neuralib.util.gpu
Get basic GPU info table and verbose
cuda driver (Windows/Linux)
metal backend support (MacOS)
from neuralib.util.gpu import print_gpu_table
print_gpu_table()
- neuralib.util.gpu.print_gpu_table(backend, *, check_smi=False)[source]
Print GPU info table and check the compatibility with backend package
- Parameters:
backend (Literal['tensorflow', 'torch']) – {‘torch’, ‘tensorflow’}
check_smi (bool) – check if
nvidia-smiis runnable
- Returns:
- Return type:
None
- neuralib.util.gpu.gpu_available(backend, *, check_smi=False)[source]
- Parameters:
backend (Literal['tensorflow', 'torch']) – {‘torch’, ‘tensorflow’}
check_smi (bool) – check if
nvidia-smiis runnable
- Returns:
- Return type:
bool
- neuralib.util.gpu.check_mps_available(backend)[source]
Check if metal is available
- Parameters:
backend (Literal['tensorflow', 'torch']) – {‘torch’, ‘tensorflow’}
- Returns:
bool
- Return type:
bool
- neuralib.util.gpu.check_nvidia_cuda_available(backend, check_smi=False)[source]
Checks if the GPU driver reacts and otherwise raises a custom error. Useful to check before long GPU-dependent processes.
- Parameters:
backend (Literal['tensorflow', 'torch']) – {‘torch’, ‘tensorflow’}
check_smi (bool) – check if
nvidia-smiis runnable
- Return type:
bool