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Merge pull request #38543 from phemmer:github-issue-newline

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PiperOrigin-RevId: 306896868
Change-Id: Id339d8f6279d881f07e5e49fa1de7dea022ff59a
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TensorFlower Gardener 2020-04-16 12:18:18 -07:00
commit 5e4e005194
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34
.github/ISSUE_TEMPLATE/00-bug-issue.md vendored
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@ -10,32 +10,30 @@ labels: 'type:bug'
we only address code/doc bugs, performance issues, feature requests and
build/installation issues on GitHub. tag:bug_template</em>
**System information**
- Have I written custom code (as opposed to using a stock
example script provided in TensorFlow):
- OS Platform and Distribution (e.g.,
Linux Ubuntu 16.04):
- Mobile device (e.g. iPhone 8, Pixel 2, Samsung Galaxy) if
the issue happens on mobile device:
- TensorFlow installed from (source or
binary): - TensorFlow version (use command below):
- Python version: - Bazel
version (if compiling from source):
- GCC/Compiler version (if compiling from
source):
- CUDA/cuDNN version: - GPU model and memory:
**System information**
- Have I written custom code (as opposed to using a stock example script provided in TensorFlow):
- OS Platform and Distribution (e.g., Linux Ubuntu 16.04):
- Mobile device (e.g. iPhone 8, Pixel 2, Samsung Galaxy) if the issue happens on mobile device:
- TensorFlow installed from (source or binary):
- TensorFlow version (use command below):
- Python version:
- Bazel version (if compiling from source):
- GCC/Compiler version (if compiling from source):
- CUDA/cuDNN version:
- GPU model and memory:
You can collect some of this information using our environment capture
[script](https://github.com/tensorflow/tensorflow/tree/master/tools/tf_env_collect.sh)
You can also obtain the TensorFlow version with: 1. TF 1.0: `python -c "import
tensorflow as tf; print(tf.GIT_VERSION, tf.VERSION)"` 2. TF 2.0: `python -c
"import tensorflow as tf; print(tf.version.GIT_VERSION, tf.version.VERSION)"`
You can also obtain the TensorFlow version with:
1. TF 1.0: `python -c "import tensorflow as tf; print(tf.GIT_VERSION, tf.VERSION)"`
2. TF 2.0: `python -c "import tensorflow as tf; print(tf.version.GIT_VERSION, tf.version.VERSION)"`
**Describe the current behavior**
**Describe the expected behavior**
**Standalone code to reproduce the issue**
**Standalone code to reproduce the issue**
Provide a reproducible test case that is the bare minimum necessary to generate
the problem. If possible, please share a link to Colab/Jupyter/any notebook.

33
.github/ISSUE_TEMPLATE/80-performance-issue.md vendored
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@ -11,32 +11,29 @@ As per our
we only address code/doc bugs, performance issues, feature requests and
build/installation issues on GitHub. tag:performance_template</em>
**System information**
- Have I written custom code (as opposed to using a stock
example script provided in TensorFlow):
- OS Platform and Distribution (e.g.,
Linux Ubuntu 16.04):
- Mobile device (e.g. iPhone 8, Pixel 2, Samsung Galaxy) if
the issue happens on mobile device:
- TensorFlow installed from (source or
binary): - TensorFlow version (use command below):
- Python version: - Bazel
version (if compiling from source):
- GCC/Compiler version (if compiling from
source):
- CUDA/cuDNN version: - GPU model and memory:
**System information**
- Have I written custom code (as opposed to using a stock example script provided in TensorFlow):
- OS Platform and Distribution (e.g., Linux Ubuntu 16.04):
- Mobile device (e.g. iPhone 8, Pixel 2, Samsung Galaxy) if the issue happens on mobile device:
- TensorFlow installed from (source or binary):
- TensorFlow version (use command below):
- Python version:
- Bazel version (if compiling from source):
- GCC/Compiler version (if compiling from source):
- CUDA/cuDNN version:
- GPU model and memory:
You can collect some of this information using our environment capture
[script](https://github.com/tensorflow/tensorflow/tree/master/tools/tf_env_collect.sh)
You can also obtain the TensorFlow version with: 1. TF 1.0: `python -c "import
tensorflow as tf; print(tf.GIT_VERSION, tf.VERSION)"` 2. TF 2.0: `python -c
"import tensorflow as tf; print(tf.version.GIT_VERSION, tf.version.VERSION)"`
You can also obtain the TensorFlow version with:
1. TF 1.0: `python -c "import tensorflow as tf; print(tf.GIT_VERSION, tf.VERSION)"`
2. TF 2.0: `python -c "import tensorflow as tf; print(tf.version.GIT_VERSION, tf.version.VERSION)"`
**Describe the current behavior**
**Describe the expected behavior**
**Standalone code to reproduce the issue**
**Standalone code to reproduce the issue**
Provide a reproducible test case that is the bare minimum necessary to generate
the problem. If possible, please share a link to Colab/Jupyter/any notebook.