From 53312681362952586bb2044a0fcea52a2dec43c7 Mon Sep 17 00:00:00 2001 From: Deyu Huang Date: Thu, 17 Mar 2022 10:43:19 +0800 Subject: [PATCH] Rename the default branch to main (#1880) Rename the default branch to main Signed-off-by: Deyu Huang --- .github/ISSUE_TEMPLATE/bug-performance-issue.md | 2 +- CONTRIBUTING.md | 2 +- .../azure_pipelines/onnxruntime_nightly_test.yml | 2 +- .../pretrained_model_test-matrix.yml | 2 +- tutorials/README.md | 16 ++++++++-------- 5 files changed, 12 insertions(+), 12 deletions(-) diff --git a/.github/ISSUE_TEMPLATE/bug-performance-issue.md b/.github/ISSUE_TEMPLATE/bug-performance-issue.md index d26ed6739..fd91f5d64 100644 --- a/.github/ISSUE_TEMPLATE/bug-performance-issue.md +++ b/.github/ISSUE_TEMPLATE/bug-performance-issue.md @@ -7,7 +7,7 @@ about: Use this template for reporting a bug or a performance issue. **Dubugging advice** [delete this section if it doesn't solve your issue] - Add a `--opset` flag with the highest possible opset you can use. Some ops only convert in higher opsets. -- Try installing the latest tf2onnx from master. Some bug fixes might not have been released to PyPI. Run `pip uninstall tf2onnx` and `pip install git+https://github.com/onnx/tensorflow-onnx` +- Try installing the latest tf2onnx from main. Some bug fixes might not have been released to PyPI. Run `pip uninstall tf2onnx` and `pip install git+https://github.com/onnx/tensorflow-onnx` - If using a saved model, use the Tensorflow `saved_model_cli` to determine the correct `--tag` and `--signature_def` flags to use. If the signature you need is not listed, use the `--concrete_function` flag to index into the model's defined functions. - If your model was made in tf1.x, try running tf2onnx in a venv with tensorflow 1.x installed. tf2.x should be able to read tf1 models, but sometimes there are bugs. diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md index 87541c100..c7d863e1b 100644 --- a/CONTRIBUTING.md +++ b/CONTRIBUTING.md @@ -11,7 +11,7 @@ We're always looking for your help to fix bugs and improve the product. Create a 4. Make and checkin your changes along with unit tests 5. git commit your changes 6. git push origin HEAD -7. To request merge into master send a pull request from the web ui +7. To request merge into main send a pull request from the web ui https://github.com/onnx/tensorflow-onnx. diff --git a/ci_build/azure_pipelines/onnxruntime_nightly_test.yml b/ci_build/azure_pipelines/onnxruntime_nightly_test.yml index 632d563b7..e556677a2 100644 --- a/ci_build/azure_pipelines/onnxruntime_nightly_test.yml +++ b/ci_build/azure_pipelines/onnxruntime_nightly_test.yml @@ -107,5 +107,5 @@ schedules: displayName: Daily onnxruntime nightly unittest branches: include: - - master + - main always: true diff --git a/ci_build/azure_pipelines/pretrained_model_test-matrix.yml b/ci_build/azure_pipelines/pretrained_model_test-matrix.yml index d14fcdcda..1d712ddf5 100755 --- a/ci_build/azure_pipelines/pretrained_model_test-matrix.yml +++ b/ci_build/azure_pipelines/pretrained_model_test-matrix.yml @@ -60,5 +60,5 @@ schedules: displayName: pre-trained model test, full matrix branches: include: - - master + - main always: true diff --git a/tutorials/README.md b/tutorials/README.md index d7cdab69c..352552fac 100644 --- a/tutorials/README.md +++ b/tutorials/README.md @@ -5,20 +5,20 @@ The following tutorials show how to convert various models to ONNX. ## Image Classifiers -[efficientnet-edge](https://github.com/onnx/tensorflow-onnx/blob/master/tutorials/efficientnet-edge.ipynb) +[efficientnet-edge](https://github.com/onnx/tensorflow-onnx/blob/main/tutorials/efficientnet-edge.ipynb) -[efficientnet-lite](https://github.com/onnx/tensorflow-onnx/blob/master/tutorials/efficientnet-lite.ipynb) +[efficientnet-lite](https://github.com/onnx/tensorflow-onnx/blob/main/tutorials/efficientnet-lite.ipynb) -[keras-resnet50](https://github.com/onnx/tensorflow-onnx/blob/master/tutorials/keras-resnet50.ipynb) - shows how to convert a keras model via python api +[keras-resnet50](https://github.com/onnx/tensorflow-onnx/blob/main/tutorials/keras-resnet50.ipynb) - shows how to convert a keras model via python api ## Object Detectors -[ssd-mobilenet](https://github.com/onnx/tensorflow-onnx/blob/master/tutorials/ConvertingSSDMobilenetToONNX.ipynb) +[ssd-mobilenet](https://github.com/onnx/tensorflow-onnx/blob/main/tutorials/ConvertingSSDMobilenetToONNX.ipynb) -[efficientdet](https://github.com/onnx/tensorflow-onnx/blob/master/tutorials/efficientdet.ipynb) +[efficientdet](https://github.com/onnx/tensorflow-onnx/blob/main/tutorials/efficientdet.ipynb) -[mobiledet](https://github.com/onnx/tensorflow-onnx/blob/master/tutorials/mobiledet-tflite.ipynb) - shows how to convert a tflite model +[mobiledet](https://github.com/onnx/tensorflow-onnx/blob/main/tutorials/mobiledet-tflite.ipynb) - shows how to convert a tflite model ## Nlp -[Huggingface Bert Example](https://github.com/onnx/tensorflow-onnx/blob/master/tutorials/huggingface-bert.ipynb) +[Huggingface Bert Example](https://github.com/onnx/tensorflow-onnx/blob/main/tutorials/huggingface-bert.ipynb) -[The original Tensorflow Bert model](https://github.com/onnx/tensorflow-onnx/blob/master/tutorials/BertTutorial.ipynb) - depreciated, use huggingface +[The original Tensorflow Bert model](https://github.com/onnx/tensorflow-onnx/blob/main/tutorials/BertTutorial.ipynb) - depreciated, use huggingface