tensorflow.python.framework.errors_impl.ResourceExhaustedError: OOM when allocating tensor with shape[1,1424,2128,64]

tensorflow.python.framework.errors_impl.ResourceExhaustedError: OOM when allocating tensor with shape[1,1424,2128,64]

1、开始以为是 是显卡显存不足，没有想到是gpu问题

ref: https://www.cnblogs.com/heiao10duan/p/9083303.html

Dense(1024, activation='relu'), #将batch_size从4096改为1024因为我的显存不够

2、开始以为是没有选中独立显卡

# import os #key: https://blog.csdn.net/littlehaes/article/details/82317220

# os.environ["CUDA_VISIBLE_DEVICES"] = "2" #ref: https://www.cnblogs.com/ying-chease/p/9473938.html

#ref: https://www.cnblogs.com/darkknightzh/archive/2004/01/13/8576825.html

# ref:http://www.voidcn.com/article/p-xhpiftyw-bte.html

# ref:https://blog.csdn.net/weixin_43301333/article/details/108854504

# os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' # ref:https://blog.csdn.net/zqx951102/article/details/88897117

# ref:https://www.imooc.com/article/details/id/289425

3、 后来通过list_local_devices发现是没有装TensorFlow-gpu， install TensorFlow-gpu

# from tensorflow.python.client import device_lib

# print(device_lib.list_local_devices())

# https://blog.csdn.net/littlehaes/article/details/82317220

但是注意，安装命令应该使用：conda install -c anaconda tensorflow-gpu

而不是pip3 uninstall tensorflow-gpu

测试是否安装成功

方法一：

import tensorflow as tf

import tensorflow.compat.v1 as tfs

sess = tfs.Session(config=tfs.ConfigProto(log_device_placement=True))

输出中看到：

2020-12-10 08:38:41.553101: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1241] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 3001 MB memory) -> physical GPU (device: 0, name: Quadro P1000, pci bus id: 0000:01:00.0, compute capability: 6.1)

Device mapping:

方法二：

from tensorflow.python.client import device_lib

print(device_lib.list_local_devices())

输出中看到：

ncarnation: 5727256362115513404

, name: "/device:GPU:0"

device_type: "GPU"

memory_limit: 3147143577

locality {

bus_id: 1

links {

}

}

4、安装成功后，代码运行报错

from tensorflow.python._pywrap_tensorflow_internal import *

ImportError: DLL load failed: 找不到指定的模块。

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