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If I understand it correctly, when translating a dataset with neuralmonkey-run (using pretrained model), all the translations (or outputs) are held in the memory... (this loop here: https://github.com/ufal/neuralmonkey/blob/master/neuralmonkey/learning_utils.py#L323) ... and only after producing all the outputs, they are being written into the output (https://github.com/ufal/neuralmonkey/blob/master/neuralmonkey/learning_utils.py#L383)
When processing/translating large files, this might cause memory issues.
The text was updated successfully, but these errors were encountered:
Totally agree.
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If I understand it correctly, when translating a dataset with neuralmonkey-run (using pretrained model), all the translations (or outputs) are held in the memory...
(this loop here: https://github.com/ufal/neuralmonkey/blob/master/neuralmonkey/learning_utils.py#L323)
... and only after producing all the outputs, they are being written into the output
(https://github.com/ufal/neuralmonkey/blob/master/neuralmonkey/learning_utils.py#L383)
When processing/translating large files, this might cause memory issues.
The text was updated successfully, but these errors were encountered: