# Caffe2 predictor requires all input blobs (including the
        # real model inputs) are initialized in init_net
        for value_info in graph_def.input:
            if value_info.name in initialized:
                continue
            op_def = caffe2_pb2.OperatorDef()
            op_def.output.extend([value_info.name])
            op_def.type = 'GivenTensorFill'

            shape = list(d.dim_value for d in value_info.type.tensor_type.shape.dim)
            # TODO: Putting this in the init net will make it run faster, but it
            # causes some tests to fail...
            # shape = (1,)

            shape_arg = op_def.arg.add()
            shape_arg.name = 'shape'
            shape_arg.ints.extend(shape)

            values_arg = op_def.arg.add()
            values_arg.name = 'values'
            values_arg.floats.extend(np.ones(shape).flatten().tolist())

            init_net.op.extend([op_def])

Traceback (most recent call last):
  File "conversion.py", line 1, in <module>
    import onnx_caffe2.frontend as c2_onnx
  File "/home/chaitanya/.local/lib/python2.7/site-packages/onnx_caffe2/frontend.py", line 8, in <module>
    from onnx import onnx_pb2, checker
  File "/home/chaitanya/.local/lib/python2.7/site-packages/onnx/__init__.py", line 7, in <module>
    from . import checker, helper
  File "/home/chaitanya/.local/lib/python2.7/site-packages/onnx/checker.py", line 14, in <module>
    from onnx import defs
  File "/home/chaitanya/.local/lib/python2.7/site-packages/onnx/defs/__init__.py", line 6, in <module>
    import onnx.onnx_cpp2py_export as C
ImportError: /home/chaitanya/.local/lib/python2.7/site-packages/onnx/onnx_cpp2py_export.so: undefined symbol: _ZNK6google8protobuf7Message13SpaceUsedLongEv

---------------------------------------------------------------------------
ModuleNotFoundError                       Traceback (most recent call last)
~/projects/onnx/caffe2/build/caffe2/python/_import_c_extension.py in <module>()
     27     try:
---> 28         from caffe2.python.caffe2_pybind11_state_gpu import *  # noqa
     29         if num_cuda_devices():  # noqa

ModuleNotFoundError: No module named 'caffe2.python.caffe2_pybind11_state_gpu'

During handling of the above exception, another exception occurred:

ImportError                               Traceback (most recent call last)
~/projects/onnx/caffe2/build/caffe2/python/_import_c_extension.py in <module>()
     39         try:
---> 40             from caffe2.python.caffe2_pybind11_state import *  # noqa
     41         except ImportError as e:

ImportError: /home/arogozhn/projects/onnx/caffe2/build/caffe2/python/caffe2_pybind11_state.so: undefined symbol: _Py_ZeroStruct

During handling of the above exception, another exception occurred:

SystemExit                                Traceback (most recent call last)
<ipython-input-1-401d8c4e960a> in <module>()
----> 1 import onnx_caffe2.backend as backend

~/py36/lib/python3.6/site-packages/onnx_caffe2/backend.py in <module>()
     11 
     12 import caffe2
---> 13 from caffe2.python import core, workspace
     14 from caffe2.proto import caffe2_pb2
     15 import caffe2.python.utils

~/projects/onnx/caffe2/build/caffe2/python/core.py in <module>()
     28 
     29 from caffe2.proto import caffe2_pb2
---> 30 from caffe2.python import scope, utils, workspace
     31 from caffe2.python.control_ops_grad import \
     32     gen_do_gradient, gen_if_gradient, gen_while_gradient

~/projects/onnx/caffe2/build/caffe2/python/workspace.py in <module>()
     35 from caffe2.python import scope, utils
     36 
---> 37 import caffe2.python._import_c_extension as C
     38 
     39 logger = logging.getLogger(__name__)

~/projects/onnx/caffe2/build/caffe2/python/_import_c_extension.py in <module>()
     42             logging.critical(
     43                 'Cannot load caffe2.python. Error: {0}'.format(str(e)))
---> 44             sys.exit(1)
     45 
     46 # libcaffe2_python contains a global Workspace that we need to properly delete

import io
import os
import torch
from torch.autograd import Variable
import onnx
from onnx_caffe2.backend import Caffe2Backend
from onnx_caffe2.helper import save_caffe2_net
from torchvision.models import alexnet

model = alexnet()
test_input = torch.randn(1, 3, 224, 224)
f = io.BytesIO()
torch.onnx.export(model, Variable(test_input), f, verbose=True)
onnx_model = onnx.ModelProto.FromString(f.getvalue())

