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Last additions:
May, 25th 2007:
April, 26th 2007:
Apr, 10th. 2007:
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Details of sci-libs/tensorflow:
Description: Computation framework using data flow graphs for scalable machine learning
Homepage: https://www.tensorflow.org/
available versions:
| releases | alpha | amd64 | arm | hppa | ia64 | mips | ppc | ppc64 | ppc macos | s390 | sh | sparc | x86 | USE-Flags | dependencies | ebuild warnings |
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| tensorflow-2.5.0-r1 |
- | ~ | - | - | - | - | - | - | - | - | - | - | - | cuda
mpi
+python
xla
| show | TensorFlow 2.0 is a major release that contains some incompatibilities
with TensorFlow 1.x. For more information about migrating to TF2.0 see:
https://www.tensorflow.org/guide/migrate
TensorFlow is being built with Nvidia CUDA support. Your default compiler
version is not supported by the currently installed CUDA. TensorFlow will
instead be compiled using: ${GCC_HOST_COMPILER_PATH}.
If the build fails with linker errors try rebuilding the relevant
dependencies using the same compiler version.
WARNING: TensorFlow is being built with its default CUDA compute capabilities: 3.5 and 7.0.
These may not be optimal for your GPU.
To configure TensorFlow with the CUDA compute capability that is optimal for your GPU,
set TF_CUDA_COMPUTE_CAPABILITIES in your make.conf, and re-emerge tensorflow.
For example, to use CUDA capability 7.5 & 3.5, add: TF_CUDA_COMPUTE_CAPABILITIES=7.5,3.5
You can look up your GPU's CUDA compute capability at https://developer.nvidia.com/cuda-gpus
or by running /opt/cuda/extras/demo_suite/deviceQuery | grep 'CUDA Capability'
| | tensorflow-2.5.0 |
- | ~ | - | - | - | - | - | - | - | - | - | - | - | cuda
mpi
+python
xla
| show | TensorFlow 2.0 is a major release that contains some incompatibilities
with TensorFlow 1.x. For more information about migrating to TF2.0 see:
https://www.tensorflow.org/guide/migrate
TensorFlow is being built with Nvidia CUDA support. Your default compiler
version is not supported by the currently installed CUDA. TensorFlow will
instead be compiled using: ${GCC_HOST_COMPILER_PATH}.
If the build fails with linker errors try rebuilding the relevant
dependencies using the same compiler version.
WARNING: TensorFlow is being built with its default CUDA compute capabilities: 3.5 and 7.0.
These may not be optimal for your GPU.
To configure TensorFlow with the CUDA compute capability that is optimal for your GPU,
set TF_CUDA_COMPUTE_CAPABILITIES in your make.conf, and re-emerge tensorflow.
For example, to use CUDA capability 7.5 & 3.5, add: TF_CUDA_COMPUTE_CAPABILITIES=7.5,3.5
You can look up your GPU's CUDA compute capability at https://developer.nvidia.com/cuda-gpus
or by running /opt/cuda/extras/demo_suite/deviceQuery | grep 'CUDA Capability'
| | tensorflow-2.4.0 |
- | ~ | - | - | - | - | - | - | - | - | - | - | - | cuda
mpi
+python
xla
| show | TensorFlow 2.0 is a major release that contains some incompatibilities
with TensorFlow 1.x. For more information about migrating to TF2.0 see:
https://www.tensorflow.org/guide/migrate
TensorFlow is being built with Nvidia CUDA support. Your default compiler
version is not supported by the currently installed CUDA. TensorFlow will
instead be compiled using: ${GCC_HOST_COMPILER_PATH}.
If the build fails with linker errors try rebuilding the relevant
dependencies using the same compiler version.
WARNING: Tensorflow is being built with its default CUDA compute capabilities: 3.5 and 7.0.
These may not be optimal for your GPU.
To configure Tensorflow with the CUDA compute capability that is optimal for your GPU,
set TF_CUDA_COMPUTE_CAPABILITIES in your make.conf, and re-emerge tensorflow.
For example, to use CUDA capability 7.5 & 3.5, add: TF_CUDA_COMPUTE_CAPABILITIES=7.5,3.5
You can look up your GPU's CUDA compute capability at https://developer.nvidia.com/cuda-gpus
or by running /opt/cuda/extras/demo_suite/deviceQuery | grep 'CUDA Capability'
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Legend: + stable~ testing- not availablesome ebuild warning depend on specific use-flags or architectures, all ebuild-warnings are shown.
Tutorials:
no tutorial found
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