hi i am getting following error. is there some limit on protein length?
n_input: 985
opening seq.aln
cuda:0
batch_size: 10
sigma: 22.5
alpha: 0.5
seq.aln opened with object id 138143134556656 for worker 0
seq.aln opened with object id 138143134557008 for worker 1
OutOfMemoryError Traceback (most recent call last)
in <cell line: 10>()
9 test_aln = '/content/alignscape/data/Human_kinome/human_kinome_noPLK5.aln'
10 if np.genfromtxt('seq.aln').size > 0:
---> 11 align_scape.main(ali="seq.aln", batch_size=10,
12 outname="som", somside=somside, nepochs=nepochs,
13 scheduler="exp", alpha=alpha, sigma= sigma)
2 frames
/content/alignscape/quicksom/som.py in call(self, x, learning_rate_op)
317 expanded_x = x.expand(-1, self.grid_size, -1)
318 expanded_weights = self.centroids.unsqueeze(0).expand((batch_size, -1, -1))
--> 319 delta = expanded_x - expanded_weights
320 delta = torch.mul(learning_rate_multiplier.reshape(*learning_rate_multiplier.size(), 1).expand_as(delta), delta)
321
OutOfMemoryError: CUDA out of memory. Tried to allocate 24.74 GiB (GPU 0; 14.75 GiB total capacity; 5.45 GiB already allocated; 9.14 GiB free; 5.48 GiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split_size_mb to avoid fragmentation. See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF
hi i am getting following error. is there some limit on protein length?
n_input: 985
opening seq.aln
cuda:0
batch_size: 10
sigma: 22.5
alpha: 0.5
seq.aln opened with object id 138143134556656 for worker 0
seq.aln opened with object id 138143134557008 for worker 1
OutOfMemoryError Traceback (most recent call last)
in <cell line: 10>()
9 test_aln = '/content/alignscape/data/Human_kinome/human_kinome_noPLK5.aln'
10 if np.genfromtxt('seq.aln').size > 0:
---> 11 align_scape.main(ali="seq.aln", batch_size=10,
12 outname="som", somside=somside, nepochs=nepochs,
13 scheduler="exp", alpha=alpha, sigma= sigma)
2 frames
/content/alignscape/quicksom/som.py in call(self, x, learning_rate_op)
317 expanded_x = x.expand(-1, self.grid_size, -1)
318 expanded_weights = self.centroids.unsqueeze(0).expand((batch_size, -1, -1))
--> 319 delta = expanded_x - expanded_weights
320 delta = torch.mul(learning_rate_multiplier.reshape(*learning_rate_multiplier.size(), 1).expand_as(delta), delta)
321
OutOfMemoryError: CUDA out of memory. Tried to allocate 24.74 GiB (GPU 0; 14.75 GiB total capacity; 5.45 GiB already allocated; 9.14 GiB free; 5.48 GiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split_size_mb to avoid fragmentation. See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF