我已经在我的ubuntu 16.04中安装了tensorflow,使用的是ubuntu内置的apt cuda安装。
现在我的问题是,我如何测试tensorflow是否真的使用gpu?我有一个gtx 960m gpu。当我导入tensorflow时,这是输出
I tensorflow/stream_executor/dso_loader.cc:105] successfully opened CUDA library libcublas.so locally
I tensorflow/stream_executor/dso_loader.cc:105] successfully opened CUDA library libcudnn.so locally
I tensorflow/stream_executor/dso_loader.cc:105] successfully opened CUDA library libcufft.so locally
I tensorflow/stream_executor/dso_loader.cc:105] successfully opened CUDA library libcuda.so.1 locally
I tensorflow/stream_executor/dso_loader.cc:105] successfully opened CUDA library libcurand.so locally
这个输出是否足够检查tensorflow是否使用gpu ?
下面的代码段应该给出tensorflow可用的所有设备。
from tensorflow.python.client import device_lib
print(device_lib.list_local_devices())
样例输出
(名字:“/ cpu: 0”
device_type:“CPU”
memory_limit: 268435456
位置{
}
化身:4402277519343584096,
名称:“/ gpu: 0”
device_type:“GPU”
memory_limit: 6772842168
位置{
bus_id: 1
}
化身:7471795903849088328
physical_device_desc: "设备:0,名称:GeForce GTX 1070, pci总线id: 0000:05:00.0"
]
这将证实张量流使用GPU同时训练也?
Code
sess = tf.Session(config=tf.ConfigProto(log_device_placement=True))
输出
I tensorflow/core/common_runtime/gpu/gpu_device.cc:885] Found device 0 with properties:
name: GeForce GT 730
major: 3 minor: 5 memoryClockRate (GHz) 0.9015
pciBusID 0000:01:00.0
Total memory: 1.98GiB
Free memory: 1.72GiB
I tensorflow/core/common_runtime/gpu/gpu_device.cc:906] DMA: 0
I tensorflow/core/common_runtime/gpu/gpu_device.cc:916] 0: Y
I tensorflow/core/common_runtime/gpu/gpu_device.cc:975] Creating TensorFlow device (/gpu:0) -> (device: 0, name: GeForce GT 730, pci bus id: 0000:01:00.0)
Device mapping:
/job:localhost/replica:0/task:0/gpu:0 -> device: 0, name: GeForce GT 730, pci bus id: 0000:01:00.0
I tensorflow/core/common_runtime/direct_session.cc:255] Device mapping:
/job:localhost/replica:0/task:0/gpu:0 -> device: 0, name: GeForce GT 730, pci bus id: 0000:01:00.0