tf.test.is_gpu_available
| View source on GitHub |
Returns whether TensorFlow can access a GPU. (deprecated)
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. |
© 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.4/api_docs/python/tf/test/is_gpu_available
