wangwei created SINGA-315:
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Summary: Reduce memory footprint by Python generator for parameter
gradient
Key: SINGA-315
URL: https://issues.apache.org/jira/browse/SINGA-315
Project: Singa
Issue Type: New Feature
Reporter: wangwei
The parameter gradient tensors are stored in memory until BP is finished.
This is not necessary as we can update the parameter once its gradient is
ready. Then we free the gradient tensor.
In this way, we reduce the memory footprint by avoiding store all gradient
tensors.
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