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RELEASE.md
* Add `UnifiedGRU` as the new GRU implementation for tf2.0. Change the default recurrent activation function for GRU from `hard_sigmoid` to `sigmoid`, and `reset_after` to True in 2.0. Historically recurrent activation is `hard_sigmoid` since it is fast than 'sigmoid'. With new unified backend between CPU and GPU mode, since the CuDNN kernel is using sigmoid, we change
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.bazelrc
build:cuda_clang --config=tensorrt build:cuda_clang --action_env=TF_CUDA_CLANG="1" build:cuda_clang --@local_config_cuda//:cuda_compiler=clang # Select supported compute capabilities (supported graphics cards). # This is the same as the official TensorFlow builds. # See https://developer.nvidia.com/cuda-gpus#compute # `compute_XY` enables PTX embedding in addition to SASS. PTX
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README.md
[Docker container](https://www.tensorflow.org/install/docker), and [build from source](https://www.tensorflow.org/install/source). To install the current release, which includes support for [CUDA-enabled GPU cards](https://www.tensorflow.org/install/gpu) *(Ubuntu and Windows)*: ``` $ pip install tensorflow ``` Other devices (DirectX and MacOS-metal) are supported using
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