Closed njzjz closed 2 days ago
The recent changes focus on modifying the reuse
parameter in TensorFlow's tf.variable_scope
function calls throughout multiple files in the deepmd
module. Specifically, the parameter is set from a variable to tf.AUTO_REUSE
for consistency and to potentially avoid errors related to variable reuse.
Files Modified | Change Summary |
---|---|
deepmd/tf/descriptor/se_a_mask.py |
Changed reuse parameter in tf.variable_scope to tf.AUTO_REUSE . |
deepmd/tf/fit/dos.py |
Changed reuse parameter in tf.variable_scope to tf.AUTO_REUSE . |
deepmd/tf/fit/ener.py |
Changed reuse parameter in tf.variable_scope from a variable to tf.AUTO_REUSE . |
[Not applicable: Changes involve simple substitutions in parameter values for existing function calls and do not modify control flow or functionalities substantially.]
Objective | Addressed | Explanation |
---|---|---|
Fix error when loading a model with the se_a_mask descriptor (#3928) |
✅ |
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All modified and coverable lines are covered by tests :white_check_mark:
Project coverage is 82.87%. Comparing base (
20aeaf8
) to head (70d4d4e
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It looks something goes wrong in the UT...
Fix #3928. Prevent
fitting_attr
from becomingfitting_attr_1
.Summary by CodeRabbit
tf.AUTO_REUSE
to streamline code and reduce the likelihood of variable reuse conflicts.