Question

在Ubuntu 16.04上运行，最新（1.1.0）张量流（通过pip3 install tensorflow-gpu安装），CUDA8 + CUDNN5。

代码看起来或多或少是这样的：

import tensorflow as tf
from tensorflow.contrib.learn import KMeansClustering

trainencflt = #pandas frame with ~30k rows and ~300 columns
def train_input_fn():
    return (tf.constant(trainencflt, shape = [trainencflt.shape[0], trainencflt.shape[1]]), None)

configuration = tf.contrib.learn.RunConfig(log_device_placement=True)
model = KMeansClustering(num_clusters=k,
                         initial_clusters=KMeansClustering.RANDOM_INIT,
                         relative_tolerance=1e-8,
                         config=configuration)
model.fit(input_fn = train_input_fn, steps = 100)

当它运行时，我看到：

2017-06-15 10:24:41.564890: I tensorflow/core/common_runtime/gpu/gpu_device.cc:887] Found device 0 with properties:
name: GeForce GTX 1080
major: 6 minor: 1 memoryClockRate (GHz) 1.7335
pciBusID 0000:81:00.0
Total memory: 7.92GiB
Free memory: 7.81GiB
2017-06-15 10:24:41.564934: I tensorflow/core/common_runtime/gpu/gpu_device.cc:908] DMA: 0
2017-06-15 10:24:41.564942: I tensorflow/core/common_runtime/gpu/gpu_device.cc:918] 0:   Y
2017-06-15 10:24:41.564956: I tensorflow/core/common_runtime/gpu/gpu_device.cc:977] Creating TensorFlow device (/gpu:0) -> (device: 0, name: GeForce GTX 1080, pci bus id: 0000:81:00.0)

分配内存：

+-----------------------------------------------------------------------------+
| Processes:                                                       GPU Memory |
|  GPU       PID  Type  Process name                               Usage      |
|=============================================================================|
|    1       548    C   python                                        7745MiB |
+-----------------------------------------------------------------------------+

但是后来没有任何操作在GPU上执行（它始终保持在0％，CPU利用率在所有内核上都飙升）：

+-----------------------------------------------------------------------------+
| NVIDIA-SMI 375.66                 Driver Version: 375.66                    |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|===============================+======================+======================|
|   1  GeForce GTX 1080    Off  | 0000:02:00.0     Off |                  N/A |
| 29%   43C    P8    13W / 180W |   7747MiB /  8114MiB |      0%      Default |
+-------------------------------+----------------------+----------------------+

没有看到任何展示位置日志（即使我将log_device_placement指定为True）。

我确实尝试了the simple GPU examples，他们工作得很好（至少放置日志看起来很好）。

我错过了什么吗？

Answer 1

通过代码库 - TF 1.1.0根本就没有GPU内核。

TF KMeansClustering不在GPU上运行

1 个答案: