Open khatchad opened 6 months ago
Add this test works:
https://github.com/ponder-lab/ML/commit/2db36e27afd9399c70a788a6800b675c19505379
I believe the problem is that the data sources are hard-coded:
But, it could also have something to do with the way other APIs are being constructed. For example, the points-to set for tf.ones()
is empty.
Looking at the summary of tf.reshape()
, I see that there's a data copy:
That may mean if the data source has something wrong with it, any copied data would also have the problem. Thus, the problem may not be with the tf.reshape()
operation itself but rather with how data sources other than MNIST are constructed.
That being said, copy_data()
in the above summary doesn't use its argument.
Thus, my best guess is that the problem involves a combination of the (new) XML summaries and the hard-coded initialization of the dataflow.
Consider the following code:
t2
should be a (reshaped) tensor, and the argument tof()
should also be tracked as a tensor. Instead, I'm seeing this tensor analysis result:In the IR,
v245
refers to the return value oftf.ones()
. That's the only tensor in this file.Regression
tf.reshape()
, but it callscopy_data()
instead ofread_data()
.tf.reshape()
in the code, stemming from theMethodReference
fieldcom.ibm.wala.cast.python.ml.client.PythonTensorAnalysisEngine.reshape
.