From afa414d060f52cc1f45cad0f1f6cd016fa994ace Mon Sep 17 00:00:00 2001 From: Philipp Schmid <32632186+philschmid@users.noreply.github.com> Date: Wed, 16 Jun 2021 13:24:00 +0200 Subject: [PATCH] updated DLC images and sample notebooks (#12191) --- docs/source/sagemaker.md | 36 +++++++++++++++++++++++------------- 1 file changed, 23 insertions(+), 13 deletions(-) diff --git a/docs/source/sagemaker.md b/docs/source/sagemaker.md index 338effb185..ec05dd3c72 100644 --- a/docs/source/sagemaker.md +++ b/docs/source/sagemaker.md @@ -16,22 +16,14 @@ limitations under the License. # Run training on Amazon SageMaker -Hugging Face and Amazon are introducing new [Hugging Face Deep Learning Containers (DLCs)](https://github.com/aws/deep-learning-containers/blob/master/available_images.md#huggingface-training-containers) to make it easier than ever to train Hugging Face Transformer models in [Amazon SageMaker](https://aws.amazon.com/sagemaker/). +Hugging Face and Amazon are introducing new [Hugging Face Deep Learning Containers (DLCs)](#deep-learning-container-dlc-overview) to make it easier than ever to train Hugging Face Transformer models in [Amazon SageMaker](https://aws.amazon.com/sagemaker/). + +You can find a full list of all available [Hugging Face Deep Learning Containers](#deep-learning-container-dlc-overview) at the end of this page. To learn how to access and use the new Hugging Face DLCs with the Amazon SageMaker Python SDK, check out the guides and resources below. --- -## Deep Learning Container (DLC) overview - -The Deep Learning Container are in every available where Amazon SageMaker is available. You can see the [AWS region table](https://aws.amazon.com/about-aws/global-infrastructure/regional-product-services/) for all AWS global infrastructure. To get an detailed overview of all included packages look [here in the release notes](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/deep-learning-containers-images.html). - -| 🤗 Transformers version | 🤗 Datasets version | PyTorch/TensorFlow version | type | device | Python Version | Example `image_uri` | -| ----------------------- | ------------------- | -------------------------- | -------- | ------ | -------------- | --------------------------------------------------------------------------------------------------------------------------------- | -| 4.4.2 | 1.5.0 | PyTorch 1.6.0 | training | GPU | 3.6 | `763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-pytorch-training:1.6.0-transformers4.4.2-gpu-py36-cu110-ubuntu18.04` | -| 4.4.2 | 1.5.0 | TensorFlow 2.4.1 | training | GPU | 3.7 | `763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-tensorflow-training:2.4.1-transformers4.4.2-gpu-py37-cu110-ubuntu18.04` | - ---- ## Getting Started: Train a 🤗 Transformers Model @@ -194,8 +186,8 @@ You can find here a list of the official notebooks provided by Hugging Face. | [Spot Instances and continues training](https://github.com/huggingface/notebooks/blob/master/sagemaker/05_spot_instances/sagemaker-notebook.ipynb) | End-to-End to Text-Classification example using spot instances with continued training. | | [SageMaker Metrics](https://github.com/huggingface/notebooks/blob/master/sagemaker/06_sagemaker_metrics/sagemaker-notebook.ipynb) | End-to-End to Text-Classification example using SageMaker Metrics to extract and log metrics during training | | [Distributed Training Data Parallelism Tensorflow](https://github.com/huggingface/notebooks/blob/master/sagemaker/07_tensorflow_distributed_training_data_parallelism/sagemaker-notebook.ipynb) | End-to-End distributed binary Text-Classification example using `Keras` and `TensorFlow` -| [Distributed Seq2Seq Training with Data Parallelism and BART](https://github.com/huggingface/notebooks/blob/master/sagemaker/08_distributed_summarization_bart_t5/sagemaker-notebook.ipynb) | End-to-End distributed summarization example `BART-large` and 🤗 Transformers example script for `summarization` | - +| [Distributed Seq2Seq Training with Data Parallelism and BART](https://github.com/huggingface/notebooks/blob/master/sagemaker/08_distributed_summarization_bart_t5/sagemaker-notebook.ipynb) | End-to-End distributed summarization example with `BART-large` and 🤗 Transformers example script for `summarization` | +| [Image Classification using Vision Transformer](https://github.com/huggingface/notebooks/blob/master/sagemaker/09_image_classification_vision_transformer/sagemaker-notebook.ipynb) | End-to-End image classification example with `Vision Transformers` | --- @@ -382,6 +374,24 @@ huggingface_estimator = HuggingFace( ``` + +## Deep Learning Container (DLC) overview + +The Deep Learning Container are in every available where Amazon SageMaker is available. You can see the [AWS region table](https://aws.amazon.com/about-aws/global-infrastructure/regional-product-services/) for all AWS global infrastructure. To get an detailed overview of all included packages look [here in the release notes](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/deep-learning-containers-images.html). + +| 🤗 Transformers version | 🤗 Datasets version | PyTorch/TensorFlow version | type | device | Python Version | Example `image_uri` | +| ----------------------- | ------------------- | -------------------------- | -------- | ------ | -------------- | --------------------------------------------------------------------------------------------------------------------------------- | +| 4.4.2 | 1.5.0 | PyTorch 1.6.0 | training | GPU | 3.6 | `763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-pytorch-training:1.6.0-transformers4.4.2-gpu-py36-cu110-ubuntu18.04` | +| 4.4.2 | 1.5.0 | TensorFlow 2.4.1 | training | GPU | 3.7 | `763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-tensorflow-training:2.4.1-transformers4.4.2-gpu-py37-cu110-ubuntu18.04` | +| 4.5.0 | 1.5.0 | PyTorch 1.6.0 | training | GPU | 3.6 | `763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-pytorch-training:1.6.0-transformers4.4.2-gpu-py36-cu110-ubuntu18.04` | +| 4.5.0 | 1.5.0 | TensorFlow 2.4.1 | training | GPU | 3.7 | `763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-tensorflow-training:2.4.1-transformers4.5.0-gpu-py37-cu110-ubuntu18.04` | +| 4.6.1 | 1.6.2 | PyTorch 1.6.0 | training | GPU | 3.6 | `763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-pytorch-training:1.6.0-transformers4.5.0-gpu-py36-cu110-ubuntu18.04` | +| 4.6.1 | 1.6.2 | PyTorch 1.7.1 | training | GPU | 3.6 | `763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-pytorch-training:1.7.1-transformers4.6.1-gpu-py36-cu110-ubuntu18.04` | +| 4.6.1 | 1.6.2 | TensorFlow 2.4.1 | training | GPU | 3.7 | `763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-tensorflow-training:2.4.1-transformers4.6.1-gpu-py37-cu110-ubuntu18.04` | + +--- + + ## Additional Resources - [Announcement Blog Post](https://huggingface.co/blog/the-partnership-amazon-sagemaker-and-hugging-face)