Shashankwer opened a new issue #707:
URL: https://github.com/apache/singa/issues/707
Hi,
The issue might be known, however while creating a Neural network layer
stack with unmatched layer can cause the current python session to end
abruptly, without generating any stack trace. while calculating model.loss(e.g.
autograd.mse_loss(y,t) )
for example of a simple feed forward neural network:
class MLP():
def __init__(self):
self.linear1 = autograd.Linear(3,4)
self.linear2 = autograd.Linear(4,3)
def forward(self,x):
y = self.linear1(x)
return self.linear2(x)
if the output does not have a dimension of 3, the current session will
terminate without generating any error.
A stack trace is generated with below warning.
WARNING: Logging before InitGoogleLogging() is written to STDERR
F0520 17:37:19.265754 288538048 tensor.cc:431] Check failed: shape_.at(m -
i) == 1 (3 vs. 1) i= 0
*** Check failure stack trace: ***
This causes to rerun the entire program/notebook again. The same issue is
not seen in autograd.backward which generates an assertion error.
Thanks and Regards,
Shashank
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