# @package onnx # Module caffe2.python.onnx.backend_rep from caffe2.python import core from caffe2.proto import caffe2_pb2 from onnx.backend.base import BackendRep, namedtupledict class Caffe2Rep(BackendRep): def __init__(self, init_net, predict_net, workspace, uninitialized): super(Caffe2Rep, self).__init__() self.init_net = init_net self.predict_net = predict_net self.workspace = workspace # The list of uninitialized external_inputs in workspace, we need this to # pair the name with given sequence inputs. self.uninitialized = uninitialized self.nets_created = False self.ran_init_net = False @property def _name_scope(self): if self.predict_net.device_option.device_type == caffe2_pb2.CUDA: return 'gpu_{}'.format(self.predict_net.device_option.device_id) return '' def run(self, inputs, **kwargs): super(Caffe2Rep, self).run(inputs, **kwargs) with core.DeviceScope(self.predict_net.device_option): if isinstance(inputs, dict): with core.NameScope(self._name_scope): for key, value in inputs.items(): self.workspace.FeedBlob(key, value) elif isinstance(inputs, list) or isinstance(inputs, tuple): if len(self.uninitialized) != len(inputs): raise RuntimeError('Expected {} values for uninitialized ' 'graph inputs ({}), but got {}.'.format( len(self.uninitialized), ', '.join(self.uninitialized), len(inputs))) for i, value in enumerate(inputs): # namescope already baked into protobuf self.workspace.FeedBlob(self.uninitialized[i], value) else: # single input self.workspace.FeedBlob(self.uninitialized[0], inputs) if not self.nets_created: self.workspace.CreateNet(self.init_net) self.workspace.CreateNet(self.predict_net) self.nets_created = True if not self.ran_init_net: self.workspace.RunNet(self.init_net.name) self.ran_init_net = True self.workspace.RunNet(self.predict_net.name) output_values = [] for name in self.predict_net.external_output: try: output_values.append(self.workspace.FetchBlob(name)) except Exception: output_values.append(self.workspace.FetchInt8Blob(name)) return namedtupledict('Outputs', self.predict_net.external_output)(*output_values)