OOM when allocating tensor of shape [] and type float [[node conv2d_224/kernel/Initializer/random_uniform/min (defined at ./intances/utils.py:19) ]]

【OOM when allocating tensor of shape [] and type float [[node conv2d_224/kernel/Initializer/random_uniform/min (defined at ./intances/utils.py:19) ]]】的更多相关文章

OOM when allocating tensor of shape [] and type float [[node conv2d_224/kernel/Initializer/random_uniform/min (defined at ./intances/utils.py:19) ]]

当你们在用模型加载,tensorflow-gpu预测的时候,有没有出现这样的错误?? 经过网上的资料查阅,更多的解释是GPU的显存不足造成的,于是乎,我查看了一下GPU显存:nvidia-smi 不看不知道,一看确实是那么回事:tensorflow-gpu执行默认将GPU显存占满,官网也做了解释说明:https://www.tensorflow.org/guide/using_gpu 刚开始没有看到官网的解释,思路是当程序执行完成之后,能不能自动的执行释放显存的程序,网上这方面的代码不多,后来又…

【tf.keras】Resource exhausted: OOM when allocating tensor with shape [9216,4096] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc

运行以下类似代码: while True: inputs, outputs = get_AlexNet() model = tf.keras.Model(inputs=inputs, outputs=outputs) model.summary() adam_opt = tf.keras.optimizers.Adam(learning_rate) # The compile step specifies the training configuration. model.compile(opt…

Resource exhausted: OOM when allocating tensor with shape[3,3,384,384] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0。。。。。

报错信息: OP_REQUIRES failed at assign_op.h:111 : Resource exhausted: OOM when allocating tensor with shape[3,3,384,384] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc 大概意思是资源耗尽,无法在分配tensor了. 因为我之前有跑其他程序,然后使用ctrl+z中…

tensorflow报错 tensorflow Resource exhausted: OOM when allocating tensor with shape

在使用tensorflow的object detection时,出现以下报错 tensorflow Resource exhausted: OOM when allocating tensor with shape 可能的解决方法: 减小训练的batch大小…

显存不够----ResourceExhaustedError (see above for traceback): OOM when allocating tensor with shape[4096]

ResourceExhaustedError (see above for traceback): OOM when allocating tensor with shape[4096] 类似问题 https://github.com/CharlesShang/TFFRCNN/issues/68 参考: http://blog.csdn.net/qing101hua/article/details/77153222 方案: take a look at the memory usage of y…