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Fix wrong assumption about the order of weights in a keras Model #178
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Previously a wrong assumption was made about the ordering of weight values required for the input argument to `keras.Model.set_weights()` and `tf.keras.Model.set_weights()`. It turns out that the correct ordering is obtained by - iterating over Model.layers, and - in an inner loop, iterate over the weights of the indivisual Layers Previously the ordering was iterating over Model.weights, which can differ from the above-mentioned ordering in some cases, e.g., in a functional model with BatchNormalization Layers as covered by the unit tests added in this PR. BUG Fixes: tensorflow/tfjs#511
caisq
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pyu10055,
bileschi,
davidsoergel,
dsmilkov,
ericdnielsen and
nsthorat
nsthorat
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Jul 20, 2018
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Reviewed 2 of 2 files at r1.
Reviewable status: 0 of 1 approvals obtained (waiting on @nsthorat, @davidsoergel, @ericdnielsen, @dsmilkov, @pyu10055, and @bileschi)
dsmilkov
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Jul 20, 2018
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Reviewed 2 of 2 files at r1.
Reviewable status:complete! 1 of 1 approvals obtained (waiting on @davidsoergel, @ericdnielsen, @dsmilkov, @pyu10055, and @bileschi)
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Previously a wrong assumption was made about the ordering of
weight values required for the input argument to
keras.Model.set_weights()andtf.keras.Model.set_weights().It turns out that the correct ordering is obtained by
Previously the ordering was iterating over Model.weights, which
can differ from the above-mentioned ordering in some cases, e.g.,
in a functional model with BatchNormalization Layers as covered
by the unit tests added in this PR.
BUG
Fixes: tensorflow/tfjs#511
This change is