---
name: Performance Issue
about: Use this template for reporting a performance issue
labels: 'type:performance'

---

<em>Please make sure that this is an issue related to performance of TensorFlow.
As per our
[GitHub Policy](https://github.com/tensorflow/tensorflow/blob/master/ISSUES.md),
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:

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)"`

**Describe the current behavior**

**Describe the expected behavior**

**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.

**Other info / logs** Include any logs or source code that would be helpful to
diagnose the problem. If including tracebacks, please include the full
traceback. Large logs and files should be attached.
