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Returns whether TensorFlow can access a GPU.
Aliases:
tf.test.is_gpu_available(
cuda_only=False,
min_cuda_compute_capability=None
)
Args:
cuda_only: limit the search to CUDA GPUs.min_cuda_compute_capability: a (major,minor) pair that indicates the minimum CUDA compute capability required, or None if no requirement.
Note that the keyword arg name "cuda_only" is misleading (since routine will return true when a GPU device is available irrespective of whether TF was built with CUDA support or ROCm support. However no changes here because
++ Changing the name "cuda_only" to something more generic would break backward compatibility
++ Adding an equivalent "rocm_only" would require the implementation check the build type. This in turn would require doing the same for CUDA and thus potentially break backward compatibility
++ Adding a new "cuda_or_rocm_only" would not break backward compatibility, but would require most (if not all) callers to update the call to use "cuda_or_rocm_only" instead of "cuda_only"
Returns:
True if a GPU device of the requested kind is available.