From 71d60b408a0de731ac7eb7aefa514848de09f44d Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Xavier=20Dupr=C3=A9?= Date: Thu, 7 Sep 2023 19:49:30 +0200 Subject: [PATCH] Fix links to notebooks broken because the notebooks were moved (#17446) --- docs/ecosystem/index.md | 2 +- docs/execution-providers/TensorRT-ExecutionProvider.md | 2 +- .../community-maintained/TVM-ExecutionProvider.md | 4 ++-- 3 files changed, 4 insertions(+), 4 deletions(-) diff --git a/docs/ecosystem/index.md b/docs/ecosystem/index.md index d1e52e8678..12c8335f64 100644 --- a/docs/ecosystem/index.md +++ b/docs/ecosystem/index.md @@ -21,7 +21,7 @@ ONNX Runtime functions as part of an ecosystem of tools and platforms to deliver * [Azure Container Instance: Facial Expression Recognition](https://github.com/Azure/MachineLearningNotebooks/blob/master/how-to-use-azureml/deployment/onnx/onnx-inference-facial-expression-recognition-deploy.ipynb){:target="_blank"} * [Azure Container Instance: MNIST](https://github.com/Azure/MachineLearningNotebooks/blob/master/how-to-use-azureml/deployment/onnx/onnx-inference-mnist-deploy.ipynb){:target="_blank"} * [Azure Container Instance: Image classification (Resnet)](https://github.com/Azure/MachineLearningNotebooks/blob/master/how-to-use-azureml/deployment/onnx/onnx-modelzoo-aml-deploy-resnet50.ipynb){:target="_blank"} -* [Azure Kubernetes Services: FER+](https://github.com/microsoft/onnxruntime/blob/main/docs/python/inference/notebooks/onnx-inference-byoc-gpu-cpu-aks.ipynb){:target="_blank"} +* [Azure Kubernetes Services: FER+](https://github.com/microsoft/onnxruntime/blob/main/docs/python/notebooks/onnx-inference-byoc-gpu-cpu-aks.ipynb){:target="_blank"} * [Azure IoT Sedge (Intel UP2 device with OpenVINO)](https://github.com/Azure-Samples/onnxruntime-iot-edge/blob/master/AzureML-OpenVINO/README.md){:target="_blank"} * [Automated Machine Learning](https://github.com/Azure/MachineLearningNotebooks/blob/master/how-to-use-azureml/automated-machine-learning/classification-bank-marketing-all-features/auto-ml-classification-bank-marketing-all-features.ipynb){:target="_blank"} diff --git a/docs/execution-providers/TensorRT-ExecutionProvider.md b/docs/execution-providers/TensorRT-ExecutionProvider.md index 1df0c467b1..a304c41270 100644 --- a/docs/execution-providers/TensorRT-ExecutionProvider.md +++ b/docs/execution-providers/TensorRT-ExecutionProvider.md @@ -540,5 +540,5 @@ This example shows how to run the Faster R-CNN model on TensorRT execution provi ./onnxruntime_perf_test -r 1 -e tensorrt -i "trt_fp16_enable|true" /path/to/onnx/your_inferred_model.onnx ``` -Please see [this Notebook](https://github.com/microsoft/onnxruntime/blob/main/docs/python/inference/notebooks/onnx-inference-byoc-gpu-cpu-aks.ipynb) for an example of running a model on GPU using ONNX Runtime through Azure Machine Learning Services. +Please see [this Notebook](https://github.com/microsoft/onnxruntime/blob/main/docs/python/notebooks/onnx-inference-byoc-gpu-cpu-aks.ipynb) for an example of running a model on GPU using ONNX Runtime through Azure Machine Learning Services. diff --git a/docs/execution-providers/community-maintained/TVM-ExecutionProvider.md b/docs/execution-providers/community-maintained/TVM-ExecutionProvider.md index 50932074ca..3338a25374 100644 --- a/docs/execution-providers/community-maintained/TVM-ExecutionProvider.md +++ b/docs/execution-providers/community-maintained/TVM-ExecutionProvider.md @@ -233,7 +233,7 @@ It is also possible to use a precompiled model. The compiled model can be obtained using the [OctoML platform](https://onnx.octoml.ai) or compiled directly (see **Support precompiled model** section in -[Sample notebook for ResNet50 inference with TVM EP](https://github.com/microsoft/onnxruntime/blob/main/docs/python/inference/notebooks/onnxruntime-tvm-tutorial.ipynb) +[Sample notebook for ResNet50 inference with TVM EP](https://github.com/microsoft/onnxruntime/blob/main/docs/python/notebooks/onnxruntime-tvm-tutorial.ipynb) for more information on model compilation). In order to use the precompiled model, only need to pass two options: @@ -247,7 +247,7 @@ the files of the precompiled model are located. You can read more about these options in section [Configuration options](#configuration-options) above. ## Samples -- [Sample notebook for ResNet50 inference with TVM EP](https://github.com/microsoft/onnxruntime/blob/main/docs/python/inference/notebooks/onnxruntime-tvm-tutorial.ipynb) +- [Sample notebook for ResNet50 inference with TVM EP](https://github.com/microsoft/onnxruntime/blob/main/docs/python/notebooks/onnxruntime-tvm-tutorial.ipynb) ## Known issues - At this moment, the TVM EP has only been verified on UNIX/Linux and Windows systems.