From d122bf0f730e05113a2ae27b54df79426ecd9475 Mon Sep 17 00:00:00 2001 From: lvmingfu Date: Thu, 14 Apr 2022 10:28:46 +0800 Subject: [PATCH] fix error links for master --- .../mindspore/source_en/migration_guide/neural_network_debug.md | 2 +- tutorials/experts/source_en/dataset/optimize.ipynb | 2 +- tutorials/experts/source_zh_cn/others/gradient_accumulation.md | 2 +- 3 files changed, 3 insertions(+), 3 deletions(-) diff --git a/docs/mindspore/source_en/migration_guide/neural_network_debug.md b/docs/mindspore/source_en/migration_guide/neural_network_debug.md index 5434992da9..f2fd0d58b2 100644 --- a/docs/mindspore/source_en/migration_guide/neural_network_debug.md +++ b/docs/mindspore/source_en/migration_guide/neural_network_debug.md @@ -37,7 +37,7 @@ This section introduces the problems and solutions during Network Debugging proc For script development and network process debugging, we recommend using the PyNative mode for debugging. The PyNative mode supports executing single operators, normal functions and networks, as well as separate operations for computing gradients. In PyNative mode, you can easily set breakpoints and get intermediate results of network execution, and you can also debug the network by means of pdb. -By default, MindSpore is in Graph mode, which can be set as PyNative mode via `context.set_context(mode=context.PYNATIVE_MODE)`. Related examples can be found in [Debugging With PyNative Mode](https://www.mindspore.cn/tutorials/en/master/advanced/pynative_graph/pynative.html). +By default, MindSpore is in Graph mode, which can be set as PyNative mode via `context.set_context(mode=context.PYNATIVE_MODE)`. Related examples can be found in [Debugging With PyNative Mode](https://www.mindspore.cn/tutorials/zh-CN/master/advanced/pynative_graph/pynative.html). #### Getting More Error Messages diff --git a/tutorials/experts/source_en/dataset/optimize.ipynb b/tutorials/experts/source_en/dataset/optimize.ipynb index cf8dfd1b9a..72b653c7bd 100644 --- a/tutorials/experts/source_en/dataset/optimize.ipynb +++ b/tutorials/experts/source_en/dataset/optimize.ipynb @@ -7,7 +7,7 @@ "\n", "`Ascend` `GPU` `CPU` `Data Preparation`\n", "\n", - "[![Download Notebook](https://mindspore-website.obs.cn-north-4.myhuaweicloud.com/website-images/master/resource/_static/logo_notebook_en.png)](https://mindspore-website.obs.cn-north-4.myhuaweicloud.com/master/tutorials/experts/en/dataset/mindspore_optimize.ipynb) [![View Source On Gitee](https://mindspore-website.obs.cn-north-4.myhuaweicloud.com/website-images/master/resource/_static/logo_source_en.png)](https://gitee.com/mindspore/docs/blob/master/tutorials/experts/source_en/dataset/optimize.ipynb)" + "[![Download Notebook](https://mindspore-website.obs.cn-north-4.myhuaweicloud.com/website-images/master/resource/_static/logo_notebook_en.png)](https://mindspore-website.obs.cn-north-4.myhuaweicloud.com/notebook/master/tutorials/experts/en/dataset/mindspore_optimize.ipynb) [![View Source On Gitee](https://mindspore-website.obs.cn-north-4.myhuaweicloud.com/website-images/master/resource/_static/logo_source_en.png)](https://gitee.com/mindspore/docs/blob/master/tutorials/experts/source_en/dataset/optimize.ipynb)" ], "metadata": {} }, diff --git a/tutorials/experts/source_zh_cn/others/gradient_accumulation.md b/tutorials/experts/source_zh_cn/others/gradient_accumulation.md index 78761ea365..4f47f52002 100644 --- a/tutorials/experts/source_zh_cn/others/gradient_accumulation.md +++ b/tutorials/experts/source_zh_cn/others/gradient_accumulation.md @@ -293,7 +293,7 @@ if __name__ == "__main__": **验证模型:** -通过ModelZoo中`lenet`目录下的[eval.py](https://gitee.com/mindspore/models/blob/master/official/cv/lenet/train.py)，使用保存的CheckPoint文件，加载验证数据集，进行验证。 +通过ModelZoo中`lenet`目录下的[eval.py](https://gitee.com/mindspore/models/blob/master/official/cv/lenet/eval.py)，使用保存的CheckPoint文件，加载验证数据集，进行验证。 ```bash python eval.py --data_path=./MNIST_Data --ckpt_path=./gradient_accumulation.ckpt --device_target=GPU -- Gitee