ResourceExhaustedError: OOM when allocating tensor with shape[10,256,400,528]

时间 2020-01-25

标签 resourceexhaustederror oom allocating tensor shape 繁體版

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使用keras库进行模型训练时，出现如下错误： ResourceExhaustedError (see above for traceback): OOM when allocating tensor with shape[10,256,400,528] 解决方法以下： [10,256,400,528]的第一个参数表示batch_size的大小，第二个参数表示某层卷积核的个数，第三个参数表示图像的

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1. ''tensorflow.python.framework.errors_impl.ResourceExhaustedError: OOM when allocating tensor with sh
2. ResourceExhaustedError (see above for traceback): OOM when allocating tensor with shape[682112,156]
3. Error：OOM when allocating tensor with shape[......]
4. 【tf.keras】Resource exhausted: OOM when allocating tensor with shape [9216,4096] and type float on /j
5. OOM when allocating tensor with shape[300,14,14,256] and type float on /job:localhost/replica:0/tas
6. [显存被占满，程序无法运行问题]ResourceExhaustedError (see above for traceback): OOM when allocating tensor
7. DLA, programming with tensor cores
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1. ''tensorflow.python.framework.errors_impl.ResourceExhaustedError: OOM when allocating tensor with sh
2. ResourceExhaustedError (see above for traceback): OOM when allocating tensor with shape[682112,156]
3. Error：OOM when allocating tensor with shape[......]
4. 【tf.keras】Resource exhausted: OOM when allocating tensor with shape [9216,4096] and type float on /j
5. OOM when allocating tensor with shape[300,14,14,256] and type float on /job:localhost/replica:0/tas
6. [显存被占满，程序无法运行问题]ResourceExhaustedError (see above for traceback): OOM when allocating tensor
7. DLA, programming with tensor cores
8. keras 报错 ValueError: Tensor conversion requested dtype int32 for Tensor with dtype float32: 'Tensor(
9. GAC write failed when upgrade with InstallShield
10. tensorflow models api:ValueError: Tensor conversion requested dtype string for Tensor with dtype flo

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