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Solving the conflict with Keras BatchNormalization. #50

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Solving the conflict with Keras BatchNormalization. #50

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779e9e5
Update memory_saving_gradients.py
purpleyun Apr 26, 2020
1521761
Update memory_saving_gradients.py
purpleyun Apr 26, 2020
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2 changes: 2 additions & 0 deletions memory_saving_gradients.py
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Original file line number Diff line number Diff line change
Expand Up @@ -88,8 +88,10 @@ def gradients(ys, xs, grad_ys=None, checkpoints='collection', **kwargs):
fwd_ops = [op for op in fwd_ops if not '/assign' in op.name]
fwd_ops = [op for op in fwd_ops if not '/Assign' in op.name]
fwd_ops = [op for op in fwd_ops if not '/read' in op.name]
fwd_ops = [op for op in fwd_ops if not '/Read' in op.name]
ts_all = ge.filter_ts(fwd_ops, True) # get the tensors
ts_all = [t for t in ts_all if '/read' not in t.name]
ts_all = [t for t in ts_all if '/Read' not in t.name]
ts_all = set(ts_all) - set(xs) - set(ys)

# construct list of tensors to checkpoint during forward pass, if not
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