在多进程中使用一张图运行tensorflow

时间:2018-08-15 01:55:14

标签: python tensorflow multiprocessing python-multiprocessing ensemble-learning

我正在尝试训练具有5个集成网络的分类器。我决定用不同的批次来训练它们,所以我想创建多个过程来节省时间。

这是我的算法设计:

import multiprocessing as mp
import tensorflow as tf

# create() function returns 5 optimizer for 5 network, i.e. len(opt_list) = 5
opt_list = create()

def sub_process(sess, opt, feed_batch):
    sess.run(opt, feed_dict=feed_batch)

batch_list = []
for i in range(5):
    batch = generate_batch(batch_size=100)
    batch_list.append(batch)

for i in range(5):
    p = mp.Process(target=sub_process, args=(sess, opt_list[i], batch_list[i]))
    p.start()

for i in range(5):
    p.join()

首先,我构建图形并将每个网络部署在5个不同的设备上(我总共有5个GPU)。

然后,我从数据集中抽取样本(例如,如果要将100张图像馈送到一个网络,则将生成500个样本)

接下来,我使用python3包多处理程序创建5个进程。每个进程在给定参数输入的情况下运行sub_process函数。

但是,当我运行代码时,出现以下错误

2018-08-14 18:13:56.776853: E tensorflow/core/grappler/clusters/utils.cc:82] Failed to get device properties, error code: 3
2018-08-14 18:13:56.776940: E tensorflow/core/grappler/clusters/utils.cc:82] Failed to get device properties, error code: 3
2018-08-14 18:13:56.776978: E tensorflow/core/grappler/clusters/utils.cc:82] Failed to get device properties, error code: 3
2018-08-14 18:13:56.777004: E tensorflow/core/grappler/clusters/utils.cc:82] Failed to get device properties, error code: 3
2018-08-14 18:13:56.830762: E tensorflow/core/grappler/clusters/utils.cc:82] Failed to get device properties, error code: 3
2018-08-14 18:13:56.831239: E tensorflow/core/grappler/clusters/utils.cc:82] Failed to get device properties, error code: 3
2018-08-14 18:13:56.831262: E tensorflow/core/grappler/clusters/utils.cc:82] Failed to get device properties, error code: 3
2018-08-14 18:13:56.831285: E tensorflow/core/grappler/clusters/utils.cc:82] Failed to get device properties, error code: 3
2018-08-14 18:13:56.902612: E tensorflow/core/grappler/clusters/utils.cc:82] Failed to get device properties, error code: 3
2018-08-14 18:13:57.654653: E tensorflow/stream_executor/cuda/cuda_driver.cc:1227] failed to enqueue async memcpy from host to device: CUDA_ERROR_NOT_INITIALIZED; GPU dst: 0x1085d87f000; host src: 0x1083783f700; size: 4=0x4
2018-08-14 18:13:57.660200: E tensorflow/stream_executor/cuda/cuda_driver.cc:1227] failed to enqueue async memcpy from host to device: CUDA_ERROR_NOT_INITIALIZED; GPU dst: 0x1085d87f000; host src: 0x1083783f700; size: 4=0x4
2018-08-14 18:13:57.758658: E tensorflow/stream_executor/cuda/cuda_driver.cc:1227] failed to enqueue async memcpy from host to device: CUDA_ERROR_NOT_INITIALIZED; GPU dst: 0x1085d87f000; host src: 0x1083783f700; size: 4=0x4
2018-08-14 18:13:57.808281: E tensorflow/stream_executor/cuda/cuda_driver.cc:1227] failed to enqueue async memcpy from host to device: CUDA_ERROR_NOT_INITIALIZED; GPU dst: 0x1085d87f000; host src: 0x1083783f700; size: 4=0x4

谁能告诉我为什么会出现这样的错误?要获得我想要的代码,应该对我的代码进行哪些更改?

谢谢!

1 个答案:

答案 0 :(得分:0)

我建议您看一下tf.contrib.distribute,它有一个不错的API,可从多个GPU中获得良好的性能。