# now convert proto to caffe2
caffe2_dir = "~/local/caffe2"
if not os.path.exists(caffe2_dir):
    os.makedirs(caffe2_dir)
init_net, pred_net = Caffe2Backend.onnx_graph_to_caffe2_net(
    onnx_model, device="CPU")
init_net_file = os.path.join(caffe2_dir, "mobile_init_net.pb")
pred_net_file = os.path.join(caffe2_dir, "mobile_pred_net.pb")
save_caffe2_net(init_net, init_net_file, output_txt=False)
save_caffe2_net(pred_net, pred_net_file, output_txt=True)

op {
  input: "1"
  input: "2"
  output: "121"
  name: ""
  type: "Conv"
  arg {
    name: "dilations"
    ints: 1
    ints: 1
  }
  arg {
    name: "strides"
    ints: 1
    ints: 1
  }
  arg {
    name: "pads"
    ints: 1
    ints: 1
    ints: 1
    ints: 1
  }
  arg {
    name: "group"
    i: 1
  }
  arg {
    name: "kernels"
    ints: 3
    ints: 3
  }
}
op {
  input: "121"
  input: "3"
  output: "122"
  name: ""
  type: "Add"
  arg {
    name: "broadcast"
    i: 1
  }
  arg {
    name: "axis"
    i: 1
  }
}

Ubuntu 16.04.4 LTS, Python 3.6 Caffe2 CPU;
Ubuntu 16.04.4 LTS, Python 3.6 Caffe2 GPU CUDA 9.0 CuDNN7;
Caffe2 docker Ubuntu 16.04.2 LTS, Python 2.7 Caffe2 CPU;

[MC] Reading from public effective user settings. 
libc++abi.dylib: terminating with uncaught exception of type caffe2::EnforceNotMet: [enforce fail at conv_op_impl.h:37] filter.dim32(i + 2) == kernel_[i].  Error from operator:  
input: "9" input: "1" output: "11" name: "" type: "Conv" arg { name: "kernels" ints: 5 ints: 5 } arg { name: "strides" ints: 1 ints: 1 } arg { name: "pads" ints: 2 ints: 2 ints: 2 ints: 2 } arg { name: "dilations" ints: 1 ints: 1 } arg { name: "group" i: 1 }

device_option {
  device_type: 0
  cuda_gpu_id: 0
}

IIn [51]: model = onnx.load("/Users/ohara/data/models/super_resolution.onnx")

In [52]: prepared_backend = onnx_caffe2.backend.prepare(model)
---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-52-2fbcb732bd1d> in <module>()
----> 1 prepared_backend = onnx_caffe2.backend.prepare(model)

/Users/ohara/anaconda3/envs/python2/lib/python2.7/site-packages/onnx_caffe2/backend.pyc in prepare(cls, predict_graph, device, init_graph, **kwargs)
    309                 init_net = caffe2_pb2.NetDef()
    310 
--> 311             predict_net, _ = cls._onnx_graph_to_caffe2_net(predict_graph)
    312             predict_net.device_option.CopyFrom(get_device_option(device))
    313 

/Users/ohara/anaconda3/envs/python2/lib/python2.7/site-packages/onnx_caffe2/backend.pyc in _onnx_graph_to_caffe2_net(cls, graph_def)
    423 
    424         net_def = caffe2_pb2.NetDef()
--> 425         net_def.name = graph_def.name
    426 
    427         # environment from ONNX name to Caffe2 name

AttributeError: 'ModelProto' object has no attribute 'name'

christoph:~/caffe2-inference-test$ python run-caffe2.py MNIST.simple.caffe2 
WARNING:root:This caffe2 python run does not have GPU support. Will run in CPU only mode.
WARNING:root:Debug message: No module named caffe2_pybind11_state_gpu
Traceback (most recent call last):
  File "run-caffe2.py", line 51, in <module>
    sys.exit( main() )
  File "run-caffe2.py", line 43, in main
    predictor = caffe2.python.workspace.Predictor(init_net, predict_net)
RuntimeError: [enforce fail at operator.cc:52] blob != nullptr. op Scale: Encountered a non-existing input blob: 1 

Traceback (most recent call last):
  File "test_model_large_stepping.py", line 37, in test
    cf_rep = c2.prepare(_model)
  File "/Users/xxx/onnx-caffe2/onnx_caffe2/backend.py", line 559, in prepare
    for imp in model.opset_import:
AttributeError: 'ModelProto' object has no attribute 'opset_import'

from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals

import unittest
import numpy as np
import onnx
import onnx_caffe2.backend as c2
from onnx import helper
from onnx.onnx_pb2 import TensorProto

class TestLargeModel(unittest.TestCase):
  MODEL_PATH = "../../../onnx_models/"

  def test(self):
    _model = onnx.load(self.MODEL_PATH + "shufflenet/model.pb")
    cf_rep = c2.prepare(_model)

if __name__ == '__main__':
  unittest.main()

import onnx
import onnx_caffe2.backend

[libprotobuf FATAL google/protobuf/stubs/common.cc:61] This program requires version 3.4.0 of the Protocol Buffer runtime library, but the installed version is 2.6.1.  Please update your library.  If you compiled the program yourself, make sure that your headers are from the same version of Protocol Buffers as your link-time library.  (Version verification failed in "google/protobuf/any.pb.cc".)
terminate called after throwing an instance of 'google::protobuf::FatalException'
  what():  This program requires version 3.4.0 of the Protocol Buffer runtime library, but the installed version is 2.6.1.  Please update your library.  If you compiled the program yourself, make sure that your headers are from the same version of Protocol Buffers as your link-time library.  (Version verification failed in "google/protobuf/any.pb.cc".)
Aborted (core dumped)`

$ protoc --version
libprotoc 3.4.0