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update dependent
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tp-nan committed Jan 17, 2024
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8 changes: 6 additions & 2 deletions docs/installation.mdx
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Expand Up @@ -14,9 +14,9 @@ The basic environment is as follows:
| Dependency | Version | Remarks |
|--------------------|:------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| `cuda` | >= 11.0 | - The CUDA version must be consistent with the version that PyTorch depends on (for the convenience of `torch.utils.cpp_extension` to compile code on the fly). <br />- Compatibility testing with CUDA 10.2(no support for c++17) is no longer performed. |
| `pytorch` | >= 1.10.0(cuda11) | - Compatibility testing is no longer performed for `c++14/cuda-10.2/pytorch==1.10.2`, but you may still be able to run it with simple modifications. |
| `pytorch` | >= 1.10.2(cuda11) | - Compatibility testing is no longer performed for `c++14/cuda-10.2/pytorch==1.10.2`, but you may still be able to run it with simple modifications. |
| `opencv`(optional) | 4.x | At least the core, imgproc, imgcodecs, and highgui modules are included. |
| `tensorrt`(optional) |>= 7.2<br /><= 9.1.0.4| - There is a [memory leak](https://github.com/NVIDIA/TensorRT/issues/351) in TensorRT 7.0 with dynamic inputs.<br />- TensorRT 7.1 and earlier cannot directly INT8-quantize models with dynamic inputs.
| `tensorrt`(optional) |>= 7.2<br /><= 9.2| - There is a [memory leak](https://github.com/NVIDIA/TensorRT/issues/351) in TensorRT 7.0 with dynamic inputs.


:::note
Expand All @@ -28,6 +28,10 @@ The easiest way is to choose NGC mirror for source code compilation (official mi

- Minimum support nvcr.io/nvidia/pytorch:21.07-py3 (Starting from 0.3.2rc3)
- Maximum support nvcr.io/nvidia/pytorch:23.08-py3
- Latest test version: nvcr.io/nvidia/pytorch:22.12-py3

If you encounter any compilation or runtime issues inside the Docker container, please submit an issue.


First, clone the code:

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Expand Up @@ -15,9 +15,9 @@ type: explainer
| 依赖 | 版本 | 备注 |
|------------------|:-----------------------|---------------------------------------------------------------------------------------------------------------------------------------------|
| `cuda` | >= 11.0 | - 与PyTorch依赖的cuda版本必须一致(便于`torch.utils.cpp_extension`即时编译代码) <br />- 不再对CUDA 10.2(不支持c++17)的兼容进行测试。 |
| `pytorch` | >= 1.10.0(cuda11) | - 对于`c++14/cuda-10.2/pytorch==1.10.2`不再进行兼容测试,然而通过简单修改,您可能仍可运行。 |
| `pytorch` | >= 1.10.2(cuda11) | - 对于`c++14/cuda-10.2/pytorch==1.10.2`不再进行兼容测试,然而通过简单修改,您可能仍可运行。 |
| `opencv`(可选) | 3.x, 4.x | 至少包含 core, imgproc,imgcodecs 和 highgui 四个模块 |
| `tensorrt`(可选) | >= 7.2(Starting from 0.3.2rc3)<br /><= 9.1.0.4 | - tensorrt 7.0 动态输入下存在[内存泄漏](https://github.com/NVIDIA/TensorRT/issues/351)<br />- tensorrt 7.1 及以下无法直接int8化动态输入的模型 |
| `tensorrt`(可选) | >= 7.2(Starting from 0.3.2rc3)<br /><= 9.2 | - tensorrt 7.0 动态输入下存在[内存泄漏](https://github.com/NVIDIA/TensorRT/issues/351) |

:::note
以上依赖项均来源于默认存在的特定计算后端。构筑c++核心不依赖于以上任意一项。
Expand All @@ -27,6 +27,9 @@ type: explainer
最简单的方式是可以选择<font color='Brown'>NGC镜像</font>进行源码编译(低版本驱动依靠 Forward Compatibility 或者 Minor Version Compatibility 依然可能跑起来官方镜像)。
- 最低支持 nvcr.io/nvidia/pytorch:21.07-py3(从0.3.2rc3开始)
- 最高支持 nvcr.io/nvidia/pytorch:23.08-py3
- 测试版本 nvcr.io/nvidia/pytorch:22.12-py3

如果在docker容器内遇到编译或者运行问题,请提交issue。

首先,克隆代码:

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