From f1e71b241844c440e3e0e79e95d612eef1da2b3c Mon Sep 17 00:00:00 2001 From: Frank Liu Date: Wed, 12 Jul 2023 18:29:09 -0700 Subject: [PATCH] [docs] Updates README for pytorch 2.0.1 --- README.md | 1 + engines/pytorch/pytorch-engine/README.md | 71 ++++++++++++------------ 2 files changed, 37 insertions(+), 35 deletions(-) diff --git a/README.md b/README.md index a2c4aaec1393..2fbc46661c83 100644 --- a/README.md +++ b/README.md @@ -85,6 +85,7 @@ The following pseudocode demonstrates running training: ## Release Notes +* [0.23.0](https://github.com/deepjavalibrary/djl/releases/tag/v0.23.0) ([Code](https://github.com/deepjavalibrary/djl/tree/v0.23.0)) * [0.22.1](https://github.com/deepjavalibrary/djl/releases/tag/v0.22.1) ([Code](https://github.com/deepjavalibrary/djl/tree/v0.22.1)) * [0.21.0](https://github.com/deepjavalibrary/djl/releases/tag/v0.21.0) ([Code](https://github.com/deepjavalibrary/djl/tree/v0.21.0)) * [0.20.0](https://github.com/deepjavalibrary/djl/releases/tag/v0.20.0) ([Code](https://github.com/deepjavalibrary/djl/tree/v0.20.0)) diff --git a/engines/pytorch/pytorch-engine/README.md b/engines/pytorch/pytorch-engine/README.md index 4332f7afd447..9c300f1cb192 100644 --- a/engines/pytorch/pytorch-engine/README.md +++ b/engines/pytorch/pytorch-engine/README.md @@ -46,6 +46,7 @@ The following table illustrates which pytorch version that DJL supports: | PyTorch engine version | PyTorch native library version | |------------------------|-------------------------------------------| +| pytorch-engine:0.23.0 | 1.11.0, 1.12.1, **1.13.1**, 2.0.1 | | pytorch-engine:0.22.1 | 1.11.0, 1.12.1, **1.13.1**, 2.0.0 | | pytorch-engine:0.21.0 | 1.11.0, 1.12.1, **1.13.1** | | pytorch-engine:0.20.0 | 1.11.0, 1.12.1, **1.13.0** | @@ -109,21 +110,21 @@ export PYTORCH_FLAVOR=cpu ### macOS For macOS, you can use the following library: -- ai.djl.pytorch:pytorch-jni:2.0.0-0.22.1 -- ai.djl.pytorch:pytorch-native-cpu:2.0.0:osx-x86_64 +- ai.djl.pytorch:pytorch-jni:2.0.1-0.23.0 +- ai.djl.pytorch:pytorch-native-cpu:2.0.1:osx-x86_64 ```xml ai.djl.pytorch pytorch-native-cpu osx-x86_64 - 2.0.0 + 2.0.1 runtime ai.djl.pytorch pytorch-jni - 2.0.0-0.22.1 + 2.0.1-0.23.0 runtime ``` @@ -133,21 +134,21 @@ For macOS, you can use the following library: ### macOS M1 For macOS M1, you can use the following library: -- ai.djl.pytorch:pytorch-jni:2.0.0-0.22.1 -- ai.djl.pytorch:pytorch-native-cpu:2.0.0:osx-aarch64 +- ai.djl.pytorch:pytorch-jni:2.0.1-0.23.0 +- ai.djl.pytorch:pytorch-native-cpu:2.0.1:osx-aarch64 ```xml ai.djl.pytorch pytorch-native-cpu osx-aarch64 - 2.0.0 + 2.0.1 runtime ai.djl.pytorch pytorch-jni - 2.0.0-0.22.1 + 2.0.1-0.23.0 runtime ``` @@ -158,29 +159,29 @@ installed on your GPU machine, you can use one of the following library: #### Linux GPU -- ai.djl.pytorch:pytorch-jni:2.0.0-0.22.1 -- ai.djl.pytorch:pytorch-native-cu118:2.0.0:linux-x86_64 - CUDA 11.8 +- ai.djl.pytorch:pytorch-jni:2.0.1-0.23.0 +- ai.djl.pytorch:pytorch-native-cu118:2.0.1:linux-x86_64 - CUDA 11.8 ```xml ai.djl.pytorch pytorch-native-cu118 