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use tf.cond instead of tf.control_flow_ops.cond #1460

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merged 1 commit into from
Nov 9, 2023
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use tf.cond instead of tf.control_flow_ops.cond #1460

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5 changes: 2 additions & 3 deletions returnn/tf/util/basic.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3697,7 +3697,7 @@ def debug_register_better_repr():

def cond(pred, true_fn, false_fn, name=None):
"""
This is a wrapper around tf.control_flow_ops.cond().
This is a wrapper around tf.cond().
This will be a branched execution, i.e. either fn1() or fn2() will be executed,
or at least the resulting graph will be evaluated.
If pred can is constant at the call, only the corresponding fn will be called.
Expand Down Expand Up @@ -3727,9 +3727,8 @@ def cond(pred, true_fn, false_fn, name=None):
return true_fn()
else:
return false_fn()
from tensorflow.python.ops import control_flow_ops

return control_flow_ops.cond(pred, true_fn, false_fn, name=name)
return tf.cond(pred, true_fn, false_fn, name=name)


def single_strided_slice(x, axis, begin=None, end=None, step=None):
Expand Down
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