Dear Miyamoto. It Seem out of memory problem. You can open file *.theanorc* and edit the *optimizer*. *optimizer = fast_run* or if it is not success you can set the *optimizer = None*
Thanks Regards Toto *Toto Haryanto* *Mahasiswa Program Doktor* *Fakultas Ilmu Komputer * *Universitas Indonesia * ========================== Office: Depertemen Ilmu Komputer IPB Jl. Meranti Wing 20 Level 5 Kampus Darmaga-Bogor (0251)8625584 <http://cs.ipb.ac.id/~bioinfo/> email : totoharyanto@[ipb.ac.id || apps.ipb.ac.id <totoharya...@ipb.ac.id>] http://totoharyanto.staff.ipb.ac.id http://cs.ipb.ac.id/~bioinfo/ ========================== On Fri, May 24, 2019 at 10:55 AM 宮本剛 <miyamoto.tsuyoshi1...@gmail.com> wrote: > Hi. > > I tried to execute a sample python program on the book > Deep-Learning-with-Keras > <https://github.com/PacktPublishing/Deep-Learning-with-Keras> > > But the program cause Memory Error detailed follows: > > MemoryError: > Apply node that caused the error: Elemwise{sgn}(Elemwise{add,no_inplace}.0) > Toposort index: 419 > Inputs types: [TensorType(float32, 4D)] > Inputs shapes: [(3, 400, 400, 64)] > Inputs strides: [(40960000, 1600, 4, 640000)] > Inputs values: ['not shown'] > Inputs type_num: [11] > Outputs clients: [[Elemwise{mul}(Elemwise{mul}.0, Elemwise{sgn}.0)]] > > Backtrace when the node is created(use Theano flag traceback.limit=N to make > it longer): > File "C:\ProgramData\Anaconda3\lib\site-packages\theano\gradient.py", line > 1326, in access_grad_cache > term = access_term_cache(node)[idx] > File "C:\ProgramData\Anaconda3\lib\site-packages\theano\gradient.py", line > 1021, in access_term_cache > output_grads = [access_grad_cache(var) for var in node.outputs] > File "C:\ProgramData\Anaconda3\lib\site-packages\theano\gradient.py", line > 1021, in <listcomp> > output_grads = [access_grad_cache(var) for var in node.outputs] > File "C:\ProgramData\Anaconda3\lib\site-packages\theano\gradient.py", line > 1326, in access_grad_cache > term = access_term_cache(node)[idx] > File "C:\ProgramData\Anaconda3\lib\site-packages\theano\gradient.py", line > 1021, in access_term_cache > output_grads = [access_grad_cache(var) for var in node.outputs] > File "C:\ProgramData\Anaconda3\lib\site-packages\theano\gradient.py", line > 1021, in <listcomp> > output_grads = [access_grad_cache(var) for var in node.outputs] > File "C:\ProgramData\Anaconda3\lib\site-packages\theano\gradient.py", line > 1326, in access_grad_cache > term = access_term_cache(node)[idx] > File "C:\ProgramData\Anaconda3\lib\site-packages\theano\gradient.py", line > 1162, in access_term_cache > new_output_grads) > > Debugprint of the apply node: > Elemwise{sgn} [id A] <TensorType(float32, 4D)> '' > |Elemwise{add,no_inplace} [id B] <TensorType(float32, 4D)> '' > |InplaceDimShuffle{0,2,3,1} [id C] <TensorType(float32, 4D)> '' > | |AbstractConv2d{convdim=2, border_mode='half', subsample=(1, 1), > filter_flip=True, imshp=(None, 3, None, None), kshp=(64, 3, 3, 3), > filter_dilation=(1, 1), num_groups=1, unshared=False} [id D] > <TensorType(float32, 4D)> '' > | |InplaceDimShuffle{0,3,1,2} [id E] <TensorType(float32, 4D)> '' > | | |Join [id F] <TensorType(float32, 4D)> '' > | | |TensorConstant{0} [id G] <TensorType(int8, scalar)> > | | |/variable [id H] <TensorType(float32, 4D)> > | | |/variable [id I] <TensorType(float32, 4D)> > | | |/placeholder [id J] <TensorType(float32, 4D)> > | |InplaceDimShuffle{3,2,0,1} [id K] <TensorType(float32, 4D)> '' > | |block1_conv1/kernel [id L] <TensorType(float32, 4D)> > |Reshape{4} [id M] <TensorType(float32, (True, True, True, False))> '' > |block1_conv1/bias [id N] <TensorType(float32, vector)> > |MakeVector{dtype='int64'} [id O] <TensorType(int64, vector)> '' > |Elemwise{Cast{int64}} [id P] <TensorType(int64, scalar)> '' > | |TensorConstant{1} [id Q] <TensorType(int8, scalar)> > |Elemwise{Cast{int64}} [id R] <TensorType(int64, scalar)> '' > | |TensorConstant{1} [id Q] <TensorType(int8, scalar)> > |Elemwise{Cast{int64}} [id S] <TensorType(int64, scalar)> '' > | |TensorConstant{1} [id Q] <TensorType(int8, scalar)> > |Subtensor{int64} [id T] <TensorType(int64, scalar)> '' > |Shape [id U] <TensorType(int64, vector)> '' > | |block1_conv1/bias [id N] <TensorType(float32, vector)> > |Constant{0} [id V] <int64> > > > I don't know what's wrong. > > > > -- > > --- > You received this message because you are subscribed to the Google Groups > "theano-users" group. > To unsubscribe from this group and stop receiving emails from it, send an > email to theano-users+unsubscr...@googlegroups.com. > To view this discussion on the web visit > https://groups.google.com/d/msgid/theano-users/31013f94-a40c-4c52-bf3b-d78390a33a61%40googlegroups.com > <https://groups.google.com/d/msgid/theano-users/31013f94-a40c-4c52-bf3b-d78390a33a61%40googlegroups.com?utm_medium=email&utm_source=footer> > . > For more options, visit https://groups.google.com/d/optout. > -- --- You received this message because you are subscribed to the Google Groups "theano-users" group. 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