InvalidArgumentError (see above for traceback): Assign requires shapes of both tensors to match. lhs shape = [12288] rhs shape = [49152]
解決辦法：清空下checkpoint緩存就可以
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InvalidArgumentError (see above for traceback): Assign requires shapes of both tensors to match. lhs shape= [2048,38] rhs shape= [2048,2]
卷積層后連接LSTM層的報錯（InvalidArgumentError (see above for traceback): Incompatible shapes: [128] vs. [384]）
顯存不夠----ResourceExhaustedError (see above for traceback): OOM when allocating tensor with shape[4096]
tensorflow ResourceExhaustedError (see above for traceback): OOM when allocating tensor with shape[256,256,15,15] and type float on 報錯（顯存不夠報錯）
錯誤：基於tensorflow識別mnist數據集出現ResourceExhaustedError (see above for traceback): OOM when allocating tensor with shape[10000,32,28,28] and type float on
InvalidArgumentError (see above for traceback): You must feed a value for placeholder tensor 'Y' with dtype float
InvalidArgumentError: ConcatOp : Dimensions of inputs should match: shape[0] = [1,136,240,64] vs. shape[1] = [1,135,240,64]
【error】OutOfRangeError (see above for traceback): RandomShuffleQueue
LHS和RHS理解
Lhs和Rhs的含義