Error：OOM when allocating tensor with shape[......]
問題描述： 訓練模型時，遇到： 原因： 內存不夠，OOM即ran out of memory 可以使用top命令動態監聽運行時間非常短的程序的內存使用情況：參考 啓用2個session，一個session運行top命令，另一個session運行指定的程序，top命令會輸出與這個命令相關的資源使用情況。 解決方法： 最直觀的方式就是減小batch_size或者hidden_layer中的單元數 減少
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相關文章
- 1. ResourceExhaustedError: OOM when allocating tensor with shape[10,256,400,528]
- 2. ''tensorflow.python.framework.errors_impl.ResourceExhaustedError: OOM when allocating tensor with sh
- 3. 【tf.keras】Resource exhausted: OOM when allocating tensor with shape [9216,4096] and type float on /j
- 4. OOM when allocating tensor with shape[300,14,14,256] and type float on /job:localhost/replica:0/tas
- 5. ResourceExhaustedError (see above for traceback): OOM when allocating tensor with shape[682112,156]
- 6. You must feed a value for placeholder tensor 'Placeholder_1' with dtype float and shape [?,10]
- 7. keras 報錯 ValueError: Tensor conversion requested dtype int32 for Tensor with dtype float32: 'Tensor(
- 8. DLA, programming with tensor cores
- 9. [顯存被佔滿，程序無法運行問題]ResourceExhaustedError (see above for traceback): OOM when allocating tensor
- 10. ValueError: Tensor Tensor("Placeholder:0", shape=(3, 3, 1, 32), dtype=float32)