mirror of
https://github.com/zebrajr/pytorch.git
synced 2025-12-06 12:20:52 +01:00
3eb5940cf5
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/12022 codemod -d . --extensions h,cc,cpp,cu,py,proto,pbtxt,pb.txt,config cuda_gpu_id device_id codemod with 'Yes to all' Reviewed By: orionr Differential Revision: D9986213 fbshipit-source-id: f5614a5d26078817aee8caf79a494abfd6a95ff1
62 lines
2.8 KiB
Python
62 lines
2.8 KiB
Python
## @package onnx
|
|
# Module caffe2.python.onnx.backend_rep
|
|
from __future__ import absolute_import
|
|
from __future__ import division
|
|
from __future__ import print_function
|
|
from __future__ import unicode_literals
|
|
|
|
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 = [self.workspace.FetchBlob(name)
|
|
for name in self.predict_net.external_output]
|
|
return namedtupledict('Outputs',
|
|
self.predict_net.external_output)(*output_values)
|