keras是否会自动使用gpu? [英] Does keras use gpu automatically?

问题描述

似乎它会自动使用gpu，但我不知道为什么.

It seems like it uses gpu automatically, but I do not know why.

首先，我声明如下

tf_config = tf.ConfigProto( allow_soft_placement=True )
tf_config.gpu_options.allow_growth = True
sess = tf.Session(config=tf_config) 
keras.backend.set_session(sess)

然后我定义了以下模型

with K.tf.device('/gpu:0'):
    some keras model

很明显，它将使用gpu，并且我检查了它是否按预期使用了第一个gpu(索引为0).

This is obvious that it will use the gpu and I checked it uses the first gpu(with index 0) as I expected.

但是，我删除了该行

with K.tf.device('/gpu:0'):

并重新缩进所有keras模型.我运行了代码，仍然看起来像是使用第一个gpu(索引为0).

and re-indented all the keras model. I ran the code, it still seems like using first gpu(with index 0).

在我的Ubuntu上，我使用nvidia-smi命令检查gpu的内存使用情况，然后在Windows上查看了进程管理器.

On my ubuntu I used nvidia-smi command to check the gpu memory usage, and I looked on the process manager on my windows.

它们两者都占用gpu内存及其用法.

Both of them take the gpu memory and its usages.

据我所知，如果我不将tensorflow保留到其模型中，则不会使用gpu.但是使用Keras时，它似乎自动使用了gpu ...是因为我运行了代码

As far as I remember, tensorflow does not use gpu if I do not spare them to its model. But with Keras it seems like it uses gpu automatically ... is it because I ran the code

tf_config = tf.ConfigProto( allow_soft_placement=True )
tf_config.gpu_options.allow_growth = True
sess = tf.Session(config=tf_config) 
keras.backend.set_session(sess)

还是我想念其他原因吗?

or is there some other reason I am missing?

推荐答案

根据文档如果存在TensorFlow，它将默认使用GPU:

According to the documentation TensorFlow will use GPU by default if it exist:

如果TensorFlow操作同时具有CPU和GPU实施，则在将操作分配给设备时， GPU设备将被赋予优先级.例如，matmul同时具有CPU和GPU内核. 在具有设备cpu:0和gpu:0的系统上，将选择gpu:0来运行

If a TensorFlow operation has both CPU and GPU implementations, the GPU devices will be given priority when the operation is assigned to a device. For example, matmul has both CPU and GPU kernels. On a system with devices cpu:0 and gpu:0, gpu:0 will be selected to run

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