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import tensorflow as tf | |
use_gpu = tf.test.is_gpu_available( | |
cuda_only=True, | |
min_cuda_compute_capability=None | |
) | |
cpu_device_id = 0 | |
gpu_device_id = 0 | |
def get_device_name(): | |
""" | |
Get the current tensorflow device name we are using. | |
""" | |
global use_gpu | |
global cpu_device_id | |
global gpu_device_id | |
return '/device:gpu:' + str(gpu_device_id) if use_gpu else '/device:cpu:' + str(cpu_device_id) | |
def set_use_gpu(v: bool): | |
""" | |
Set whether to use CUDA or not. | |
""" | |
global use_gpu | |
use_gpu = v | |
def get_use_gpu(): | |
""" | |
Get whether we are using CUDA or not. | |
""" | |
global use_gpu | |
return use_gpu | |
def set_cpu_device_id(did: int): | |
""" | |
Set the cpu device id we are using. | |
""" | |
global cpu_device_id | |
cpu_device_id = did | |
def get_cpu_device_id(): | |
""" | |
Get the cpu device id we are using. | |
""" | |
global cpu_device_id | |
return cpu_device_id | |
def set_gpu_device_id(did: int): | |
""" | |
Set the gpu device id we are using. | |
""" | |
global gpu_device_id | |
gpu_device_id = did | |
def get_gpu_device_id(): | |
""" | |
Get the gpu device id we are using. | |
""" | |
global gpu_device_id | |
return gpu_device_id | |