samskalicky commented on a change in pull request #17623: Dynamic subgraph
compile support
URL: https://github.com/apache/incubator-mxnet/pull/17623#discussion_r384247773
##########
File path: example/extensions/lib_subgraph/test_subgraph.py
##########
@@ -88,3 +91,54 @@
out4 = sym_block(mx.nd.ones((3,2)),mx.nd.ones((3,2)))
print(out4)
+# Gluon Hybridize partitioning with shapes/types without inference
+print('-------------------------------')
+print('Testing Gluon Hybridize partitioning with shapes/types without
inference')
+inputs = [a,b]
+sym_block2 = nn.SymbolBlock(sym, inputs)
+sym_block2.initialize()
+sym_block2.optimize_for(mx.nd.ones((3,2)), mx.nd.ones((3,2)), backend='myProp')
+sym_block2.export('partitioned')
+
+
+###############################################
+# Test with subgraph directly consuming params
+###############################################
+# example model, ops to be partitioned have args
+d2 = mx.sym.exp(a)
Review comment:
Remember this is not a test, this an example python script showing different
ways of partitioning the model. It prints out the results of forward just to
show that the results are the same. The comparison to the regular symbol flow
is just giving us a baseline to compare again built-in MXNet computation flow.
The actual tests are in tests/python/unittest/test_extensions.py
----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
For queries about this service, please contact Infrastructure at:
[email protected]
With regards,
Apache Git Services
