From 105a4eec404f32b9c2d23425577f5c2d1a4a3051 Mon Sep 17 00:00:00 2001 From: Nihal Harish Date: Fri, 15 May 2020 14:44:23 -0700 Subject: [PATCH 1/5] Update sagemaker.md --- docs/sagemaker.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/sagemaker.md b/docs/sagemaker.md index 94d93b837..d8c9cde9d 100644 --- a/docs/sagemaker.md +++ b/docs/sagemaker.md @@ -43,7 +43,7 @@ This library `smdebug` itself supports versions other than the ones listed above | [TensorFlow](tensorflow.md) | 1.13, 1.14, 1.15 | | Keras (with TensorFlow backend) | 2.3 | | [MXNet](mxnet.md) | 1.4, 1.5, 1.6 | -| [PyTorch](pytorch.md) | 1.2, 1.3 | +| [PyTorch](pytorch.md) | 1.2, 1.3, 1.4, 1.5 | | [XGBoost](xgboost.md) | [As Framework](xgboost.md#use-xgboost-as-a-framework) | #### Setting up SageMaker Debugger with your script on your container From fab3cf5f99bbeec7f11192876c1d8514d3734042 Mon Sep 17 00:00:00 2001 From: Nihal Harish Date: Fri, 15 May 2020 14:50:28 -0700 Subject: [PATCH 2/5] Update sagemaker.md --- docs/sagemaker.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/docs/sagemaker.md b/docs/sagemaker.md index d8c9cde9d..d502563e0 100644 --- a/docs/sagemaker.md +++ b/docs/sagemaker.md @@ -27,9 +27,9 @@ Here's a list of frameworks and versions which support this experience. | Framework | Version | | --- | --- | -| [TensorFlow](tensorflow.md) | 1.15 | +| [TensorFlow](tensorflow.md) | 1.15, 2.1 | | [MXNet](mxnet.md) | 1.6 | -| [PyTorch](pytorch.md) | 1.3 | +| [PyTorch](pytorch.md) | 1.3, 1.4 | | [XGBoost](xgboost.md) | >=0.90-2 [As Built-in algorithm](xgboost.md#use-xgboost-as-a-built-in-algorithm)| More details for the deep learning frameworks on which containers these are can be found here: [SageMaker Framework Containers](https://docs.aws.amazon.com/sagemaker/latest/dg/pre-built-containers-frameworks-deep-learning.html) and [AWS Deep Learning Containers](https://aws.amazon.com/machine-learning/containers/). You do not have to specify any training container image if you want to use them on SageMaker. You only need to specify the version above to use these containers. @@ -40,7 +40,7 @@ This library `smdebug` itself supports versions other than the ones listed above | Framework | Versions | | --- | --- | -| [TensorFlow](tensorflow.md) | 1.13, 1.14, 1.15 | +| [TensorFlow](tensorflow.md) | 1.13, 1.14, 1.15, 2.1, 2.2 | | Keras (with TensorFlow backend) | 2.3 | | [MXNet](mxnet.md) | 1.4, 1.5, 1.6 | | [PyTorch](pytorch.md) | 1.2, 1.3, 1.4, 1.5 | From a8de03b041aa22783e7818df82f13d3db4c65e43 Mon Sep 17 00:00:00 2001 From: Nihal Harish Date: Fri, 15 May 2020 14:52:15 -0700 Subject: [PATCH 3/5] Update sagemaker.md --- docs/sagemaker.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/sagemaker.md b/docs/sagemaker.md index d502563e0..224a71dee 100644 --- a/docs/sagemaker.md +++ b/docs/sagemaker.md @@ -29,7 +29,7 @@ Here's a list of frameworks and versions which support this experience. | --- | --- | | [TensorFlow](tensorflow.md) | 1.15, 2.1 | | [MXNet](mxnet.md) | 1.6 | -| [PyTorch](pytorch.md) | 1.3, 1.4 | +| [PyTorch](pytorch.md) | 1.3, 1.4, 1.5 | | [XGBoost](xgboost.md) | >=0.90-2 [As Built-in algorithm](xgboost.md#use-xgboost-as-a-built-in-algorithm)| More details for the deep learning frameworks on which containers these are can be found here: [SageMaker Framework Containers](https://docs.aws.amazon.com/sagemaker/latest/dg/pre-built-containers-frameworks-deep-learning.html) and [AWS Deep Learning Containers](https://aws.amazon.com/machine-learning/containers/). You do not have to specify any training container image if you want to use them on SageMaker. You only need to specify the version above to use these containers. From ef934056d102143e2145e62d50b67bc29b394f9d Mon Sep 17 00:00:00 2001 From: Nihal Harish Date: Fri, 15 May 2020 15:33:35 -0700 Subject: [PATCH 4/5] Update sagemaker.md --- docs/sagemaker.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/sagemaker.md b/docs/sagemaker.md index 224a71dee..36d9029a8 100644 --- a/docs/sagemaker.md +++ b/docs/sagemaker.md @@ -29,7 +29,7 @@ Here's a list of frameworks and versions which support this experience. | --- | --- | | [TensorFlow](tensorflow.md) | 1.15, 2.1 | | [MXNet](mxnet.md) | 1.6 | -| [PyTorch](pytorch.md) | 1.3, 1.4, 1.5 | +| [PyTorch](pytorch.md) | 1.4, 1.5 | | [XGBoost](xgboost.md) | >=0.90-2 [As Built-in algorithm](xgboost.md#use-xgboost-as-a-built-in-algorithm)| More details for the deep learning frameworks on which containers these are can be found here: [SageMaker Framework Containers](https://docs.aws.amazon.com/sagemaker/latest/dg/pre-built-containers-frameworks-deep-learning.html) and [AWS Deep Learning Containers](https://aws.amazon.com/machine-learning/containers/). You do not have to specify any training container image if you want to use them on SageMaker. You only need to specify the version above to use these containers. From aa8f4a9eadd87aaec56f2f783f136a5dcd77274e Mon Sep 17 00:00:00 2001 From: Nihal Harish Date: Tue, 19 May 2020 14:37:51 -0700 Subject: [PATCH 5/5] Update sagemaker.md --- docs/sagemaker.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/sagemaker.md b/docs/sagemaker.md index 36d9029a8..01c03568b 100644 --- a/docs/sagemaker.md +++ b/docs/sagemaker.md @@ -44,7 +44,7 @@ This library `smdebug` itself supports versions other than the ones listed above | Keras (with TensorFlow backend) | 2.3 | | [MXNet](mxnet.md) | 1.4, 1.5, 1.6 | | [PyTorch](pytorch.md) | 1.2, 1.3, 1.4, 1.5 | -| [XGBoost](xgboost.md) | [As Framework](xgboost.md#use-xgboost-as-a-framework) | +| [XGBoost](xgboost.md) | 0.90-2, 1.0-1 | #### Setting up SageMaker Debugger with your script on your container