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README.md
[pip package](https://www.tensorflow.org/install/pip), to [enable GPU support](https://www.tensorflow.org/install/gpu), use a [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 ```
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tensorflow/c/eager/abstract_operation.h
// // Example: If one calls `op->SetDeviceName("/device:GPU")`, the value // returned by DeviceName should be "/device:GPU:*" until a particular GPU is // chosen for the operation by the device placement logic in the // executor. After that, the value returned by DeviceName will be a full // device name such as "/job:localhost/replica:0/task:0/device:GPU:1". virtual const string& DeviceName() const = 0;
C - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Wed Jul 14 16:20:41 GMT 2021 - 6.8K bytes - Viewed (0) -
tensorflow/c/eager/parallel_device/parallel_device.h
// For example if `device_name` is // "/job:localhost/replica:0/task:0/device:CUSTOM:0" // and `underlying_devices` is // {"/job:localhost/replica:0/task:0/device:GPU:0", // "/job:localhost/replica:0/task:0/device:GPU:1"} // Then executing an operation on CUSTOM:0 will execute it on GPU:0 and GPU:1. // // Implicit copies onto `device_name` are allowed, replicating the value once // per device in `underlying_devices`. Implicit copies off of the device throw
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ci/official/containers/linux_arm64/devel.usertools/aarch64_clang.bazelrc
# bazel test invocation as normal. test:nonpip_filters --test_tag_filters=-no_oss,-oss_serial,-gpu,-tpu,-benchmark-test,-v1only,-no_aarch64,-no_oss_py38,-no_oss_py39,-no_oss_py310 test:nonpip_filters --build_tag_filters=-no_oss,-oss_serial,-gpu,-tpu,-benchmark-test,-v1only,-no_aarch64,-no_oss_py38,-no_oss_py39,-no_oss_py310
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.github/bot_config.yml
cuda_comment: > From the template it looks like you are installing **TensorFlow** (TF) prebuilt binaries: * For TF-GPU - See point 1 * For TF-CPU - See point 2 ----------------------------------------------------------------------------------------------- **1. Installing **TensorFlow-GPU** (TF) prebuilt binaries** Make sure you are using compatible TF and CUDA versions.
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tensorflow/c/README.md
- Nightly builds: - [Linux CPU-only](https://storage.googleapis.com/tensorflow-nightly/github/tensorflow/lib_package/libtensorflow-cpu-linux-x86_64.tar.gz) - [Linux GPU](https://storage.googleapis.com/tensorflow-nightly/github/tensorflow/lib_package/libtensorflow-gpu-linux-x86_64.tar.gz)
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.bazelrc
test:unsupported_cpu_linux --config=release_base build:unsupported_gpu_linux --config=cuda build:unsupported_gpu_linux --config=unsupported_cpu_linux build:unsupported_gpu_linux --action_env=TF_CUDA_VERSION="11" build:unsupported_gpu_linux --action_env=TF_CUDNN_VERSION="8" build:unsupported_gpu_linux --repo_env=TF_CUDA_COMPUTE_CAPABILITIES="sm_35,sm_50,sm_60,sm_70,sm_75,compute_80" build:unsupported_gpu_linux --config=tensorrt
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.github/ISSUE_TEMPLATE/tensorflow_issue_template.yaml
attributes: label: GCC/compiler version description: If compiling from source - type: input id: Cuda attributes: label: CUDA/cuDNN version - type: input id: Gpu attributes: label: GPU model and memory description: If compiling from source - type: textarea id: what-happened attributes: label: Current behavior?
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ci/official/containers/linux_arm64/devel.usertools/aarch64.bazelrc
# bazel test invocation as normal. test:nonpip_filters --test_tag_filters=-no_oss,-oss_serial,-gpu,-tpu,-benchmark-test,-v1only,-no_aarch64,-no_oss_py38,-no_oss_py39,-no_oss_py310 test:nonpip_filters --build_tag_filters=-no_oss,-oss_serial,-gpu,-tpu,-benchmark-test,-v1only,-no_aarch64,-no_oss_py38,-no_oss_py39,-no_oss_py310
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ci/official/envs/linux_x86_cuda
source ci/official/envs/linux_x86 TFCI_BAZEL_COMMON_ARGS="--repo_env=TF_PYTHON_VERSION=$TFCI_PYTHON_VERSION --config release_gpu_linux" TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX=linux_cuda TFCI_BUILD_PIP_PACKAGE_ARGS="--repo_env=WHEEL_NAME=tensorflow" TFCI_DOCKER_ARGS="--gpus all" TFCI_LIB_SUFFIX="-gpu-linux-x86_64"
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