ``pytest`` - - `PyTest `_ 8.3.4 + - `PyTest `__ 8.3.4 * - ``python-dotenv`` - - `python-dotenv `_ 1.0.1 + - `python-dotenv `__ 1.0.1 * - ``seaborn`` - - `Seaborn `_ 0.13.2 + - `Seaborn `__ 0.13.2 * - ``transformers`` - - `Transformers `_ 4.47.0 + - `Transformers `__ 4.47.0 ``pytorch_benchmark_setup.sh`` downloads the following datasets from Hugging Face: - * `bghira/pseudo-camera-10k `_ + * `bghira/pseudo-camera-10k `__ {% for model_group in model_groups %} {% for model in model_group.models %}