Cannot use GPU when output.shape[1] * nnz(a) > 2^31

[ahukui]

When I use the gcn layer, I always meets this problem.

InvalidArgumentError: 2 root error(s) found. (0) Invalid argument: Cannot use GPU when output.shape[1] * nnz(a) > 2^31 [[node graph_convolution_23/SparseTensorDenseMatMul/SparseTensorDenseMatMul (defined at /home/labadmin/anaconda2/lib/python2.7/site-packages/keras/backend/tensorflow_backend.py:1083) ]] [[loss_3/add_2/_677]] (1) Invalid argument: Cannot use GPU when output.shape[1] * nnz(a) > 2^31 [[node graph_convolution_23/SparseTensorDenseMatMul/SparseTensorDenseMatMul (defined at /home/labadmin/anaconda2/lib/python2.7/site-packages/keras/backend/tensorflow_backend.py:1083) ]] 0 successful operations. 0 derived errors ignored.

[zhouchunpong]

I meet this problem too ！

[cquzys]

hello, do you solve it? can you share your method? thanks

[ahukui]

No

[ahukui]

You can run your code on CPU.

------------------ 原始邮件 ------------------ 发件人: "Horace"<[email protected]>; 发送时间: 2019年12月14日(星期六) 中午11:06 收件人: "tkipf/keras-gcn"<[email protected]>; 抄送: "kui"<[email protected]>;"Author"<[email protected]>; 主题: Re: [tkipf/keras-gcn] Cannot use GPU when output.shape[1] * nnz(a) > 2^31 (#51)

hello, do you solve it? can you share your method? thanks

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[innekemayachita]

Is there any solution on this issue?

[icoric4]

@innekemayachita Have you found anything maybe?

[YingtongDou]

You can cast the sparse matrix to dense matrix and use tf.matmul

[b3326023]

Same problem here.

[b3326023]

You can cast the sparse matrix to dense matrix and use tf.matmul

But if we have a large matrix with most of zero, we would like to use sparse matrix, so shouldn't cast to dense matrix

[krobasky]

I had this problem on tensorflow 2.4.1, it went away when I upgraded to 2.5 + cuda lib v11; I don't know if the trouble was with the tensorflow version, cuda, or both.