[GitHub] [incubator-tvm] trevor-m commented on issue #5134: [RELAY] Add MergeCompilerRegions pass

[GitBox <gi...@apache.org>]

trevor-m commented on issue #5134: [RELAY] Add MergeCompilerRegions pass
URL: https://github.com/apache/incubator-tvm/pull/5134#issuecomment-604752323
 
 
   Hello, I am trying to use this (in combination with ) but I am getting a segfault every time I call `MergeCompilerRegions`. Here is a small repro script. I expect the entire model to be partitioned into a single subgraph.
   
   ```
   from tvm import relay
   import mxnet as mx
   from mxnet.gluon.model_zoo.vision import get_model
   from tvm.relay import op as reg
   
   def _register_external_op_helper(op_name, supported=True):
       @reg.register(op_name, "target.test")
       def _func_wrapper(attrs, args):
           return supported
       return _func_wrapper
   
   _register_external_op_helper("nn.conv2d")
   _register_external_op_helper("nn.dense")
   _register_external_op_helper("nn.relu")
   _register_external_op_helper("add")
   _register_external_op_helper("multiply")
   _register_external_op_helper("nn.bias_add")
   _register_external_op_helper("nn.batch_flatten")
   _register_external_op_helper("nn.max_pool2d")
   _register_external_op_helper("nn.dropout")
   _register_external_op_helper("nn.batch_norm")
   _register_external_op_helper("nn.global_avg_pool2d")
   
   def test_resnet():
       block = get_model('resnet18_v1', pretrained=True)
       mod, params = relay.frontend.from_mxnet(block, shape={'data': (1, 3, 224, 224)}, dtype='float32')
       mod = relay.transform.AnnotateTarget("test")(mod)
       mod = relay.transform.MergeCompilerRegions()(mod)
       mod = relay.transform.PartitionGraph()(mod)
       print(mod)
   
   test_resnet()
   ```

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