linux-x86_64 - 2.0.0 + 2.0.1 runtime ai.djl.pytorch pytorch-jni - 2.0.0-0.22.1 + 2.0.1-0.23.0 runtime ``` ### Linux CPU -- ai.djl.pytorch:pytorch-jni:2.0.0-0.22.1 -- ai.djl.pytorch:pytorch-native-cpu:2.0.0:linux-x86_64 +- ai.djl.pytorch:pytorch-jni:2.0.1-0.23.0 +- ai.djl.pytorch:pytorch-native-cpu:2.0.1:linux-x86_64 ```xml @@ -188,20 +189,20 @@ installed on your GPU machine, you can use one of the following library: pytorch-native-cpu linux-x86_64 runtime - 2.0.0 + 2.0.1 ai.djl.pytorch pytorch-jni - 2.0.0-0.22.1 + 2.0.1-0.23.0 runtime ``` ### For aarch64 build -- ai.djl.pytorch:pytorch-jni:2.0.0-0.22.1 -- ai.djl.pytorch:pytorch-native-cpu-precxx11:2.0.0:linux-aarch64 +- ai.djl.pytorch:pytorch-jni:2.0.1-0.23.0 +- ai.djl.pytorch:pytorch-native-cpu-precxx11:2.0.1:linux-aarch64 ```xml @@ -209,12 +210,12 @@ installed on your GPU machine, you can use one of the following library: pytorch-native-cpu-precxx11 linux-aarch64 runtime - 2.0.0 + 2.0.1 ai.djl.pytorch pytorch-jni - 2.0.0-0.22.1 + 2.0.1-0.23.0 runtime ``` @@ -224,22 +225,22 @@ installed on your GPU machine, you can use one of the following library: We also provide packages for the system like CentOS 7/Ubuntu 14.04 with GLIBC >= 2.17. All the package were built with GCC 7, we provided a newer `libstdc++.so.6.24` in the package that contains `CXXABI_1.3.9` to use the package successfully. -- ai.djl.pytorch:pytorch-jni:2.0.0-0.22.1 -- ai.djl.pytorch:pytorch-native-cu118-precxx11:2.0.0:linux-x86_64 - CUDA 11.8 -- ai.djl.pytorch:pytorch-native-cpu-precxx11:2.0.0:linux-x86_64 - CPU +- ai.djl.pytorch:pytorch-jni:2.0.1-0.23.0 +- ai.djl.pytorch:pytorch-native-cu118-precxx11:2.0.1:linux-x86_64 - CUDA 11.8 +- ai.djl.pytorch:pytorch-native-cpu-precxx11:2.0.1:linux-x86_64 - CPU ```xml ai.djl.pytorch pytorch-native-cu118-precxx11 linux-x86_64 - 2.0.0 + 2.0.1 runtime ai.djl.pytorch pytorch-jni - 2.0.0-0.22.1 + 2.0.1-0.23.0 runtime ``` @@ -249,13 +250,13 @@ All the package were built with GCC 7, we provided a newer `libstdc++.so.6.24` i ai.djl.pytorch pytorch-native-cpu-precxx11 linux-x86_64 - 2.0.0 + 2.0.1 runtime ai.djl.pytorch pytorch-jni - 2.0.0-0.22.1 + 2.0.1-0.23.0 runtime ``` @@ -270,29 +271,29 @@ For the Windows platform, you can choose between CPU and GPU. #### Windows GPU -- ai.djl.pytorch:pytorch-jni:2.0.0-0.22.1 -- ai.djl.pytorch:pytorch-native-cu118:2.0.0:win-x86_64 - CUDA 11.8 +- ai.djl.pytorch:pytorch-jni:2.0.1-0.23.0 +- ai.djl.pytorch:pytorch-native-cu118:2.0.1:win-x86_64 - CUDA 11.8 ```xml ai.djl.pytorch pytorch-native-cu118 win-x86_64 - 2.0.0 + 2.0.1 runtime ai.djl.pytorch pytorch-jni - 2.0.0-0.22.1 + 2.0.1-0.23.0 runtime ``` ### Windows CPU -- ai.djl.pytorch:pytorch-jni:2.0.0-0.22.1 -- ai.djl.pytorch:pytorch-native-cpu:2.0.0:win-x86_64 +- ai.djl.pytorch:pytorch-jni:2.0.1-0.23.0 +- ai.djl.pytorch:pytorch-native-cpu:2.0.1:win-x86_64 ```xml @@ -300,12 +301,12 @@ For the Windows platform, you can choose between CPU and GPU. pytorch-native-cpu win-x86_64 runtime - 2.0.0 + 2.0.1 ai.djl.pytorch pytorch-jni - 2.0.0-0.22.1 + 2.0.1-0.23.0 runtime ```